The AI Adoption Podcast

Organisations selling AI-powered election-winning services are operating openly. Deep fakes can place words in the mouths of public figures before any rebuttal reaches its audience. An estimated 95% of content on social media carries some form of AI manipulation. These are not hypothetical futures; they are the present.Dawn Butler, Member of Parliament for London’s Brent East constituency and member of the Speaker's AI Commission, makes the case that the greatest risk is not the technology itself: it’s the historical bias embedded in the data that trains it.Dawn argues that every data set carries a history, and that history in policing, health and public life is one of structural inequality. Building AI on top of that history does not neutralise it; it amplifies and automates it. She also challenges the widely held assumption that regulation stifles innovation, contending instead that an ethical regulatory framework will become a mark of quality that organisations and citizens will actively seek out. The conversation also covers what it means to be human in an age of artificial intelligence, and why teaching children to think critically is one of the most important acts of democratic resistance available to us today.Highlights• Facial recognition systems have an inbuilt bias and still produce misidentifications even at optimised accuracy thresholds.• BMI, used routinely in clinical settings, was derived from measurements of roughly 2,000 white men and was never designed for medical application.• Denmark has legal protections for citizens' intellectual property and voice that the UK does not yet provide.• Dawn argues that companies should be fined in a meaningful way to create real accountability, using the analogy of the seatbelt as a model for safety regulation that does not prevent progress.If you lead an organisation that uses data to make decisions about people, this episode sets out why the provenance of that data is not a technical detail. It is a governance responsibility.Chapters 00:00 The Evolution of Data and Ethics02:04 AI's Impact on Democracy and Human Rights05:50 Guarding Against Misinformation and Deep Fakes12:26 AI in Policing: Risks and Benefits15:45 The Responsibility of Tech Companies20:41 The Need for Regulation and Legislation22:25 Balancing Innovation and Regulation23:54 The Human Element in AI29:47 The Role of the Speaker's AI Commission

The companies driving the AI revolution are spending more on infrastructure this year than they earned last year. The contracts that justify those investments have not yet been fully realised. And somewhere in the middle of that gap sits a question that no analyst, executive or policymaker has cleanly answered: is this a sustainable expansion, or the largest technology bubble ever constructed?Tom Parker, independent financial journalist and contributor to the Financial Times, the Centre for European Policy Studies, and leading legal and accountancy organisations, argues that the answer depends almost entirely on whether AI adoption in the real economy keeps pace with the infrastructure being built to support it.The conversation covers the nature and scale of the current AI valuation environment, drawing direct comparisons with the dot-com era. It examines the staggering capital requirements of the data centre build-out and the energy demands that follow, including OpenAI's projection of needing 250 gigawatts of compute power by 2033. It addresses the specific sovereignty risks facing the UK, including the NHS-Palantir contract and what it reveals about Britain's dependence on American platforms. It tackles the future of work through a lens that is personal: Tom reflects on the risk AI poses to his own profession, as a journalist and podcast host.Highlights from the conversation:• Amazon, Google, Microsoft and Meta are each expected to spend over $100 billion on infrastructure this year, equivalent to 50% of their prior year revenues. Meta has had to take on debt financing despite earning $200 billion last year.• Sam Altman has projected OpenAI will need 250 gigawatts of compute power by 2033. That is the current total energy consumption of India and would produce twice the CO2 output of ExxonMobil.• A pixel AI tool for skin cancer detection reached 97% accuracy, ahead of top clinicians, but its training data was overwhelmingly Caucasian. For other ethnicities, accuracy dropped sharply, illustrating ethical dangers of AI and why the human expert cannot yet be removed from the loop.• The NHS holds cradle-to-grave health data on every citizen in the UK. Without a sovereign AI capability to use it, that data will pass to foreign platforms, potentially at enormous future cost to the public purse.• Voice cloning now requires just three seconds of audio to replicate a voice at 80 to 90% accuracy. Two years ago, it required three minutes.This episode is essential listening for any leader trying to understand not just the promise of AI, but the economic and geopolitical architecture that will determine whether that promise can be kept.Chapters00:00 The Complex Compute Value Chain05:46 Investment and Infrastructure in AI12:03 Societal Impact and Adoption of AI17:58 Energy Demands of AI24:06 AI Sovereignty and Ethical Considerations30:14 The Future of Work in an AI-Driven World

The gap between AI capability and workforce readiness is widening. Billions are flowing into AI models and data centres, yet the people expected to use these tools remain largely untrained, unsupported, and very exposed. That gap, left unaddressed, could trigger a wave of job losses more severe than anything seen since deindustrialisation in the 1980s.Euan Blair, Founder and CEO of Multiverse, makes the case that AI skilling is not a technology problem. It is a people problem, and one that generic training courses will never solve.Euan argues that worker in every sector need a meaningful, practical understanding of AI, not just technologists. He challenges the idea that handing AI adoption to a learning and development team is sufficient. He argues that contextualised, on-the-job training is the only route to productivity gains organisations are chasing. He sets out real dangers facing workers aged 40 to 49, currently the most productive demographic yet the most overlooked when it comes to AI reskilling. And he makes a direct challenge to boards: the question is not whether to invest in AI skills, but whether leaders will act now or wait until the damage is done.Highlights from the conversation:• An NHS worker at the Royal Free Hospital digitised the patient journey using AI, doubling the daily department caseload and cutting patient waiting times by a third• A council worker built an AI triage process that spots invalid eviction notices in seconds, preventing homelessness and saving the council significant resource• The OBR estimates AI could add tens of billions to UK GDP in the coming years, but a 25-to-30-year adoption cycle is possible if training is not urgently prioritised• The workforce is bifurcating between those with genuine AI skills and those without. Organisations face the same divide• Boards must stop measuring AI adoption through licence activations and hour utilisation and focus instead on tangible outcomes tied to cost, revenue, and missionThis episode is essential listening for any leader who wants to understand AI adoption and its actual requirements of their organisation and their people.Chapters: 00:00 AI and Workforce Transformation02:55 The Evolution of Skills in the AI Era05:59 Job Displacement and Human-AI Collaboration09:07 Supporting Early Career and Mid-Career Workers11:54 The Role of Leadership in AI Adoption15:05 Measuring Productivity Gains from AI17:49 The Responsibility of Training and Reskilling20:50 Long-Term Strategies for AI Integration23:57 Preparing for the Future of Work with AI

Hollywood is not being disrupted quietly. A 12-year-old with a laptop has the potential to produce a film that rivals studio budgets. The traditional linear franchise model, from comics to cinema to merchandise to theme parks, is giving way to something far less predictable and far more open.Samantha Tauber, Founder of VNCCII and creator of a science futures franchise that spans music, storytelling, animation and world-building, makes the case that AI does not replace human creativity. It radically expands who gets to participate in it.Samantha is building her franchise around a single principle: human-created seed intellectual property sets the intention, the values and the creative lore of a story world. Generative AI then becomes the scalability engine, producing derivative content, spin-off characters, localised narratives and interactive storylines within those brand guardrails. The community of fans and co-creators can contribute to and potentially earn from the story itself.The conversation moves from the practical to the profound. We discuss how IP can be protected when the floodgates are already open. There are precedents such as the OpenAI and Disney licensing deal for independent creators. Samantha believes transparency about AI use is both an ethical obligation and a creative asset.Key highlights from this episode:• Why Samantha describes AI as a symbiotic partner in idea generation rather than a replacement for human originality• How the "dynamic mythos engine" model creates four revenue layers: seed IP, AI derivative content, a story platform, and a licensing and monetisation architecture• What the Grimes Elf.Tech experiment revealed about community-led creative licensing• Why Ben Affleck's deal with Netflix and the company Interpositive signals a shift in how Hollywood itself is beginning to respond• How Samantha's first novel is being laser-etched onto nano material and sent to the moon aboard a SpaceX Falcon 9 rocket, as part of the first Galactic Library Preservation for HumanityThis episode is for anyone who creates, commissions, funds or leads in a world where the tools of production no longer belong exclusively to the few.Chapters00:00 The Democratisation of Creativity03:06 AI as a Catalyst for Creative Innovation05:48 Building a Nonlinear Creative Model08:55 Understanding the Dynamic Mythos Engine11:55 Intellectual Property in the Age of AI15:07 The Future of Hollywood and New Creative Legacies18:01 Creating a Legacy Through Storytelling

In this episode, I speak with Eric Tyree, Head of Data and AI at Virgin Media O2, about a reality many organisations are still avoiding. AI adoption does not start with technology. It starts with pressure in the market.Eric describes a telecoms sector where services are commoditised, margins are tight, and customers are quick to leave. That context shapes everything at VM02. AI is built directly from corporate strategy, with a clear focus to improve efficiency under price pressure while creating meaningful differentiation through personalised service.This leads to a very different approach. AI is treated as transformation, not tooling. Every initiative is tied to changes in processes, skills, and operating models. If those do not shift, the technology delivers little value.We explore voice interfaces that now rival call centres and enable personalised offers at scale. This is leading to a more subtle shift inside the organisation. Productivity tools are available to everyone, yet adoption is uneven because training alone is not enough. Real gains come when roles are redesigned and ways of working are deliberately changed.There is also a strong message on culture. Data-driven decision making at VM02 has become embedded to the point that poor data disrupts the business. The same intentional effort is now being applied to AI.I highlight one important message. Technology and transformation are not separate programmes. They succeed or fail together.This is a grounded account of AI adoption inside a large organisation that is under real commercial pressure and responding with discipline.Chapters00:00 AI Strategy Aligned with Business Goals02:01 Framing AI Adoption in Telecommunications05:12 Key Initiatives Driving AI at VM0209:03 Enhancing Productivity through AI Tools13:01 Cultural Transformation through Data Democracy18:04 Integrating Transformation with Technology23:31 Lessons Learned in AI Implementation25:59 Advice for Organisations Starting Their AI Journey

In this episode, I speak with Janusz Marecki, AI Partner at Ahrens, and the conversation cuts through the optimism that often surrounds AI.Janusz sets out a clear position. Current AI systems have fundamental shortcomings. They approximate answers rather than produce deterministic outcomes. Every token carries a probability of error, and those errors compound as outputs grow. This is not a marginal issue. It is embedded in how AI systems work.He also challenges a widely held assumption. AI systems are not continually learning from experience or new data. Once training stops, their knowledge is fixed. Attempts to update them through external data can introduce contradictions rather than resolve gaps. This creates the conditions for hallucination and, consequently, undermines trust.Enterprises are adapting through agentic systems. By breaking tasks into smaller components and orchestrating multiple models, organisations are improving performance. This comes at a cost because AI systems become more specialised and less general. The promise of broad applicability begins to narrow.Human oversight remains central. In mission critical environments, outputs need to be verified, either by people or by deterministic systems. Without this, reliability is insufficient. With it, the efficiency gains begin to erode.The implications extend to the workforce. Entry level programming roles are already being automated. Yet these roles are essential for developing future expertise. Removing them risks creating a structural gap in capability over time.Janusz draws a sharp distinction. There is real value in today’s AI applications. That is not in question. But expectations around artificial general intelligence are misplaced. Achieving AGI will require fundamentally new advances, not incremental improvements to existing models.This is a conversation grounded in reality rather than projection.Chapters00:00 The Shortcomings of Current AI Systems02:32 Reality Check on AI Adoption05:57 Understanding Errors in AI Outputs11:02 The Role of Agentic AI Systems14:49 Humans in the Loop: Necessity or Burden?17:49 The Future of Programming Jobs19:14 AI Bubble vs. AGI Bubble21:18 Defining Artificial General Intelligence22:42 The Role of an AI Partner25:12 Investments in Innovative AI Startups

In this episode of The AI Adoption Podcast, I speak with Sahar Danesh from the British Standards Institution about the role that standards play in the adoption and governance of artificial intelligence.Many organisations are racing to adopt AI. Productivity gains and competitive pressure are driving large and rapid investments. Yet this conversation revealed a striking gap between adoption and governance.Sahar shared findings from a BSI study showing that fewer than a quarter of organisations reported having a formal AI governance programme. Many employees are already using AI tools without formal oversight. Only a small proportion of organisations have clear processes governing confidential data used for AI training.This creates a growing governance gap. As Sahar says: Businesses are investing heavily in AI without always considering the risks they are opening themselves up to.Standards exist to address precisely this challenge. International AI standards such as ISO/IEC 42001 provide guidance for responsible use of AI and support transparency in decision making. These standards are already being adopted globally, yet many organisations still view standards as bureaucracy rather than operational tools.Sahar argued that this perception is mistaken. Standards are not barriers to innovation. They provide the common language that enables organisations to collaborate across borders and operate confidently within global supply chains and strong ecosystems.She also highlighted a deeper issue. AI governance is often treated as a technical responsibility, yet AI affects every department within an organisation. Governance frameworks therefore require engagement across the business together with training and AI literacy.One warning stood out clearly in our discussion. Organisations risk sleepwalking into a governance gap if enthusiasm for AI outpaces oversight. According to Sahar, standards provide a practical route for organisations to close that gap while building trust with customers, regulators and employees.This conversation offers a valuable perspective on AI governance at a time when organisations are investing heavily in AI but still searching for structures that ensure it is used responsibly and ethically.Chapters00:00 The Role of AI in Business Productivity03:33 BSI's Contribution to AI Standards06:39 Global AI Regulations09:27 Balancing Business Needs and Consumer Protection11:52 The Importance of AI Governance13:50 Standards vs. Innovation: A Misconception16:02 The AI Standards Hub and Its Impact18:39 Integrating Standards into Governance Frameworks24:28 Practical Advice for AI Governance

This is for anyone recruiting or looking for a job or a new role. In this episode of The AI Adoption Podcast, I speak with Annabel Ashley from Indeed about AI adoption where it matters most, inside day-to-day operations at the sharp end of hiring.Indeed is already an AI-enabled organisation. Annabel shared that over 70% of Indeedians use AI at least weekly, and over 80% say it adds value to their working day. They have a ‘function first’ approach, as teams adopt tools that fit their work, rather than a single top-down rollout. In her role in government relations, AI helps Annabel track legislation and compare timelines quickly. Engineers use coding assistants and reported saving around four hours a week. Customer service teams use AI to build product mock-ups and create before and after performance summaries for clients, even though they do not see themselves as technical.We discussed the recruitment process itself. Annabel’s view is that recruiters needs to move away from CV-based hiring towards skills-led, capability-based recruiting. That shift tackles the growing problem of candidates using AI to polish applications while employers use AI to screen them. A skills-first model reduces the risk that good candidates are filtered out because of language, formatting, or miscommunication.On responsible AI, Annabel described Indeed’s principles, including jobseeker-first, fairness and equality, hiring as human, and innovating responsibly. The operational point was ‘human in the loop’, keeping judgement with people, supported by governance that adapts with ethics, regulation, and technology.We closed on future skills. Annabel emphasised communication, problem solving, and emotional intelligence, plus a mindset of lifelong learning. The argument was practical: AI may automate routine tasks, yet the advantage stays with people who can adapt and work well with others.Listen to the episode for an in-depth view of AI in hiring, with the labour market context Indeed sees in real time.Chapters00:00 AI's Impact on Employment and Skills03:11 Indeed's AI Integration and Employee Experience07:08 AI Efficiency vs. Human Creativity08:22 AI in Hiring: Streamlining the Process10:17 Maintaining Human Connection in AI Hiring11:57 Ethics and Transparency in AI Use15:35 Transformations in Work Practices18:25 Future Job Market Dynamics21:58 The Role of Agentic AI23:30 Shifting from CVs to Skills-Based Hiring25:12 Essential Skills for Future Employment27:52 The Value of a Diverse Workforce

In this episode of the AI Adoption Podcast, I speak with Chelsea Chamberlain, Chief Technology Officer at Roc Technologies, about to get an in-depth understanding of AI adoption across the UK public and private sectors.Chelsea sees a clear divergence in pace. Private sector firms in sectors such as banking, legal and pharmaceuticals are accelerating. Public sector organisations, on the other hand, remain constrained by cost, cyber risk and the need to demonstrate short term savings. Yet when public bodies do invest, they are often more disciplined and focused because they cannot afford experimentation or, as she says, throw AI spaghetti at a wall and hope something sticks.A recurring theme in organisation coming to AI is fear rather than resistance. CIOs don’t want to commit scarce funds to AI tools that could be redundant in months. Customers are cautious about long term managed service contracts because few believe the current answer will be the final answer.Service desks are evolving. AI is improving root cause analysis and first line troubleshooting, yet the lack of interoperability between vendor tools means human accountability still matters. As agentic AI and open standards mature, that balance may shift in favour of AI and the need for fewer people.Boards, in Chelsea’s view, are not yet treating AI as a board level mandate. Instead of reshaping operating models, many organisations are layering tools onto existing processes. That approach risks missing the structural shift AI is likely to drive.We also discuss sovereign AI, geopolitical risk, the UK’s position relative to global tech powerhouses, and the pressure on data centres and energy infrastructure. This is a grounded discussion about risk, cost, capability and leadership.

AI “of the people, by the people, for the people”. I’ve taken the words from the closing lines of Lincoln’s Gettysburg Address to describe my discussion with Josh Tan from Public AI.Josh argues that AI should be treated as public infrastructure, closer to railways, highways, libraries, utilities, and the internet than to a premium service owned by a handful of companies. The context is stark. Two or three firms dominate the global consumer chatbot market. These systems are becoming critical for industry and social culture.The issue is power. A small number of companies have gained not only commercial concentration, they have significant cultural concentration. British culture, Swiss culture, or Swedish culture is increasingly mediated through models built and controlled elsewhere. This leaves local language, norms, and identity at risk: to be shaped by external defaults. Josh points to Switzerland’s Apertus model as an example of a sovereign model designed to reflect multilingual and culturally specific patterns, including Swiss German.Governments are investing heavily in data infrastructure, compute, and model development for public benefit. Public AI aims to provide a public alternative in what is rapidly becoming not simply an AI market but an AI oligopoly. Ethics, responsibility and accountability on the part of AI providers matter as much as model performance.Geopolitical tension is accelerating interest in sovereign and public AI. As dependencies become visible, country autonomy in critical technology becomes a strategic priority.This episode explores whether AI can genuinely be built and governed for the benefit of citizens rather than concentrated private power.Chapters00:00 The Concept of Public AI02:59 Global Models of Public AI05:56 The Importance of Public AI09:02 Public AI vs Open Source AI11:49 The Flywheel Effect in AI Development14:54 Sovereign AI and Public AI17:23 The Role of Public AI in Cultural Preservation20:27 Challenges of Sovereign AI23:15 The Future of Public AI

AI adoption in financial and professional services is being sold as a technology story. Olivia Larkin makes the case that it is really a workforce transformation story. In her words, ‘AI transformation is change management and it needs to be managed in that way by a business.’Olivia leads skills and workforce policy at the City of London Corporation. She works across the UK, not just the Square Mile. She makes an interesting distinction between AI talent, a narrow, deep group that builds, governs, assures, and improves AI. Whereas, AI skills are for the wider workforce, because AI use will spread across all functions in organisations.She argues that one of the biggest AI risks is not investing in upskilling. Only around one in five UK employees currently receive AI training. Time is the everyday blocker, for employers and employees. Protected learning time changes the picture.Regulation also slows momentum. Firms face uncertainty when existing regulatory requirements meet new AI use, with grey areas that create caution and delay.Olivia still lands on a positive position. With responsible governance, AI can lift productivity and improve customer experience. The prize comes with a condition. Focus on redeploying people, not reducing headcount. Build trust, so staff do not see learning as a route to replacement.London, in her view, can become a global reference point for trusted AI in financial and professional services, if workforce investment keeps pace with the technology.Chapters00:00 The City of London Corporation03:33 Skills and Workforce Policy in Financial Services06:18 AI Skills vs. AI Talent11:01 Challenges and Risks for Companies17:09 Employee Challenges in AI Adoption20:06 Regulatory Challenges in Financial Services23:27 AI's Impact on London's Future27:47 Successful AI Strategies in Organisations30:42 Future Directions for AI Adoption

In this episode of The AI Adoption Podcast, I speak with Sumeet Bhatia from Cisco about the changing role of AI in defence and security. The discussion stays close to operational reality rather than abstract theory.We explore how AI now operates at a speed that humans cannot match. That speed allows threats to be detected earlier and systems to respond before damage spreads. At the same time, it creates new risks around trust and control. Sumeet explains that data purity, provenance, and governance are not technical hygiene issues but strategic and operational warfare necessities.Data integrity runs through the entire conversation. Poisoned data can quietly distort AI behaviour, while misinformation can undermine confidence in the information presented to human decision makers. In defence environments, that loss of confidence can be as damaging as the attack itself.Explainability becomes critical when decisions carry serious consequences. Opaque models make it difficult to understand how conclusions are reached. Without clear decision trails, accountability weakens and trust erodes under pressure.We also discuss the rise of multi-vector attacks. Disruption no longer arrives through a single route. Infrastructure, cyber systems, and information channels can all be targeted together. AI helps by recognising patterns across these fronts before instability escalates.The episode also looks at AI in operational contexts. Defence logistics faces challenges similar to large commercial supply chains. AI can support planning, predict failure points, and improve crisis response when conditions change quickly.Lessons from defence extend well beyond the military domain. The need for speed must be balanced with verification and human judgement. Policy continues to struggle to keep pace with technical capability and developments.Human oversight remains essential where lethal decisions are involved. Looking ahead, effective human–AI teaming will depend on new training approaches and a serious investment in skills.Chapters00:00 The Rise of Autonomous Cyber Warfare03:00 AI in Defence and Security05:58 AI's Role in Threat Detection08:57 Human-AI Collaboration in National Security11:59 Data Integrity and Misinformation Challenges14:50 The Explainability Crisis in AI17:40 Multi-Vector Attacks and Their Implications20:54 Operational Enhancements Through AI23:59 Lessons from Defence for the Private Sector27:02 Policy Considerations for AI in Defence30:02 The Future of Human-AI Teaming

Cash transactions are disappearing fast in the UK, but five million people still rely on cash payments. That tension sits at the heart of this episode.In my conversation with John Howells, Chief Executive of LINK, we explore the sharp fall in cash use, from six in ten payments a decade ago to fewer than one in ten today, and the consequences that follow. For most people, digital payments bring convenience and choice. For others, the elderly and those less comfortable with technology for instance, the pace of change creates real risk.John explains that cash infrastructure declines faster than people adapt. As usage falls by around ten per cent a year, ATMs, branches and cash accepting shops disappear unevenly. Banking hubs emerge as a practical response, shared branches on the high street that protect face to face access when the last local bank branch closes.We also look ahead to digital money. Stablecoins, tokenised bank deposits and central bank digital currencies point to a future where payments carry richer data and support smarter services. That future brings opportunity, including reduced fraud and more flexible support for vulnerable users, but only if inclusion is designed in.A striking argument in this episode is about responsibility. John suggests that banks should not carry the cost alone. Large technology firms such as Amazon, Meta and Google also benefit from the shift to digital payments and should contribute to sustaining the system that underpins it.This episode is a reminder that payment systems are part of the social infrastructure and community fabric, not just technology.Chapters00:00 The Cash Dilemma: Understanding the Need for Cash in a Digital World03:00 The Evolution of Payments: From Cash to Digital06:07 The Vulnerable Population: Who Are the 5 Million Cash Users?08:45 The Role of Technology: Bridging the Gap for Cash Users11:58 Banking Hubs: A Solution for Access to Cash14:52 The Future of Payments: Trends and Predictions17:55 The Impact of Digital Payments on Society20:49 The Role of AI in Financial Inclusion23:50 The Multi-Money Approach: Stablecoins and Digital Currency26:42 Preparing for the Future: What Companies Should Do

In this episode of The AI Adoption Podcast, I speak with Sydney MacGregor from HSBC Innovation Banking about a critically important aspect of AI adoption: funding, risk, and scale.Sydney works with more than 250 enterprise software companies, most of them building AI into their core products. She shares a clear view of the UK AI market, from the surge in early-stage activity to the harder reality of scaling beyond Series A.We discuss the rise of AI agents over chatbots, investor expectations shaped by rapid revenue growth, and the pressure founders face when competing with businesses scaling from zero to tens of millions in months. Sydney explains why later stage funding remains a structural weakness in the UK, even with strong research, talent, and early capital.The conversation moved onto venture debt, an area that often feels opaque to founders. Sydney explained how banks assess risk in AI businesses that can be cash-burning, the importance of investor syndicates, and the need to avoid over-leveraging while still enabling growth. We explored the role banks play supporting their AI businesses beyond capital, including global expansion, sector expertise, and trusted relationships.We close with a forward look at workflow automation, AI governance, and the conditions needed for UK AI companies to scale and stay in the UK.This episode is a rich discussion about growth, discipline, and realism in the AI economy.Chapters00:00 The Future of AI in Corporate Workflows03:05 Current State of AI Companies in the UK07:08 Government Support and Investor Appetite09:46 Investment Trends in AI Sub-sectors12:10 Regional Investment Expansion Beyond London14:16 Ensuring the UK Remains an AI Hub15:58 Supporting AI Startups Beyond Capital22:18 The Lifecycle of AI Startups27:32 Key Trends and Future Opportunities in AI

This episode with Chris Blatchford, CTO at Kingfisher, quickly became a conversation about leadership mindset and AI technology. Kingfisher is best known through its brands such as B&Q and Screwfix.Chris described an organisation that treats AI as a board-level capability. Foundations first, so teams can build safely and repeatedly rather than improvising. Kingfisher’s data lake, Nucleus, and its AI framework, Athena, sit underneath everything. That choice signals discipline and intent. AI becomes an operating model, not a sequence of use case pilots.From there, the focus shifts to customer focused innovations, personalisation and value, not superficial novelty. Customer-facing AI stays anchored in a simple outcome: customers reach the right product fast. Chris spoke about moving beyond keyword search towards conversational and semantic search, then using context such as prior searches, purchases and loyalty behaviour to sharpen relevance. He shared a hard-edged commercial marker too. Recommender systems contributed around 10% of e-commerce sales last year, with ambition to grow that through 2026.For boards, the supply chain segment will resonate. Chris described near real-time visibility at SKU level, including fulfilment timing and shipment progress, supporting faster decisions on replenishment and stock gaps. It is operational clarity in a world full of noise.Chris declared that ensuring Kingfisher rolled-out AI responsibly as one of the areas, alongside cybersecurity, that genuinely keeps him awake. Again, this reflects the depth of commitment to good AI governance, bias checks, explainability, controlled customer roll-outs, plus tech-literate executives who press on risk as well as upside. Innovation is encouraged, within a bounded context with rules.His view on AI’s impact on jobs and skills was measured and human-centric. AI tools support colleagues rather than remove them, freeing time for higher value work. Roles evolve through better prompting, stronger curation of information, and sharper critical thinking, with data-savviness becoming essential.This episode is for boards and senior teams who want to scale AI adoption that holds up under scrutiny, delivers value, and earns trust.Chapters00:00 AI in Retail02:57 Kingfisher's AI Strategy and Innovations06:08 Enhancing Customer Experience with AI08:47 Dynamic Pricing and Its Implications11:49 Supply Chain Visibility through AI14:45 Responsible AI Implementation17:55 Impact of AI on Jobs and Workforce20:47 The Effects of AI on Retail Jobs23:49 Skills for the Future Workforce26:56 Supporting SMEs in AI Adoption29:41 Advice for Large Organisations on AI Adoption

Jonathon Palmer from LinkedIn and I spoke about creativity emerging as a serious competitive advantage in AI-driven business. Jonathon made a striking point: AI makes execution easier, so the advantage shifts to the human ability to originate ideas, reframe problems, and stay curious.The discussion also challenged a common assumption in B2B ecosystems. Emotion carries more weight than logic in real decisions. People engage Brands that help people feel confident in their choice will stand out in a world shaped by AI abundance, endless options, and fast decisions.We covered the changing landscape of work. A shift is underway from job title-based hiring to skills-based hiring. Jonathon shared LinkedIn data suggesting professionals entering work today will hold twice as many jobs as someone starting 15 years earlier. As AI adoption expands, careers adaptability and lifelong learning move from a nice-to-have to a baseline expectation.A theme running through the conversation was shared responsibility. Creativity no longer sits in a single department. It becomes everyone’s work, supported by psychological safety, rigorous experimentation, and high standards.This episode brings together creativity, emotional intelligence, confidence in brand decisions, skills-first careers, and the real tactics people can use to stay visible and employable as AI reshapes work and workplaces.Chapters00:00 The Importance of Creativity in Business09:54 The New Marketing Landscape20:05 The Evolution of Brand Identity29:59 Adapting to the Future of Work

As 2025 ends, thanks to everyone who joined The AI Adoption Podcast. A recurring message is: AI adoption isn't a technology issue alone; it is a strategic transformation, leadership, and human challenge.Regulation & Trust• Regulation isn't the enemy of innovation Lord Tim Clement-Jones• AI adoption only works at scale when regulation is coherent, trusted, and designed to enable innovation, not fight it Kate Jones• Blindly adopting technology you don’t fully understand is dangerous Sunaina Aytan• The danger is trying to legislate something you don’t fully understand Konrad Shek• The UK’s light-touch approach supports innovation but risks leaving safety to those least equipped to manage it Dr Madeline Cheah (谢涵馨)Leadership & Readiness• Board members must think about productivity of their human workforce alongside their digital workforce Zahra Bahrololoumi CBE• AI readiness depends on leadership, team culture, data and documented operations Andrew McNally• AI tools are useless if not integrated into an effective business strategy Matthew Houlihan• AI isn’t a tech problem: it’s a human problem ⚡ Ben JohnsonWork & Change• You can optimise a process with AI, but you can't automate a relationship Neha Kabra• People fear losing jobs, but many AI projects fail because companies ignore change management Heather Black• The business case behind AI technology is human displacement Ian Smith• Agentic workflows create space for humans to focus on meaningful, rewarding tasks Paul O'SullivanData & Truth• There’s no AI model that doesn’t hallucinate Hamzah Malik• If our civilisation lets go of a notion of truth, we will be in fantasy land Lord Bishop Steven Croft• We risk AI model integrity if we don’t protect human-created data Allison Gardner MP• Everyone wants better AI outputs, no one wants to fund the inputs Alex DalmanAdoption at Scale• AI's transforming shipping, agriculture, and professional services, it’s happening now Marco Forgione MCIEx• We spent £113m across the NHS, but pilots don’t always lead to adoption Alex Cole• Some organisations are waiting to see what others do, the longer they wait, the further behind they get Jenna Shanks• Whatever model you used last month is already outdated Nikolay BurlutskiyLooking ahead• We’re in the first wave of adoption. The next wave's transform businesses, then create new ones Lord Kulveer Ranger• Managers need to manage agentic AI that’s in their team Sue Daley OBE• If we can build machines that learn, adapt and act, we can learn to become more human Maggie Sarfo• In an agentic economy, companies, not big tech, are in the driver’s seat Yves BollingerThanks to guests, listeners, and colleagues at Brunel Business School and the Centre for AI Social and Digital Innovations Brunel University London, with special thanks to Vimal Dalal and Eliza Kania.The conversation continues in 2026.Wishing you joy at Christmas and every success in 2026.Ashley

AI adoption often looks rational on paper while feeling human in practice. That insight sat at the centre of my conversation with Ian Smith from Baseline, and it informed the tone of our discussion.Ian spoke about reaching a point in his career where technology no longer carried the whole story. Lived experience moved to the forefront. People bring anticipation, uncertainty, curiosity and concern to AI programmes. These emotions shape AI adoption as much as any technical roadmap.Efficiency continues to matter, yet it arrives with consequences. Organisations gain speed and clarity, yet roles evolve, responsibilities shift, and expectations change. Vision sets direction, yet lived experiences determine whether progress becomes real or remains notional.Ian shared his views around personal agency. AI now gives individuals the ability to build, learn and create with a freedom that previous technologies didn’t allow. AI systems offer new routes into capability development and new forms of contribution that feel empowering.That momentum brings a parallel challenge. As personalised, agentic systems expand, boundaries around trust and control begin to stretch. Organisations face new questions about governance, oversight and responsibility when capability sits outside the structures that once shaped it.Trust carries real weight in this moment. Trust in systems, trust in data, trust in human judgement. The balance between them influences decisions, interactions and outcomes. Automating trust remains far more complex than automating efficiency.Ian finished by returning to something firmly human. Augmentation has always been part of the human story. The deeper fulfilment still comes from connection, shared presence and the moments that remind us we remain social beings even as digital intelligence becomes more present in our lives.This episode offers a steady, balanced view of AI adoption. It acknowledges the trade-offs while recognising the possibilities, and it invites listeners to consider both with clarity and care.Key messages• The lived experience around technology is crucial for organisations.• Leadership should focus on accountability and adoption, not just vision.• AI adoption is as much about people as it is about systems.• Trust and ethics are paramount in the deployment of AI.• The consumer-centric approach is reshaping technology services.• AI can empower individuals to customise their own solutions.• There is a paradox in AI replacing human jobs while creating new opportunities.• Human diversity must be preserved in the age of AI.• Ethical governance is essential for AI systems.• Maintaining human connection is vital in a technology-driven world.Chapters00:00 The Human Experience in Technology03:03 Leadership and Accountability in Technology Adoption05:37 The Paradox of AI and Human Displacement08:43 Consumer-Centric Technology and Customisation11:26 Trust, Ethics, and Governance in AI14:17 The Future of Work and Individual Agency16:52 Balancing Technology and Human Connection21:14 Tacit Knowledge and AI24:09 Governance and Shadow IT27:50 Augmenting Knowledge32:07 Retaining A Sense of Humanity

In this episode I speak with Paul O’Sullivan, SVP of Solution Engineering for the UKI and Chief Technology Officer for the UK, from Salesforce. Paul traces 75 years of AI development, from early machine intelligence ideas to the breakthroughs that brought us to today’s agentic AI era. Paul explains the shift from traditional workflows to digital workers operating alongside people. AI-enabled reasoning, automation and data-driven decisions now open space for employees to focus on meaningful tasks rather than repetitive activity.Paul outlines the elements senior managers must consider when forming an AI strategy. These include ethics, workforce readiness, data quality, resilience and long-term sustainability. He stresses that many AI pilots collapse because they lose focus on business value or fail to carry teams with them.Data chaos is common in many organisations and progress is possible by concentrating on workflows rather than attempting a huge enterprise-wide data project. Paul explores the dark side of AI, including malicious code, deepfakes, identity theft and large-scale misinformation. Boards need clear oversight and consistent guardrails.Paul discusses the build–buy–hybrid debate. The rapid cycle of AI development, model updates and new controls means few organisations can produce everything alone. Choice of partners becomes critical.We end the conversation with Paul’s view of near-term AI advances: robotics with touch-sensing algorithms, multimodal models, self-adjusting systems and strong growth in sectors such as logistics, healthcare and financial services. In two years from now, will the landscape be almost unrecognisable?

In this episode of The AI Adoption Podcast, I speak with Heather Black, CEO of Supermums. Heather created Supermums after realising that a flexible, well-paid career in tech was something many mothers could thrive in. Heather explains why she focuses on this demographic. Women remain under-represented in tech, many struggle to return to work after raising children and the gender pay gap persists. We discuss how jobs are changing due to AI. Heather argues that AI is creating new roles, not just replacing old ones, and shares examples of project managers, business analysts and technical specialists that are already working differently when they use AI tools effectively.“Some roles will go. The question is whether we help people move into the roles that are coming.” Heather BlackHeather sets out changes to employers’ expectations in the workplace. Companies now look for candidates who can use AI to work more efficiently. She identifies fear as a factor that holds people back and suggests that community-based learning helps individuals overcome that fear and adapt more quickly.We talk about change management, the importance of enthusiasm, engagement and empowerment and that good training must be designed around different learning styles. We discuss the rise of AI agents, and what needs to happen for people and AI-technologies to work effectively together. Heather offers a policy perspective on ways in which government can help ensure people are not left behind as AI reshapes work.Heather shares practical advice on future-proofing skills. This is a grounded and encouraging conversation about skills, confidence and helping people embrace an uncertain future.Chapters00:00 Empowering Women in Tech04:07 Adapting to Changing Job Landscapes07:01 Upskilling for the Future11:21 AI in the Workplace14:42 The Importance of Change Management18:21 Continuous Learning as a Core Competence21:23 Learning Styles and Personal Responsibility26:05 The Role of Leadership in AI Adoption31:30 Government Policies for AI Workforce Development

In this episode of The AI Adoption Podcast, I speak with Neha Kabra from McKinsey about how AI is reshaping leadership, customer service, employees’ roles and the expectations placed on boards.Neha explains why legacy leadership approaches are struggling. Many leadership skills remain the same, but the speed of decision making has changed. Early movers are already seeing returns, while others remain stuck in pilots that do not scale.We look at the balance between AI, customer service, productivity and staffing. A European bank improved productivity and raised its customer satisfaction by eight points. Klarna cut 700 roles and relied on AI alone, but later reversed course when customers needed empathy that a chatbot could not provide.Neha outlines three actions that help people and AI work together: clear role and responsibility boundaries, better trust and auditability, and training so teams feel confident using AI.We discuss the impact on jobs, why some roles will change and why AI is likely to create long-term value. Neha also explains that many pilots fail because of weak data foundations, unclear organisational ambition and a tendency to build broad horizontal AI tools instead of vertical use cases. As she puts it, your AI deployment is “as good or dumb as the data that sits behind it”.Neha talks about three types of AI organisations: AI first, human augmented and AI augmented. She sets out what boards should focus on and why they need to adjust their risk appetite when considering AI adoption.We also cover the role of partnerships with organisations such as OpenAI, Anthropic, Cohere, AWS, Azure, Salesforce and ServiceNow. Neha ends with advice for young people on how to future proof themselves by building AI foundations, human skills and a T-shaped profile. An important reminder that depth of knowledge and subject area expertise will continue to matter.Chapters00:00 The Impact of AI on Legacy Leadership05:43 Customer Experience and AI Integration08:47 Employee Engagement and AI Augmentation11:46 Managing Human-AI Collaboration14:24 Balancing Productivity and Innovation17:16 Challenges in Scaling AI Pilots20:02 Key Priorities for Boards in AI Adoption22:45 The Role of Partnerships in AI Success25:57 Future-Proofing Careers in an AI-Driven World

I recorded this episode with Andrew McNally, who has spent 35 years working across fund management, investment banking and advising family offices. Andrew has witnessed several major technological shifts, including the dot-com boom and bust, and I wanted to hear his view on how today’s AI wave compares.Andrew spoke openly about the financial implications of foundational technologies. He explained why they trigger significant shifts in wealth and why markets often peak long before society feels the real impact of emergent technologies. In his view, today’s AI technologies are the equivalent of the old Sinclair ZX81 in terms of maturity. He argues there is still a very long way for AI developments to go.We discussed why many organisations are not yet seeing economic value from AI. Andrew highlighted research suggesting that most companies have yet to achieve measurable benefits. This isn't because the technology is lacking, instead, organisations are not ready. He described AI readiness as a combination of leadership mindset, team culture, data organisation and documented operations.We explored challenges in the UK funding landscape. Andrew raised concerns about the “valley of death” that UK scale-ups face. This is, in part, due to the longer-term decline in equity investment, the shrinking stock market, the lack of exit opportunities for early investors and the cultural shift away from risk taking. He reflected on the role of the British Business Bank, the Treasury and pension funds in shaping the future of UK capital formation for AI companies.This is a candid conversation about what needs to change if the UK truly wants to be an AI maker rather than an AI taker. Andrew brings historical insight and financial realism to a debate that often focuses only on the technology.Listen in if you want a grounded view of how AI adoption links to capital, culture and the long-term health of UK innovation.Key messages• Companies need to assess their AI readiness.• The valley of death for startups is a significant challenge.• UK capital markets lack large pools of risk capital.• UK cultural shifts towards risk-taking are essential for growth.• Creating pools of equity capital is necessary for supporting startups.Chapters00:00 AI and Financial Markets02:45 Historical Context of Technological Shifts05:53 Current State of AI Technology09:06 AI Readiness in Organisations12:07 Funding Mechanisms for AI Startups15:09 Challenges in UK Capital Markets18:02 Cultural Shifts in Risk-Taking20:55 Role of the British Business Bank24:02 Policy making and Capital Flow26:47 Future of Financial Markets and AI30:03 Conclusion and Future Outlook

In this episode of the AI Adoption Podcast, I interviewed Marco Forgione, Director General of the Chartered Institute of Export & International Trade. Marco’s extensive experience and knowledge provides deep insights into the strategic use of AI in international trade. He argues that AI is fundamentally changing international trade and provides examples such as companies like Maersk that are using AI for predictive logistics to AI-enabled customs systems in Kenya. We discuss the challenges faced by businesses, particularly micro, small and medium sized enterprises (MSMEs), in adopting AI technologies and ways in which business leaders can address these challenges. “AI is already transforming shipping, agriculture, and professional services, it’s not science fiction, it’s happening now.” Marco ForgioneOne area that often receives little attention is the impact of AI on professional services that support international trade. Jobs and employment in these sectors will be affected, as processes are automated and simplified, with the emergence, for instance, of fully autonomous supply chains, autonomous vehicles, ports and digital customs operations. Our conversation explores the regulatory landscape and the role of government policy in facilitating AI adoption to enhance trade efficiency and economic growth. This raises the risk of the UK and the EU being left behind considering competition from the US and China. For many organisations trading internationally, the cost and skills gaps are holding them back and there is a need for the UK to ensure joined-up policy making. Marco’s central point is clear: the technology is ready; what’s needed is leadership and political will.Key messages1. AI is not yet fully adopted in by the UK’s public and private sector engaged with international trade.2. MSMEs face significant barriers to AI adoption and need tailored support.3. Larger export trading businesses are leading in AI implementation.4. AI can optimise supply chains in many different sectors and reduce costs.5. Government assistance is required for MSME AI adoption.6. Autonomous systems in shipping, ports, warehouses, and transportation are changing logistics and supply chain operations.7. AI is rapidly transforming professional services that support international trade.8. Interoperability between systems is important to enhance trade efficiency.Chapters00:00 Introduction to AI in International Trade02:43 Current State of AI Adoption in Trade05:45 Challenges in Implementing AI08:58 Empowering MSMEs in AI Adoption11:39 Future of Autonomous Supply Chains15:01 AI in Professional Services19:55 Impact of AI on Employment22:40 AI in the Creative Sector26:00 Government Policy and AI29:00 Supporting MSMEs for International Trade

In this episode of The AI Adoption Podcast, I speak with Kate Jones, CEO of the Digital Regulation Cooperation Forum (DRCF), which brings together four regulators: Ofcom, the ICO, the CMA and the FCA to work together on regulating online and digital services. We discuss the work does with the Regulatory Innovation Office, which is part of the Department for Science, Innovation and Technology. DRCF’s influence extends internationally, as countries seek to learn from and emulate its best practices. We explore what it means to build public trust in AI, how “principles-based” regulation can make compliance simpler, and how regulators are learning to collaborate like doctors working on one shared care plan for the digital economy.We discussed:• Why regulation and innovation are not opponents but partners• How UK regulators support companies build compliance “by design”• The concept of smart data and its potential to open new markets for SMEs• What boards can learn from regulators about joining up compliance functionsFind out why Kate says: “if we get digital regulation wrong, the AI environment could end up dividing society rather than lifting it.”Listen in to understand how regulation and innovation can work together to create a trusted, thriving AI ecosystem.

🎧 In this episode of The AI Adoption Podcast, I speak with Yves Bollinger, General Manager at Plan.Net Studios, part of the Serviceplan Group. We explore the fascinating intersection of AI and blockchain and how decentralised technologies such as the Masumi Protocol built on the Cardano blockchain can establish trust, identity and accountability between millions of AI agents. We explore examples such as a team of AI travel agents planning a family trip entirely through autonomous negotiation, and how organisations can monetise their proprietary data by deploying agents in the Sokosumi marketplace. Yves discusses how these technologies could reduce reliance on big tech platforms and create a new, open and verifiable digital economy.We discuss how businesses, large and small, can build or buy their own AI agents to monetise their data. This will improve productivity at the possible cost of fewer entry level jobs. We examine how leaders can prepare for a future in which agents collaborate, trade and take actions without human intervention, leading perhaps to an “agentic economy”.Business Leaders and policy makers need to recognise that, as Yves says, “If we don’t find a way to integrate young people into the workforce, the expertise to oversee artificial intelligence will cease to exist.” Listen to the full episode to hear how agentic AI is transforming trust, commerce, and the very structure of online ecosystems.Key Messages• Blockchain is a decentralised ledger that ensures data integrity.• AI agents require a reliable identification system.• The Masumi protocol facilitates agent interactions on the blockchain.• Companies can leverage their data by creating their own AI agents.• AI agents combined with blockchain technology will change the way businesses interact with customers.• Small businesses can utilise agentic workers for efficiency.• Customisation of AI agents is essential for specific business needs.• The job market will shift due to the rise of AI agents.• Society must rethink taxation in light of reduced workforce participation.• AI and blockchain technologies are already impacting our lives today.Chapters00:00 Introduction to AI and Blockchain03:05 Understanding Blockchain Technology06:05 The Connection Between AI and Blockchain09:09 The Mazumi Protocol Explained12:12 Recent Developments in AI Agents15:04 Adopting AI Technologies in Organisations17:56 Utilising AI Agents for Small and Medium Businesses20:54 Customisation of AI Agents for Businesses23:50 Impact of AI on Job Markets26:50 Future of AI and Society

In this episode of the AI Adoption Podcast, Alex Dalman from VCCP’s Faith and I discuss the transformative role of combining human ingenuity with AI in the advertising and marketing industry. We explore how AI tools enhance creativity, the ethical implications of AI usage, and innovative campaigns like O2’s 'Daisy vs. Scammers'. Alex explains Generative Engine Optimization, which is the new frontier after SEO. The conversation addresses the challenges and responsibilities that come with AI adoption, emphasising the importance of training data and ethical practices in leveraging AI for good.👉 Listen now for a refreshing and practical perspective on AI in marketing that blends innovation with responsibility.Key messages• AI is not replacing humans yet; it's a tool to enhance creativity.• The combination of human creativity and AI is powerful.• Creativity remains subjective and hard to define, but AI can assist.• Innovative campaigns like Daisy vs. Scammers showcase AI's positive potential.• Ethics and responsibility are crucial in AI development.• The bar for creativity is higher with AI tools available.• AI can influence consumer behaviour, raising ethical concerns.• Training data is essential for effective AI implementation.• There is a tension between creativity and AI-generated content.• GEO (Generative Engine Optimization) is the new frontier for brands.Chapters00:00 AI in Advertising02:59 The Role of AI in Creative Processes05:48 Innovative AI Campaigns: Daisy vs. Scammers08:32 AI Tools and Their Impact on Creativity11:46 Ethics and Responsibility in AI Usage14:54 The Future of AI in Marketing17:39 The Dark Side of AI20:26 Ensuring Ethical and Responsible AI Development23:39 The Importance of Training Data26:27 The Tension Between Creativity and AI29:16 Advice for Incorporating AI in Marketing

In this episode of the AI Adoption Podcast, Jenna Shanks from NICE and I talk about the transformative impact of AI on customer experience and operational efficiency. She shares insights on how AI is being integrated across various industries, the cultural shifts required for successful adoption, and the importance of knowledge management. Jenna emphasises the need for organisations to embrace AI to remain competitive and highlights the skills necessary for individuals to thrive in an AI-driven world.Listen to find out why Jenna says: “What worked in the past isn’t necessarily going to work in the future and organisations that fear change risk being overtaken by their competitors.”Key Messages• AI can enhance customer interactions and build loyalty.• AI can significantly improve operational efficiency and accuracy.• Cultural shifts are essential for successful AI adoption.• Resistance to AI often stems from fear of job loss.• AI will not replace humans but will replace those not using it.• Management of knowledge essential for effective AI adoption.• Organisations must start small and build credibility with AI.• The future of work will involve new roles created by AI diffusion.• Continuous learning and adaptability are key in the AI era.Chapters00:00 Introduction to Agentic AI and NICE03:00 The Role of AI in Enhancing Customer Experience06:01 AI Implementation Across Industries08:48 Cultural Shifts in Organisations Due to AI12:08 Addressing Resistance to AI Adoption14:55 Strategic Changes in Business Models with AI17:54 The Importance of Knowledge Management for AI

AI adoption isn’t just for big companies. For the millions of small and medium-sized enterprises (SMEs) in the UK, AI could be a lifeline or a threat.In this episode of the AI Adoption Podcast, Baroness Martha Lane Fox and I discuss the impact of AI on SMEs. Martha is a cross-bench member of the House of Lords, President of the British Chamber of Commerce, is on the boards of various companies and runs her own small business. She highlights the challenges SMEs face in adopting AI, including resource constraints and the need for better data management. Our conversation explores the role of government in supporting SMEs, the importance of effective AI usage, and the potential for productivity gains. Additionally, we address the implications of AI on job disruption and the necessity for clear regulatory frameworks. The British Chambers of Commerce's initiatives to assist SMEs in adopting AI are also discussed.Here’s the clarion call: “It’s a dereliction of duty if SME leaders aren’t engrossed in AI.” Baroness Martha Lane FoxKey messages• AI is transforming the economy especially for SMEs.• SMEs often lack the resources to invest in AI.• AI can serve as a “great equaliser” for SMEs.• Data management is crucial for effective AI use.• Government should provide clear direction without over regulation.• Many SMEs are not using AI effectively despite its potential.• SME leaders must actively engage with AI technologies.• Small businesses can benefit significantly from AI tools.• SMEs must avoid the risks of superficial adoption vs. embedding AI into strategy.• The British Chamber of Commerce is launching initiatives to support AI adoption in SMEs.• The changing world of work: productivity boosts, job disruption, and the challenge of building senior talent when entry-level roles are automated.🎙️ Listen now to explore what AI adoption really means for SMEs and why leaders must “get playing with the stuff.”Chapters00:00 AI and SMEs02:01 The Impact of AI on SMEs05:40 Government's Role in SME AI Adoption07:51 Building SME AI Ecosystems10:24 Challenges for Micro and Small Businesses13:55 Infrastructure and Skills for AI16:39 Medium-Sized Businesses and AI18:41 AI's Role in Improving Productivity20:49 Job Disruption and AI22:56 Dealing with AI's Rapid Changes26:08 Regulatory Concerns for AI Adoption27:47 Support from the British Chamber of Commerce

In this episode of the AI Adoption Podcast, I am delighted to speak with Raghava Krishna, Technology Director for Digital and AI at the AA. This conversation brings together two key themes: the promise of AI in services organisations and the practical challenges of AI adoption in a complex, distributed organisation. The AA is one of the UK’s most trusted brands and integrity is critically important when implementing digital transformation and artificial intelligence. He highlights the importance of leveraging historical data to implement customer-centric AI solutions. Raghava explains how the AA established governance principles and guardrails for AI initiatives. He emphasises the need for training and education within the organisation, at all levels, to prepare for the rapid evolution of AI technology and striking a balance between innovation and trust.“AI is not just another technology. Every employee, from leadership to front line, must understand what it can and cannot do.” Raghava KrishnaKey Messages1. The AA has a rich history of 120 years, evolving from roadside assistance to a comprehensive service provider.2. Digital transformation is crucial for the AA, with a focus on expanding services through online and mobile channels.3. Artificial intelligence is being implemented to enhance customer experience and provide predictive maintenance solutions.4. Leveraging historical data is essential for making informed AI decisions and improving service delivery.5. A customer-centric approach is fundamental in identifying AI use cases that enhance member experience.6. Establishing governance and coordination is key to managing AI initiatives across different business units.7. Balancing innovation with trust is vital for maintaining customer confidence in AI solutions.8. How AI and IoT could enable predictive roadside support, such as alerting members before their battery fails.9. Guardrails are being developed to ensure responsible AI deployment and compliance with data privacy.10. Training and education on AI are necessary for all employees to foster a culture of innovation.11. Organisations should start small with AI initiatives to adapt to the rapidly changing technology landscape.Chapters00:00 The AA's Digital Journey02:47 AI Implementation and Predictive Maintenance06:00 Leveraging Historical Data for AI09:00 AI in a Distributed Organisation12:03 Balancing Innovation and Trust in AI14:40 Establishing Guardrails for AI Deployment17:43 Monitoring and Enforcing AI Guardrails20:35 Future of AI and Organisational Readiness23:48 Training and Educating for AI Adoption26:44 Rapid Changes in AI Technology

In this episode of The AI Adoption Podcast, I had the pleasure of speaking with Matt Houlihan, Senior Director of Government Affairs, Cisco Europe.Matt brings a wealth of experience from both government and the private sector, and together we explored what it truly means for organisations to be AI ready. Cisco’s AI Readiness Index provides fascinating, and at times sobering, insights: while 98% of companies see the urgency of AI adoption, only 13% consider themselves fully ready.Listen to find out why Matt says: “there’s a huge gap between the excitement about AI and organisations’ actual readiness to make a success of it.”We discussed:• The five pillars of AI readiness, which are strategy, infrastructure, data, governance, and culture/talent.• Why the UK’s productivity challenge makes tech adoption a national priority.• The dual role of AI in cybersecurity both as a threat and as a defence.• The importance of trust and responsible AI principles and how Cisco embeds them into practice.• The future of jobs, in particular, the transformation in ICT, rising demand for AI skills, and the vital role of training and digital skills.Key messages• AI readiness is crucial for successful adoption.• Leadership plays a significant role in AI readiness.• Data management is essential for effective AI use.• Cybersecurity concerns can hinder AI adoption.• Trust in AI systems is vital for organisations.• Regulation can coexist with innovation in AI.• AI is transforming job roles and productivity.• Digital skills training is necessary for workforce adaptation.• Cisco aims to train 25 million people in digital skills by 2030.• Demand for AI skills in job postings has surged.00:00 Introduction to AI Adoption and Cisco's Role04:22 Understanding AI Readiness and Its Importance10:04 Key Factors of AI Readiness13:22 The Role of Data in AI Adoption16:34 AI and Cybersecurity: A Double-Edged Sword21:16 Building Trust in AI Systems25:52 Ensuring Principles are Lived in Organisations28:05 Navigating Regulation and Innovation in AI34:15 The Impact of AI on Jobs and Skills

Sue Daley OBE, Director of Technology and Innovation at Tech UK is my guest for this episode of The AI Adoption Podcast. We discuss the current state of the UK tech sector, particularly focusing on AI adoption and its implications for businesses and the economy. The conversation covers the role of AI in the UK’s Industrial Strategy, the challenges faced by SMEs in adopting AI, and the importance of government, university and industry collaboration to support AI initiatives. Sue emphasises the need for education, awareness, and the integration of AI into everyday business tools and processes to facilitate adoption. The discussion also focuses on the future of work and the evolving landscape of jobs as agentic AI is rolled out into many organisations.Sue shares powerful insights on:• Why the UK ranks third globally in AI behind the US and China.• How AI adoption, not just innovation, drives value across every sector.• The challenge of bringing SMEs into the AI journey.• Why scaling pilots into real-world deployments is the next frontier.Listen now to understand how AI adoption is reshaping business, skills, and the future of work in the UK.Key messages• AI is a transformative technology that is itself rapidly evolving.• The UK is third in the world for AI development and adoption.• AI is integral to the UK's Industrial Strategy and economic growth.• Adoption of AI requires a narrative that resonates with businesses.• SMEs need support and education to adopt AI effectively.• AI is becoming embedded in everyday processes, tools and services.• Government, university and industry collaboration is crucial for AI adoption.• Training and upskilling the workforce is essential for AI integration.• Peer-to-peer learning can help SMEs understand AI benefits.• The future of work will involve AI augmenting human roles.Chapters00:00 Introduction to AI Adoption and Tech UK02:48 Impact of the UK's Industrial Strategy on the UK Tech Sector05:58 Moving from AI Plans to AI Adoption08:54 Key Developments for AI Adoption12:00 Small Language Models14:51 Coping with Rapid Changes in AI Technology17:55 Supporting SMEs in AI Adoption20:51 Government and Policy Support for AI23:49 The Role of Tech Companies in AI Adoption26:34 Impact of AI on Jobs and Workforce29:27 AI and the Future of Work

In this episode of the AI Adoption Podcast, Sean Betts, Chief AI and Innovation Officer at Omnicom Media Group, and I discuss the transformative impact of generative AI on marketing and advertising. Sean shares how generative and agentic AI are reshaping the industry, from producing campaign content to designing synthetic research panels that simulate consumer behaviour. He highlights the rapid advancements in creative applications, the importance of building future capabilities, and the challenges of ensuring responsible AI adoption. The conversation examines the emerging capabilities of using synthetic data, the evolution of agentic AI, and the potential societal and business model disruptions that may arise as AI technologies continue to advance.“We’re seeing early agents now … they may handle a week’s work in an hour.” Sean Betts🔎 What you’ll learn:• How Generative AI is rapidly changing the advertising landscape.• Why creative applications of AI are being widely adopted.• Efficiency and automation are key benefits of AI in business.• Why building capabilities around AI is essential for future success.• Synthetic data can enhance consumer research significantly.• Validation of synthetic data is crucial for accuracy.• Agentic AI represents a new frontier in AI capabilities.• How AI agents are evolving to perform more complex tasks.• Bias in AI decision-making poses significant risks.• Why incumbent businesses may struggle to adapt to rapid AI technological changes.Chapters00:00 Introduction to AI in Advertising01:10 Impact of Generative AI on Creativity03:53 Efficiency and Automation in Business Processes06:10 Emerging Capabilities of AI10:10 Synthetic Data and Consumer Research12:56 The Role of AI Agents19:34 Guardrails for AI Implementation22:41 Future of Agentic AI25:54 Societal Implications of AI30:47 Business Model Disruption by AI

Join me, Professor Ashley Braganza, and AI expert Dr Nikolay Burlutskiy as we explore the rise of AI agents, the power of synthetic data and what organisations must do to adopt AI responsibly. According to Nikolay, “Synthetic data proved better than real-world datasets in our trials at Astra Zeneca.”What you’ll learn:• Why 2024 was GenAI and 2025 is firmly the year of AI agents• How to set internal benchmarks and assess performance, cost and AI vulnerabilities • Best practice: start small, integrate agents securely, then scale• Use cases: from AI-generated pathology reports saving lives to automating knowledge retrieval across enterprise systems• Why synthetic data can outperform real data thus boosting AI model accuracy • The importance of upskilling your workforce in problem-solving, literacy, and keeping humans in the loopKey messages:• AI platforms can be simplified by consolidating multiple solutions into one.• Cost control is essential when adopting generative AI solutions.• Companies should establish internal benchmarks for AI model performance.• AI agents are becoming integral to business processes.• Upskilling the workforce is crucial for successful AI integration.• AI can significantly reduce waiting times using healthcare diagnostics.• The future of work will involve a collaboration between humans and AI agents.• AI has the potential to create new job opportunities while transforming existing roles.Find out why Nikolay thinks: “AI agents will change the way we work… but they must be integrated carefully, with human oversight.” Dr Nikolay BurlutskiyListen now discover how to harness GenAI, AI agents and synthetic data in your organisation.Chapters00:00 Early AI robot developments04:08 Simplifying AI Platform Creation09:59 Choosing the Right AI Models14:57 Incorporating AI Agents into Workflows20:07 The Impact of AI on Workforce Dynamics25:00 Use Cases of AI in Healthcare and Business30:04 The Role of Synthetic Data in AI Development

When machines are learning, evolving, making and enacting decisions on their own, what should you do?In this episode of The AI Adoption Podcast, I speak with Maggie Sarfo, CEO of Meres Consult, about why human emotional intelligence (EI) is the essential counterweight to machine artificial intelligence (AI) in today’s workplaces. Maggie says that leaders can navigate this shift with clarity, empathy, and adaptability.🔍 Key topics explored:• How emotional intelligence and AI can collaborate not compete• Soft skills are becoming core leadership strengths in an AI workplace• The importance of recognising and addressing fear, uncertainty and intergenerational divides that arises with AI adoption• Maggie’s Meres Adaptability Framework for managing extreme change🗣 “If we can develop machines that act on their own, we can also develop ourselves to be even more human.” Maggie SarfoThis conversation is a must-listen for leaders developing and adopting an AI strategy, team wellbeing, and long-term organisational resilience.Key messages• Emotional intelligence (EI) is crucial for effective leadership.• AI and EI can complement each other in organisational settings.• Human-AI collaboration is essential for optimal workflows.• Organisations can retain EI by embedding it in AI strategies.• Leaders must address fear and uncertainty regarding AI.• New roles, such as AI trainers and explainers, are emerging.• The Meres Adaptability Framework helps organisations navigate change.• Workshops on EI should accompany AI adoption training.• Leaders need to support their teams through AI transitions.• Emotional intelligence should be prioritised in decision-making processes.Chapters00:00 AI and Emotional Intelligence02:58 The Intersection of AI and Emotional Intelligence05:50 Human-AI Collaboration in Workflows08:56 Retaining Emotional Intelligence in AI Adoption12:09 The Role of Leaders in an AI World14:54 Addressing Fear and Uncertainty in AI18:05 Emerging Roles in the Age of AI20:54 Supporting Teams Through AI Transition24:02 The Meres Adaptability Framework27:03 Bringing It All Together: AI, Leadership, and Emotional Intelligence

💡 In this wide-ranging conversation, Lord Kulveer Ranger draws on decades of experience across technology, transport, and policy to unpack how AI must be embedded into business thinking and strategic action. He says AI is more than standalone tech tools, it is a catalyst for transformation.🚀 Topics explored in this episode:• Why change management is central to AI success• UK start ups are being “hoovered up” by overseas investors• The real skill sets businesses need to drive AI adoption and many are non-technical• Lessons from past tech waves and how to apply them to AI adoption• Why culture, not just code, will determine an organisation’s AI maturity🗣️ "You have to have those people who are also going to be the business change leaders for AI. The ones who understand which outcomes you want to drive through your business." Lord Kulveer Ranger🔎 Lord Ranger also discusses the UK’s critical need to:• Retain and scale homegrown innovation• Build an investment pipeline that keeps businesses sovereign• Rethink operating models to align strategy, culture, and technology🎙 Whether you’re a policymaker, business leader, or technologist, this episode offers strategic clarity on what enables AI to succeed in organisations and across the UK economy.Chapters00:00 Looking back to go forward07:10 Lessons from Previous Technology Waves12:28 Change Management and AI Adoption16:32 Impact of AI on Business Models and Culture24:09 Supporting Start ups and Scale-ups in the UK30:45 Strategic Priorities for AI Adoption

In this episode, I am joined by Dr Alexandra Dobra-Kiel, Innovation and Strategy Director at Serviceplan Group and member of the Advertising Association’s AI Task Force.Together, we explore why AI adoption must go far beyond implementation and why organisational culture, leadership vulnerability and strategic clarity are essential to making AI work for people, not just systems.Alexandra offers a timely and thought-provoking analysis of how businesses can avoid superficial rollouts and instead embed AI in a way that delivers sustainable value.🎯 In this conversation, we cover:Why 77% of employees are anxious about AI taking their jobs and how leaders should respond with honesty and dignityThe difference between automation and augmentation and why we need a talent reboot, not a talent reductionThe importance of psychological safety and a culture that encourages openness, experimentation and risk-takingWhy “boring tasks” are often critical for learning, and removing them may unintentionally damage developmentHow leaders must demonstrate humility and vulnerability to build trust in AIThe traps of ego-driven resistance and incremental thinking and how to escape themWhy governance should be a tool for growth, not just complianceHow to ensure AI adoption reflects both human strengths and AI limitationsWhether you're a senior leader, strategist, policymaker or innovator, this episode offers practical insights for shaping the future of work with AI.Chapters00:00  Understanding AI Adoption vs. Implementation02:58  Factors Influencing AI Adoption in Workplaces05:52  Motivating Employees to Engage with AI09:06 The Future of Jobs in the Age of AI11:40  Balancing Ethics and AI Deployment14:39  Evolving Business Models with AI17:57  Spotting Opportunities in AI20:43  Assessing Organisational Maturity in AI23:33  Innovating While Achieving Operational Efficiencies26:30  Prioritising AI Adoption in the Boardroom

In this episode of the AI Adoption Podcast, I discuss thetransformative role of AI in healthcare medical devices with Dr Alex Cole, Director of Market Strategy at CPI.  We explorevarious applications of AI, from administrative support to high-risk clinical decision-making.  This discussion highlightsthe challenges of integrating AI into medical devices, particularly within the NHS. The conversation examines the regulatory landscape, the importance of data management, and the need for skilled professionals in the field. Alex emphasisesthe necessity of building trust in AI systems and the role of policymakers in fostering innovation. Alex identifies the factors that are holding back AI adoption in the NHS and what the UK needs to do to catch up, if not exceed, the adoption of AI in the US healthcare system.Key Messages• AI has broad applications in healthcare medical devices that need to be gauged on risk factors.• The NHS faces challenges in adopting AI due to funding models.• AI Airlock allows testing of high-risk AI models in a safe environment.• The US has a more structured approach to approving AI in medical devices.• Data fragmentation is a significant barrier to effective AI use in UK healthcare.• Skills in regulatory understanding are crucial for AI integration.• Policymakers need to support industry-academic collaborations.• A kitemark for AI models could enhance trust and quality assurance.• Continuous development and post-market surveillance are essential for AI systems.• The future of AI in healthcare looks promising with increased integration.Chapters00:00 Introduction to AI in Healthcare02:07 AI Applications in Healthcare05:44 Incorporating AI into Medical Devices08:13 Challenges in AI Adoption in the NHS09:34 Understanding the NHS Airlock12:06 Catching Up with the US in AI Healthcare15:35 Data Challenges in AI Healthcare18:13 Priorities for Medical Device Companies20:06 Developing Skills for AI Integration21:02 Role of Policymakers in AI Development24:45 Future of AI in Healthcare26:22 Ensuring Trust in AI Systems

In this insightful episode, I speak with Allison Gardner, MP for Stoke-on-Trent South and an expert in AI regulation. We explore the UK Government’s AI Action Plan, the development of AI growth zones, and the critical role of governance and regulation in public services.Allison brings her expertise in health, AI policy, and data ethics to this engaging conversation, covering:✅ The Government’s AI Plans and investment in data centres✅ Using AI to improve diagnostics and manage public services like pothole detection✅ The urgent need for robust AI governance and statutory regulation✅ Support for SMEs in AI adoption✅ Protecting the creative industries and the quality of training dataAllison says: "My concern is actually we risk the integrity of our AI models if we don't protect human created data."This episode is essential for anyone interested in public policy, AI adoption, and the UK’s innovation strategy.

Ben Johnson, co-founder and CTO of Uptitude and adviser to UK Parliament, joins me to explore what it really takes for enterprise organisations to adopt AI meaningfully.🎯 Highlights:• Why AI starts with data and ends with culture• The hidden risks of bad data and siloed ownership• What leadership teams must do to embed AI across functions• A bold call for Chief AI Officers at board level📢 “It’s not just tech. AI is a human opportunity. And unless boards reflect that, we’ll keep missing its potential.”Chapters00:00 Introduction to AI Adoption in Enterprises02:11 The Importance of Data Quality11:25 Data Management Responsibilities13:31 Opportunities Driving AI Adoption19:11 Barriers to AI Adoption25:51 Strategic AI Deployment for Boards29:03 Policy Considerations for AI Adoption31:50 Balancing Internal and External Policies

In this episode of The AI Adoption Podcast, I am joined by Janine McKelvey, General Counsel for Data, AI and Security at BT Group, to discuss the critical aspects of AI adoption, focusing on governance, compliance, and the strategic implementation of AI within organisations. Janine shares insights on the essential elements of an AI strategy, understanding the AI supply chain, conducting impact assessments, and navigating legal considerations. The conversation highlights the need for skills development in AI, the impact of AI on compliance and legal jobs, and the balance between governance and value in AI initiatives. Key messages1. AI strategy is essential for organisations considering adoption.2. Understanding the AI supply chain is important for risk management.3. Impact assessments help identify potential risks associated with AI.4. Compliance with regulations is necessary for safe AI deployment.5. Skills development is vital for effective AI integration.6. AI can enhance productivity by automating mundane tasks.7. Organisations must balance governance with the pursuit of value.8. Legal considerations are critical in AI procurement and deployment.9. AI's impact on jobs will create new opportunities and roles.10. Continuous learning and adaptation are necessary in AI governance.Chapters00:00 The Components of an AI Strategy10:11 Building an AI Supply Chain: Key Considerations17:59 Achieving Compliance with Limited Resources26:01 Skills and Capabilities Needed for AI Adoption29:11 AI's Impact on Legal and Compliance Jobs32:16 Advice for Boards Adopting AI

In this episode, I’m joined by the Right Reverend Steven Croft, the Lord Bishop of Oxford. Our conversation explores the philosophical and ethical questions that arise as generative and agentic AI becomes more deeply embeddedin our lives.Together, we ask:·      How is AI reshaping the meaning of being human?·     Can faith traditions offer wisdom for this newtechnological era?·      What does responsible AI governance actuallylook like?·      And how do we ensure AI serves human dignity, not the other way around?Steven brings a rare and thoughtful perspectivebased on a wide range of experiences from his work in the House of Lords to years of theological reflection. He reminds us that AI doesn’t exist in a vacuum: it’s changing how we understand truth, trust, and each other.“The development of AI will inevitably force humanity to reflect more deeply on what it means to be human.” Steven CroftChapters00:00  Exploring Humanity in the Age of AI06:08 The Interplay of AI and Human Characteristics11:22  Faith's Role in the AI Conversation20:03  Truth in the Context of AI24:20  Human-Machine Partnerships: Opportunities and Concerns26:52  The Role of Regulators in AI Development29:52  Balancing Regulation and Innovation36:48  Trust and Transparency in AI Interactions39:20  Setting Boundaries for AI Development42:14  Social Responsibility in AI GovernanceKeywordsKeywordsaigovernance aitruth aitrust airegulation artificialintelligence generativeai agenticai aiethics aiandsociety ai chatgpt gemini google chatbot llm claude oxforddiocese

In this episode, Zahra Bahrololoumi CBE, CEO of Salesforce UK & Ireland, explores agentic AI, a new generation of artificial intelligence that processes, decides, acts and responds autonomously across business functions. In this thought-provoking episode, you’ll hear:What sets agentic AI apart from predictive and generative AIReal use cases from Agentforce, Salesforce’s AI (e.g., Heathrow Airport, Capita)How AI is driving productivity, reducing operational costs, and transforming service modelsEthical and governance challenges around autonomous AIThe human-AI partnership and the urgent need to reskill the workforceZahra’s call for a national digital skills strategy to prevent an AI-fuelled digital divide “This is not just a transition – it’s a full-scale transformation,” says Zahra.Chapters00:00  Introduction to Agentic AI and Its Impact08:07  Benefits and Applications of AI Agents12:05  The End of Human Only Workforces?18:39  Ensuring Trustworthy Agentic AI22:20  Impact of Agentic AI on Job Losses23:18  Navigating the Digital Divide and Job Displacement27:43  Where does the UK Position Itself in AI?29:34  Boardroom Priorities to Adopt Agentic AI33:42  Human Agent and AI Agent Productivity

As the UK government begins responding to Matt Clifford’s AI Opportunities Action Plan to become a global leader in AI innovation, with strategic investment in AI zones and data centre infrastructure, the debate intensifies: how do we meet the rising energy demands of AI infrastructure without compromising our green commitments?In this episode of the AI Adoption Podcast, Professor Ashley Braganza speaks with Ali Teeney, Head of AI and ML at Kraken (Octopus Energy Group’s tech arm), to examine whether Green AI is truly attainable and what it will take. Ali explores how Kraken is using AI to optimise energy grids, power homes more efficiently, and work directly with customers to build trust in new technologies. He also breaks down the real numbers behind training large language models and explains the need for policy reform, market incentives, and grid modernisation to make Green AI a reality.Drawing from Kraken’s AI innovations across the UK and international markets, Ali shares actionable insights into:• The energy cost of LLMs and future models• Optimising smart grid loads with AI • The economics of building data centres near renewable energy sources• Why UK policy reforms around grid pricing and renewable access are overdue• The difference between headline government support and system-level readinessAs governments around the world lean into AI infrastructure investment, this episode explores whether our energy systems are ready and what must change to ensure AI becomes a catalyst, not a threat, to environmental sustainability.Chapters00:00 Introduction to AI and Energy Utilisation06:01 The AI Energy Challenge14:49 Policy and Infrastructure for AI Data Centres22:59 Balancing Green Energy and AI Development27:00 Opportunities in the AI Landscape𝐖𝐚𝐧𝐭 𝐭𝐨 𝐬𝐭𝐚𝐲 𝐮𝐩𝐝𝐚𝐭𝐞𝐝? ✅ Subscribe to the AI Adoption podcast channel: https://www.youtube.com/@aiadoption-conversations/videos✅ Follow us on LinkedIn: https://www.linkedin.com/showcase/the-ai-adoption-podcast-showcase✅ Follow us on Instagram: https://www.instagram.com/theaiadoptionpodcast/#ai #artificialintelligence #ethicalai #sustainableai #aishorts #aipolicy #cybersecurity #data #energy #greenenergy

I’m delighted to share the latest episode of The AI Adoption Podcast, where I had the privilege of speaking with Hamzah Malik, Founder and CEO of Vet Pulse AI and Regent Branding.Hamzah’s story is a masterclass in identifying a niche, deeply understanding your market, and building AI solutions that create meaningful impact. Vet Pulse AI is already supporting over 1,000 veterinary professionals across the world, helping them access up-to-date, reliable knowledge, underpinned by transparency about data sources and built with the end user in mind.In our conversation, Hamzah shares:✅ Why he ventured into the veterinary sector ✅ How he combined AI with specific industry knowledge to solve real problems✅ The role of transparency in AI adoption and why it matters to end users✅ The challenges of bootstrapping an AI business while growing a digital consultancy✅ The top five things every aspiring AI founder should know before they get started✅ Why persistence, humility, and a user-first approach are keys to longer-term successIf you’re an entrepreneur, an AI enthusiast, or someone navigating the challenges of bringing new technology to market, this episode is packed with honest insights and practical advice.Chapters00:00  Introduction to AI in Veterinary Medicine02:02  Hamzah’s Journey into AI and Veterinary05:16  Identifying Market Gaps and Business Case11:30  Adopting the Vet Pulse Platform13:44  Ensuring Transparency in AI Responses16:10  Data Management and Content Sourcing18:00  Funding and Growth Strategies21:16  Building a Global Team24:11  Managing Multi-Country Regulations26:13  Advice for Aspiring AI Entrepreneurs32:55  Future Challenges and Vision𝐖𝐚𝐧𝐭 𝐭𝐨 𝐬𝐭𝐚𝐲 𝐮𝐩𝐝𝐚𝐭𝐞𝐝? ✅ Subscribe to the AI Adoption podcast channel: https://www.youtube.com/@aiadoption-conversations/videos✅ Follow us on LinkedIn: https://www.linkedin.com/showcase/the-ai-adoption-podcast-showcase✅ Follow us on Instagram: https://www.instagram.com/theaiadoptionpodcast/#ai #artificialintelligence #ethicalai #sustainableai #aishorts #aipolicy #cybersecurity #data

Autonomous AI applications are no longer speculative technologies nor are they just about self-driving cars. Autonomous AI embedded in vehicles, drones and a variety of other vehicles are creating a fundamental shift in how industries operate, move goods, respond to crises, and maintain infrastructure. In this episode of the AI Adoption Podcast, I am joined by Dr Madeline Cheah, a leading voice in cybersecurity and AI assurance with Cambridge Consulting, Capgemini’s deep tech arm, to explore the landscape of autonomous AI applications and their implications. We discuss what makes a system “autonomous,” how autonomous applications are deployed across industries, and what organisations must do to adopt them responsibly.Key Highlights:• Autonomous vehicles in action across agriculture, logistics, rail, and emergency services• Safety and efficiency gains from reducing human involvement in high-risk tasks• The risk landscape: cybersecurity, AI decision-making, and emergent behaviour• AV supply chains that include open-source code, third-party datasets, and AI models• Strategic guidance for business leaders: feasibility, safety, and system assuranceChapters00:00 Introduction to Autonomous Vehicles 04:35 Importance of Autonomous Systems06:06 Autonomous AI Applications10:57 Risks and Challenges of Autonomous Vehicles15:48 Mitigating Risks in Autonomous Systems Development18:34 Creating and Managing AI Supply Chains20:50 Regulatory Considerations for Autonomous Systems22:03 Priorities for Companies Implementing Autonomous Vehicles24:15 Impact of Autonomous Vehicles on Employment26:28 Societal Factors Driving Adoption of Autonomous Vehicles𝐖𝐚𝐧𝐭 𝐭𝐨 𝐬𝐭𝐚𝐲 𝐮𝐩𝐝𝐚𝐭𝐞𝐝? ✅ Subscribe to the AI Adoption podcast channel: https://www.youtube.com/@aiadoption-conversations/videos✅ Follow us on LinkedIn: https://www.linkedin.com/showcase/the-ai-adoption-podcast-showcase✅ Follow us on Instagram: https://www.instagram.com/theaiadoptionpodcast/#ai #artificialintelligence #ethicalai #sustainableai #aishorts #aipolicy #cybersecurity #data #autonomusvihicles

In this episode, we're joined by Konrad Shek, Director of Public Policy and Regulation at the Advertising Association.Konrad brings a unique lens to the AI conversation, blending his background in engineering, civil service, and policy with his current leadership across AI, digital technology, and data privacy in the advertising world. In this episode, he delves into how generative AI is transforming advertising –from personalised video campaigns to synthetic focus groups and hyper-efficient content creation.Chapters00:00 Introduction to AI in Advertising02:48 The Impact of AI on Advertising Practices05:49 Generative AI: Transforming Campaigns and Creativity09:02 The Future of Advertising Professionals in an AI World12:10 Regulatory Challenges and Opportunities in AI15:01 Consumer Perspectives on AI in Advertising18:10 Navigating Global Regulatory Landscapes21:05 The Role of Education in Understanding AI24:11 Conclusion and Future Outlook𝐖𝐚𝐧𝐭 𝐭𝐨 𝐬𝐭𝐚𝐲 𝐮𝐩𝐝𝐚𝐭𝐞𝐝? ✅ Subscribe to the AI Adoption podcast channel: https://www.youtube.com/@aiadoption-conversations/videos✅ Follow us on LinkedIn: https://www.linkedin.com/showcase/the-ai-adoption-podcast-showcase✅ Follow us on Instagram: https://www.instagram.com/theaiadoptionpodcast/#ai #artificialintelligence #ethicalai #sustainableai #aishorts #aipolicy #cybersecurity #data

In this episode of the AI Adoption Podcast, Professor Ashley Braganza interviews Sunaina Aytan, a cybersecurity consultant at Airbus Protect. They discuss the intersection of cybersecurity and artificial intelligence, emphasising the importance of understanding cybersecurity in the context of AI adoption. Sunaina explains the role of senior management in ensuring data security, the challenges organisations face in adopting AI, and the significance of creating an interdisciplinary, cross-functional AI Council to foster collaboration across departments. The conversation discusses the use of synthetic data to reduce bias, the need for human oversight in AI systems, and the support needed for SMEs to navigate the regulatory landscape. Agentic AI is an emerging development in the field of Artificial Intelligence and Sunaina provides interesting insights into its impact on organisations and workers.Key highlightsCybersecurity is essential for safe AI adoption.AI implementation should align with company objectives.AI education and digital literacy are crucial for employees at all levels.Synthetic data aims to reduce biases in AI training.Human oversight is necessary in AI systems.Senior management must prioritise data security. Understanding regulations is key to compliance.Creating a cross-silo AI Council fosters collaboration.Agentic AI will have profound consequences on workers.SMEs need tailored support for AI adoption.Transparency in data management is vital.Chapters00:00 Introduction to Cybersecurity and AI04:10 Understanding Cybersecurity: The Basics09:13 The Importance of Cybersecurity in AI Adoption11:59 Challenges in AI Adoption and Cybersecurity15:49 The Role of Senior Management in AI and Cybersecurity19:54 Synthetic Data: Definition and Implications23:53 Agentic AI: A New Frontier27:49 Supporting SMEs in AI Adoption31:01 Conclusions and Key Lessons𝐖𝐚𝐧𝐭 𝐭𝐨 𝐬𝐭𝐚𝐲 𝐮𝐩𝐝𝐚𝐭𝐞𝐝? ✅ Subscribe to the AI Adoption podcast channel: https://www.youtube.com/@aiadoption-conversations/videos✅ Follow us on LinkedIn: https://www.linkedin.com/showcase/the-ai-adoption-podcast-showcase✅ Follow us on Instagram: https://www.instagram.com/theaiadoptionpodcast/#ai #artificialintelligence #ethicalai #sustainableai #aishorts #aipolicy #cybersecurity #data

In this episode of The AI Adoption Podcast, Professor Ashley Braganza interviews Lord Tim Clement-Jones, a prominent figure and thought leader in AI governance and policy. They discuss the current state of AI adoption in the UK, focusing on the public sector's preparedness, the importance of data quality, and the need for trust and ethical governance. Lord Clement-Jones emphasises the role of leadership in fostering a culture of trust and the necessity of a robust regulatory framework that balances innovation with ethical considerations. The conversation also touches on the challenges faced by SMEs in adopting AI and the potential impact of agentic AI on the workforce. Overall, the episode provides valuable insights into AI adoption and the importance of collaboration between the public and private sectors.Key messages AI adoption in the public sector is hindered by cultural issues.Data quality and public trust are crucial for AI success.Leadership is essential for fostering a culture of trust in AI.Regulation can support innovation rather than hinder it.Ethics-oriented governance is vital for responsible AI development.Corporate responsibility is necessary for big tech companies.SMEs face unique challenges in adopting AI technologies.Education and skills development are key for workforce adaptation to AI.The future of AI adoption may see a divide between large and small companies.International cooperation is needed for effective AI governance.𝐖𝐚𝐧𝐭 𝐭𝐨 𝐬𝐭𝐚𝐲 𝐮𝐩𝐝𝐚𝐭𝐞𝐝? ✅ Subscribe to the AI Adoption podcast channel: https://www.youtube.com/@aiadoption-conversations/videos✅ Follow us on LinkedIn: https://www.linkedin.com/showcase/the-ai-adoption-podcast-showcase✅ Follow us on Instagram: https://www.instagram.com/theaiadoptionpodcast/#ai #artificialintelligence #ethicalai #sustainableai #aishorts #aipolicy

In the inaugural episode of the AI Adoption Podcast, Professor Ashley Braganza introduces the significance of AI in today's world, emphasising its transformative impact across various sectors. The podcast aims to provide leaders and decision-makers with insights and practical steps for successful AI adoption through in-depth conversations with experts drawn from industry, public sector, policy and academia. The podcast will address the challenges and ethical considerations involved with implementing AI. Professor Braganza shares his expertise and experiences in AI implementation, highlighting the importance of trust, public confidence, and strategic planning in navigating the complexities of AI integration. Enjoy the AI conversations that will follow this introduction to the AI Adoption Podcast.Key messages• AI will affect everyone, everywhere, right now.• AI is a transformative force reshaping industries.• AI adoption requires a strategic approach and leadership.• Trust and public confidence are critical for AI adoption.• AI is currently being utilised across various sectors.• The UK government is investing in AI skills and infrastructure.• AI adoption is challenging but necessary for organisations.