The AI Opportunity

AI isn’t just changing how we work — it’s starting to divide how people live, think, and operate.In this episode, Kenny sits down with Zac Engler, Chief AI Officer at C4 Technical Services, to explore a shift most leaders aren’t prepared for: AI is creating three types of people. Those who reject it, those who work alongside it, and those who fully integrate with it.They discuss what this divide means in practice — from rapid productivity gains and rising expectations at work, to a growing gap in individual capability. The conversation also explores the idea of a “Max-Q” moment for society, where pressure, speed, and change are all accelerating at once.As AI becomes more embedded in everyday life, the question isn’t just how you use it, but whether you choose to participate at all, or let the future be decided for you.Chapters00:25 – Introduction to Zac Engler01:25 – How Fortune 500s Are Actually Using AI (Crawl → Walk → Run)03:09 – Even Experts Are Falling Behind06:29 – “Max-Q” — The Pressure Point of This AI Moment09:28 – Why You Need a Voice in AI’s Future11:26 – The 4 Possible Futures of AI (Mad Max → Star Trek)14:00 – Could AI Shift Us to a “Meaning Economy”?16:33 – The Fragility of Society in an AI Era20:00 – Can AI Rebalance Power in Society?23:21 – Raising Kids in an AI World27:00 – AI Will Split Humanity – Here’s How30:10 – Participate or Get Left BehindFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

AI is starting to change more than how we work – it’s changing how the next generation learns, thinks, and understands the world.In this episode, Kenny sits down with David Martelli (Founder of Guild Hall Learning) to explore what education looks like in a world where AI can personalise learning, create instantly, and reshape what skills actually matter. They discuss what this shift means for parents and leaders – from raising independent, self-directed learners to helping children take ownership of their development in a rapidly changing world.They unpack why memorisation is becoming less valuable, why systems thinking and adaptability are rising, and what it really takes to prepare children for a future that doesn’t yet exist.Chapters:00:00 – Introduction to Dave Martelli & Rethinking Education02:00 – AI as a Personal Tutor for Every Child04:45 – Why Kids Must Take Ownership of Learning08:20 – From Specialists to Generalists Again09:40 – AI, Abundance, and the Future of Work16:40 – Systems Thinking: The Skill That Matters Most22:10 – Teaching Kids Through Real Problems29:20 – Why Traditional Schooling Falls Short35:00 – What Humans Do in a World Where AI Does EverythingFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

Personalisation has become one of the most powerful promises of AI – but it has also come with a growing cost: surveillance. From social media feeds to targeted ads, many systems rely on tracking individuals across the internet to predict what they might want next.In this episode, Kenny sits down with Ian Cook, SVP of AI Technology at Qloo, a company building AI that maps culture and taste without tracking personal data. Instead of analysing individuals, their systems study the relationships between music, restaurants, brands, travel, and entertainment to understand how human preferences connect.They discuss how AI can uncover cultural patterns without relying on personal identifiers, why recommendation systems can quietly create echo chambers, and what businesses can learn from analysing taste instead of behaviour. The conversation also explores a growing concern for parents and leaders alike: how the next generation should learn to question and think critically about the information AI and algorithms present to them.As AI becomes more embedded in everyday life, the real question isn’t just what these systems can predict – but whether we can build technology that expands curiosity, encourages critical thinking, and understands people without turning them into data products.Chapters:00:00 – Meet Ian Cook (SVP of AI at Qloo)01:03 – What Qloo Actually Does: Teaching AI to Understand Culture03:27 – How AI Maps Human Taste and Preferences08:56 – Personalisation Without Surveillance13:09 – The Algorithm Problem: Echo Chambers and Doom Scrolling16:46 – Parenting in the Age of AI and Social Media19:21 – Teaching the Next Generation to Question AI22:25 – The AGI Hype: Why So Many People Are Fearful28:26 – Why Ignoring AI Is the Worst Strategy31:04 – “Action Kills Anxiety” — The Best Advice for the AI EraFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

AI adoption is moving faster than the rules designed to govern it. Companies are deploying powerful systems across finance, hiring, healthcare, and security, often before fully understanding the risks that come with them.In this episode, Kenny sits down with Patrick Sullivan, VP of Strategy and Innovation at A-LIGN working at the forefront of AI governance. Drawing on nearly three decades in IT security and risk, Patrick explains why the conversation around AI is shifting from excitement about capability to serious questions about responsibility.They discuss what regulations like the EU AI Act mean for businesses, why AI systems can develop unexpected behaviours, and how bias quietly appears in areas like hiring, credit scoring, and healthcare.As AI systems gain more autonomy, the real challenge isn’t just building them, it’s governing them. The decisions leaders make now about oversight, accountability, and risk will shape how AI evolves over the next decade.Chapters00:00 – Introduction to Patrick Sullivan01:40 – From Cybersecurity to AI Governance03:06 – The EU AI Act and Why Regulation Is Rising06:01 – Protecting Humans: Bias and Real-World09:45 – Why People Over-Trust AI Systems10:43 – Emergent Behaviour and the Alignment Problem18:38 – Does Governance Slow Innovation?22:48 – The Politics of AI Regulation24:50 – AI Literacy and the Next Generation31:20 – The Real Opportunity in AI GovernanceFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

When generative AI first arrived, it didn’t feel exciting for everyone. For content and marketing teams, it felt like a direct threat.In this episode, we speak with Diane Hammons, Director of Digital Engagement at WG Content, about what that moment actually looked like inside a company. She shares the fear from teams who felt first in line to be replaced, the unexpected volunteers who leaned in anyway, and the quieter truth leaders don’t always say out loud: your job might not disappear, but it won’t stay the same either.We get into the uncomfortable bits. The tasks people once took pride in mastering are now the easiest things for AI to do. That’s not just operational change, but it’s also an identity shift. We talk about the mistake of rolling out AI policies without giving people space to explore, and why adoption is far more psychological than technical.And then there’s the bigger question: if AI drafts first, summarises first, analyses first… how do junior people learn? What are humans actually left with? Judgment. Taste. Experience. This conversation leans into the human side of AI, the part that doesn’t fit neatly into a strategy deck.Chapters:00:00 – Introduction to Diane Hammons02:49 – Pathfinder AI: Embracing Change and Innovation05:31 – Fear, Identity, and the First Wave of Change08:33 – Breaking Stereotypes About Who Adopts New Technology12:20 – When Jobs Don’t Disappear, But They Do Change16:42 – The Leadership Dilemma: Policy vs. Permission to Experiment21:50 – Building a Culture of Curiosity24:50 – In the End, All We've Got is Judgment and TasteFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

AI is moving fast, and for a lot of leaders it can feel like you’re expected to understand everything all at once.In this episode of The AI Opportunity, Kenny speaks with Allegra Guinan, Co-Founder and CTO of Lumiera, about what executives really need in order to lead well through AI change.Drawing on her background in machine learning and her work educating senior leaders, Allegra explains why executives don’t need to become AI experts to make good decisions. Instead, she shares how AI literacy, clear problem definition, and asking the right questions help leaders navigate uncertainty, avoid over-engineering, and make more grounded choices about where AI fits in their organisation.They talk about building confidence without pretending to know everything, why AI adoption works better when it starts with real problems, and why many companies discover that their first AI work is more about people, culture, and alignment than technology itself.This episode is for CEOs, COOs, CFOs, and leadership teams who want to approach AI thoughtfully, build confidence across their organisation, and move forward without rushing or guessing.Chapters00:25 - Introduction to Allegra Guinan02:49 - Why Executives Don’t Need to Be AI Experts06:33 - Understanding AI Through Practical, Everyday Examples09:01 - Starting With Real Problems, Not Technology10:43 - What AI Readiness Actually Looks Like Inside Organizations13:07 - A Real Executive Case Study on AI Readiness15:40 - Why People and Culture Decide AI Success18:30 - Bringing the Workforce Along22:05 - Common Executive Pitfalls in AI Adoption28:13 - Consumer AI vs Enterprise AI at Scale30:29 - Shadow AI, Governance, and Responsible Use32:28 - Defining Success Before Building AI35:21 - Quick Fire Round: Where AI Creates Real Business ValueFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

AI promises to scale expertise – but in regulated, high-stakes domains like finance and tax, getting it wrong can be costly.In this episode of The AI Opportunity, Kenny sits down with David Snider, Founder & CEO of Harness, to unpack what responsible AI adoption really looks like when precision, trust, and compliance matter.David shares lessons from his career spanning Bain Capital, private equity, CFO/COO roles, and entrepreneurship – including why generic AI answers often fail in real financial contexts, how to introduce AI incrementally without scaring conservative users, and where automation genuinely creates leverage for advisors and operators.Rather than chasing shiny tools, this conversation focuses on practical workflows, clear guardrails, and keeping humans firmly in control.Chapters:00:25 - Introduction to David Snider and Harness02:40 - Why Harness Was Built and the Problem It Solves04:49 - Using AI in Financial Advice Without Losing Trust09:25 - Delivering Value to Clients Over Time13:03 - Introducing AI in Conservative, High-Risk Industries17:28 - Vertical AI vs General-Purpose Tools20:07 - Data Governance, Guardrails, and Responsible AI24:11 - Culture, Behaviour Change, and Adoption Realities25:53 - Quick Fire Round: Practical AI TakeawaysFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

Many companies know they should be investing in AI and data – but far fewer know how to run those projects well. In this episode, Kenny speaks with Mark Daniel Ward and Katie Sanders from The Data Mine at Purdue University about what business leaders need to understand before launching AI, LLM, or data-driven initiatives.Drawing on years of hands-on work with companies like Cummins and Eli Lilly, Mark and Katie break down what it takes to run AI and LLM projects that deliver real business value. They explain how to scope initiatives so they move beyond experimentation, set realistic timelines, and avoid common execution pitfalls. The conversation also covers how to structure projects with clear ownership, checkpoints, and auditability, and how leaders can recognise when a data project is ready to scale – or when it’s time to stop.For CEOs, COOs, and CFOs navigating their first or next AI project, this episode offers a grounded, execution-focused playbook for moving from experimentation to impact.Learn more about the Data Mine here: https://datamine.purdue.edu/Chapters:00:00 Introduction to Data Mine and Its Mission04:09 Challenges in AI and Data for Large Enterprises05:57 The Impact of Students in Organisations10:12 Project Management and Business Outcomes11:51 Diverse Projects and Applications of AI16:18 Framework for Companies and Leaders to Start with AI19:53 Debunking Myths About AI in Organizations23:02 Advice for Executives on AI Projects26:52 Final Quick Fire QuestionsFind us on our socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

We’re entering a shift from AI that responds to AI that executes. In this Q&A episode, Kenny explains how AI agents differ from chat-based tools and why that difference matters for real businesses.We explore the rise of AI agents, how they plan, act, pause, and resume tasks across real systems, and why visibility, guardrails, and human oversight matter more than hype. A grounded look at what’s possible today, what accelerates next year, and how leaders should think about AI that executes — safely.Submit your questions at [email protected] to be featured in our weekly Q&As.Chapters:00:00 – The Rise of AI Agents03:04 – Transformative Potential of AI in Business05:39 – The Future of AI Work and Safety Concerns]Find us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

AI agents are rapidly entering the enterprise — but with new power comes new risk. In this episode, Kenny sits down with Donato Capitella, a principal security consultant and ethical hacker with 14+ years of experience breaking into systems before the bad actors do. Together, they unpack the real security challenges behind AI agents and GenAI adoption.Donato explains why prompt injection has become one of the most common attack vectors, how AI-powered workflows can unintentionally leak sensitive data, and why organisations should treat every LLM output as untrusted. Drawing on his experience reviewing 50+ enterprise GenAI implementations, he shares what teams consistently overlook and how leaders can design safer, more resilient AI systems before they hit production.It’s a practical, grounded conversation for COOs, CTOs, and product leaders looking to strengthen security and deploy AI agents safely without slowing innovation.Mentioned in the podcast:The LLM Application Security Canvas: https://reversec.com/service/generative-ai-security/Chapters:00:00 – Introduction to AI and Security05:04 – Understanding Ethical Hacking and Generative AI08:04 – Security Challenges in AI Implementation10:08 – The Concept of Prompt Injection and Its Risks16:03 – Guardrails for AI Implementation24:00 – Biggest Opportunities in AI31:33 – Advice for Leaders on AI Use CasesFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

Many people use AI as a chatbot, and though it answers questions, it doesn’t actually do anything. In this episode, we unpack the type of AI that takes action and explain the real shift happening: from AI that responds to AI that executes. We break down how tool calls work, why context and permissions matter, and why 2026 will be the year action-taking agents go mainstream.Submit your questions at [email protected] to be featured in our weekly Q&As.Chapters00:26 – The Difference Between Chatbots and AI Agents01:40 – What Is A Tool Call02:34 – How AI Can Successfully Take Action03:56 – The Importance of Governance for Trusting AIFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

In this episode, Kenny sits down with Chris Allaire, Founder and CEO of Averity, to make sense of how AI is reshaping hiring and staffing — and where it’s still nowhere near ready.Having spent nearly 30 years placing engineering and data teams, Chris has watched every wave of automation hit recruitment. His take? AI can speed things up, but it can’t replace the trust, intuition, or honesty that great hiring depends on. We explore how roles are evolving, what skills are becoming essential, and how leaders can introduce AI without losing the human connection that great hiring depends on.If you’re leading teams across tech, operations, or talent, this conversation will help you navigate AI with more realism, more clarity, and a stronger sense of what should stay human.Chapters00:00 – Introduction and Chris' Background02:45 – The Evolution of Technology and Communication05:29 – AI: Understanding Its Infancy and Misconceptions08:03 – Human in the Loop: The Importance of Oversight10:32 – The Role of AI in Recruitment and Organizational Change13:08 – The Impact of AI on the Workforce and Job Roles15:31 – Trust as the Currency in AI and Human Interaction18:18 – Trends in AI Recruitment and Future Skills22:57 – Psychology of Change: Adapting to AI in the Workplace28:19 – Final Thoughts: The Human Element in AI and BusinessFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

Many teams assume AI has to be driven by IT – but that’s no longer true. In this episode, we break down why the best AI outcomes now come from the people closest to the work. We explain how IT’s role is shifting to enablement and why 80% of adoption is really about people, process, and everyday workflows.Submit your questions at [email protected] to be featured in our weekly Q&As.Chapters00:00 The Evolving Role of IT in AI Adoption03:06 Empowerment of Non-Technical Teams in AI ImplementationFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

Too many companies try to roll out AI everywhere at once – and end up stuck. In this episode, we break down a practical way to start small, prove value fast, and choose the right first project. We explain why hero workflows – small teams, high-impact work — create the quickest and most visible wins, and how to spot them inside your organisation.Submit your questions at [email protected] for a chance to be featured in our weekly Q&As.Chapters00:00 Introduction to AI Implementation01:12 Incremental AI Adoption Framework03:12 Identifying Hero Workflows04:24 Practical Use Cases for AIFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

In this episode of The AI Opportunity, Erik Nakamura, CFO of Journal Technologies joins us to unpack how AI can genuinely improve the way finance works, without overwhelming the people who keep it running.Drawing on years of building high-performing teams, Erik explains why the real opportunity isn’t in chasing every new tool, but in choosing where AI belongs – applying it to the repeatable, low-value workflows that drain time, distract attention, and slow strategic progress. When leaders manage AI intentionally, he argues, teams gain clarity, capacity, and calm.Erik also shares how to redesign finance processes so they become reliable systems rather than recurring emergencies, why visibility and alignment matter more than automation alone, and how CFOs can guide their teams through AI adoption with transparency and purpose.For leaders in finance, operations, and strategy, this episode offers a practical blueprint for using AI to build smarter, more scalable teams – not by adding more work, but by managing the work that don’t create value in the first place.Chapters:00:26 – Opening & Introductions01:49 – The State of AI Today and How It’ll Evolve for Finance08:48 – Turning Compliance From Events Into Reliable Processes14:06 – Staff Fear, Adoption, and Human-AI Collaboration17:47 – The Importance of Velocity: Move Fast, But Don’t Rush20:25 – Aligning AI with Company Values & Strategy26:21 – Why Some CFOs Resist Change — and How to Bring Them In33:20 – Quick Fire Round and ClosingFind us on our socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

In this Q&A episode, Kenny addresses where to start using AI in the workplace. The discussion emphasizes the importance of focusing on specific goals and identifying areas of friction within workflows. We advocate for starting with small, manageable AI solutions that can have a high impact, while also stressing the necessity of human oversight in the implementation process. This approach not only boosts morale but also helps teams build confidence in using AI effectively.Submit your questions at [email protected] for a chance to be featured in our weekly Q&As.Chapters00:00 Understanding Where to Start with AI03:21 Focusing on Small, High-Impact AI Solutions05:15 The Importance of Human Oversight in AI ImplementationFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

In this session, Kenny addresses the safety of using AI with company data, particularly in regulated industries like financial advisory. He discusses the inherent risks of AI, especially when using public tools, and emphasize the importance of understanding data management policies. The conversation highlights best practices for securely integrating AI into business operations, treating AI as a new team member, and ensuring compliance and data privacy.Submit your questions at [email protected] for a chance to be featured in our weekly Q&As.Chapters00:00 Introduction to AI Safety Concerns01:28 Understanding AI Risks with Company Data03:24 Best Practices for Using AI SecurelyFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

In this episode, Rob Amor, former COO of Farfetch, Tesco and Cambium, joins us to unpack how AI is reshaping the way businesses operate, lead, and connect with customers. From rising consumer expectations to the shift toward smarter, more transparent workplaces, Rob explores why the future belongs to leaders who stay curious and build with collaboration at the core.He shares a grounded take on where AI truly delivers value, how to bring your team along the journey, and why rethinking your processes — not just your tech stack — is key to unlocking real impact.If you’re a COO or business leader figuring out how to introduce AI without losing the human touch, this conversation is your practical playbook for starting small, learning fast, and scaling what works.Chapters00:00 The changing expectations around AI in business06:40 Why clarity and communication are key to adoption12:15 Managing fear and building team buy-in19:30 The COO’s role in driving practical AI outcomes26:20 Leading with curiosity and realismFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

In our first Q&A episode, Kenny addresses the concern about AI's impact on jobs, emphasizing that AI will not necessarily eliminate jobs but will shift their nature. The conversation explores how AI can take over repetitive tasks, allowing humans to focus on more creative and judgment-based work. We encourage listeners to view AI as a tool for enhancing their work experience rather than a threat, and to identify areas where AI can assist them in their daily tasks.Submit your questions at [email protected] for a chance to be featured in our weekly Q&As.Chapters00:00 Introduction to AI and Job Concerns00:59 The Shift in Job Nature Due to AI03:26 Embracing AI as a Tool for EnhancementFind us on socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

In this episode, Kenny sits down with Lucky Gobindram, President and SVP, Global Sales of Kinemeric, to break down what practical AI adoption really looks like for small and medium-sized businesses.Lucky shares how to spot the operational bottlenecks where AI can make a measurable difference, why leaders should focus on proof of value before chasing scale, and how one home improvement company used AI to cut training time and unlock new efficiency.They also unpack the biggest misconceptions around AI — why many companies confuse experimentation with execution, and how to align AI initiatives with business goals instead of hype cycles.We explore:The mindset shift from automation to augmentationHow small businesses can measure AI’s impact without a massive data teamA real-world case study of AI improving training and efficiencyThe leadership traits that separate AI success stories from failuresChapters00:00 Introduction to AI Opportunities for Businesses02:32 Understanding AI: Augmentation vs. Automation08:33 Identifying AI Use Cases in Organizations10:05 Measuring AI Impact and Return on Investment15:29 Real-World AI Implementation: A Case Study24:10 Navigating the AI Hype Cycle34:22 Future AI Opportunities and Leadership AdviceFind us on our socials:🔗 Follow Kenny on LinkedIn: https://www.linkedin.com/in/kennyalegbe/🤖 Follow Brim on LinkedIn: https://www.linkedin.com/company/joinbrim/📩 For business or guest inquiries: [email protected]

Welcome to The AI OpportunityHosted by Kenny Alegbe, this podcast shares practical, no-nonsense advice on how to bring AI into your business to grow revenue, cut costs, and manage risk.Each 20-minute episode is clear, actionable, and easy to put into practice.