Consulting the Future

What does it really take to move enterprise AI from impressive demos to decisions that show up in quarterly results?One year into his role as Senior Vice President, Americas Consulting, Neil Dhar sits at the intersection of strategy, capital allocation, and technology execution. Leading the firm’s Americas business and a team of close to 100,000 consultants, he has a front-row view into how large organizations are reassessing their AI investments.From global healthcare leaders like Medtronic to luxury retail brands such as Neiman Marcus, the conversation has shifted. Early proofs of concept helped executives understand what was possible. Now the focus is firmly on proof of value and on whether AI can drive growth, competitiveness, and measurable return.In this episode, I speak with Neil Dhar about what has changed in the boardroom over the past year and why ROI has become the central question.Drawing on more than three decades in finance and private equity, including senior leadership roles at PwC, Neil explains why AI is increasingly being treated as a capital allocation decision rather than a technology experiment.Every dollar invested has to earn its place, whether through productivity gains, operational improvement, or new revenue opportunities. Vanity projects no longer survive scrutiny, especially when boards and investors expect results on a much shorter timeline.We also explore how IBM is applying these same principles internally. Neil shares how the company has identified hundreds of workflows across the business, prioritized those with the strongest economic impact, and used AI and automation to drive large-scale productivity gains. The result is a potential $4.5 billion in annual run rate savings by 2025, with those gains being reinvested into innovation, people, and future growth.It is a candid look at what happens when AI strategy, leadership accountability, and disciplined execution come together inside a global organization.If you are a business leader trying to separate real value from hype, or someone wrestling with how to justify AI spend beyond experimentation, this conversation offers a grounded perspective on what enterprise AI looks like when it is treated as a business decision rather than a technology trend.Are you ready to rethink how AI earns its place inside your organization, and what proof of value really means in 2026?Useful LinksConnect With Neil DharIBM Institute for Business Value, “The Enterprise in 2030” studyLearn More About IBM Consulting

Could AI be the fastest way to make a broken process more expensive?In this episode of Consulting The Future, I’m joined by Bill Briggs, CTO at Deloitte, to unpack why so many organizations can produce impressive AI pilots, yet still struggle to show real business change. Bill has spent nearly three decades advising leaders across the private and public sectors, and he has a clear point of view on what separates pilot activity from outcomes you can measure, defend in the boardroom, and scale across the enterprise.We talk about what “good ROI” actually looks like when you strip away dashboards designed for show. Bill explains why early AI efforts often fall into incrementalism, where teams layer new tools on top of old workflows, then wonder why productivity does not move. He also shares a line that will land with anyone watching cloud bills rise, you can end up “weaponizing inefficiency” and turning yesterday’s background automation into today’s token burn.A big thread in our conversation is the “innovation flywheel,” and Bill translates that into plain English. He argues that innovation cannot live in a silo with nicer office space and a few foosball tables, it has to come from the people closest to the work who know where the friction and “knuckleheadery” hides. He shares Deloitte research that shows a dramatic trust gap, with enthusiasm for AI high in the C-suite, but dropping sharply as you move toward frontline employees. The takeaway is simple, if your people do not feel included, they will resist it, and if they feel threatened, they will quietly avoid it.We also get into what it takes to move fast without losing control as GenAI and agentic systems spread. Bill points to a pattern he sees repeatedly, organizations invest heavily in technology, but underinvest in the parts that make it safe and sustainable, training, guardrails, process controls, and the engineering discipline that bakes security and governance into how solutions are built. That leads into a practical conversation about rethinking processes from scratch, and why “waiting for the next model release” can become a form of paralysis that competitors will happily exploit.Finally, Bill offers a refreshingly honest look at technical debt, including his three-part framing of malfeasance, misfeasance, and non-feasance, and how leaders can take a more surgical approach to modernization instead of repeating tired slogans like “cloud good, mainframe bad.” We close with a human moment too, Beach Boys, pinball machines, and a reminder that the best tech conversations still sound like real conversations.So where do you think most organizations are right now, building real outcomes, or putting a shiny layer on top of yesterday’s problems, and what would you change first, and please share your thoughts?

In this episode of Consulting The Future, I’m joined by Julie Teigland, Global Vice Chair – Alliances & Ecosystems at EY, to unpack the growing role marketplaces are playing in enterprise AI adoption. At a time when organizations are overwhelmed by tools, vendors, and bold claims, Julie offers a pragmatic view of how marketplaces can collapse complexity rather than add to it.We begin by exploring why so many AI initiatives stall between pilot and production. The issue, as Julie sees it, is rarely a lack of technology. It is the friction between tools, governance, integration, and operating models. Marketplaces, when designed well, bring together pre-vetted solutions, integration patterns, security signals, and governance frameworks. That coordination reduces the invisible work leaders often underestimate, such as vendor risk reviews, compliance checks, and architecture validation.Julie is candid that not all marketplaces are equal. The ones that create value are designed around business outcomes, not product listings. Fraud reduction, supply chain resilience, or industry-specific cost transformation efforts require curated ecosystems. That means benchmarks, peer usage patterns, reference architectures, and assurance around regulatory alignment. For executives facing board-level scrutiny, that difference matters.We also dive into risk and accountability. Julie highlights how many organizations focus on model ethics and accuracy, yet overlook integration risk. Once AI is embedded into workflows, the questions shift. Who owns the decision? How are outcomes logged and audited? What happens when multiple vendor systems interact? This is where governance can break down, especially at scale.Through alliances with leaders such as Microsoft and SAP, EY is helping shape how AI solutions are vetted and deployed across industries. Julie shares how EY applies a “client zero” approach, using its own marketplace internally to test value, resilience, and governance before scaling to clients. With 70,000 clients, 668,000 servers, 13,600 workflows, and 269 million transactions processed daily, the system is tested constantly under real operational pressure.We also examine the influence of the EU AI Act and the contrast between innovation-first and responsibility-by-design approaches across regions. Julie argues that speed and governance are not opposing forces. True acceleration comes from industrializing governance rather than bypassing it.If AI success depends less on technological brilliance and more on clarity, orchestration, and trust, then marketplaces may be evolving from simple app stores into operational control planes. The question is not whether ecosystems matter, but how deliberately you design them. So as AI adoption accelerates inside your organization, are you simply adding tools, or are you building a marketplace strategy that can withstand scrutiny and scale?

What separates organizations that talk about AI from those that actually redesign how work gets done? In this episode of Consulting the Future, I sit down with David Martin, Senior Partner at BCG, to explore what enterprise transformation really looks like beyond the headlines. This conversation goes straight to the heart of what consulting leaders are advising boards and C suites right now.David leads BCG’s People and Organization business and sits on the firm’s global AI leadership team, which gives him a front row seat to how large organizations are approaching AI at scale. He shared why companies seeing real returns are doing fewer things with greater ambition, rather than launching hundreds of disconnected pilots. The difference is not access to tools, it is clarity of workflow and leadership intent.We unpacked why so many organizations remain stuck in experimentation. According to David, the shift happens when leaders rethink work end to end, redesign roles, and embed AI directly into core processes rather than layering it on top. The firms making progress are not chasing marginal time savings. They are restructuring how value is created across functions such as engineering, marketing, and finance.Training emerged as a defining theme. David explained why short workshops are rarely enough and why immersive, hands on learning makes the difference. Supportive leadership behavior increases effective adoption dramatically, and curiosity at the top signals psychological safety across teams. Consulting advice today is as much about mindset and culture as it is about architecture and infrastructure.We also discussed agentic AI, governance risk, and the reality of shadow AI inside enterprise environments. While executives worry about low adoption, many employees are already experimenting outside formal systems. The consulting challenge is balancing innovation with controls, embedding governance without stifling momentum, and aligning IT, HR, and operating models around a shared framework.David reinforced a simple but powerful model. Ten percent algorithms, twenty percent technology, and seventy percent people and process. That ratio has remained consistent across digital waves, and it continues to define where transformation efforts succeed or stall. Consulting firms like BCG are increasingly focused on redesigning workflows and redefining competencies, not simply recommending new tools.As we look toward 2026, David sees acceleration ahead, particularly in healthcare and knowledge intensive sectors. The pace of change will not slow, which makes structured advisory support even more central to enterprise strategy. The question is no longer whether to adopt AI, but how to do so with intent, discipline, and a clear operating vision.If you are a business or technology leader thinking about your own roadmap, this episode offers grounded insight from someone helping define the global playbook. What role should advisory firms play in shaping your transformation strategy, and where do you need external perspective most? I would love to hear your thoughts.

On this episode of Consulting the Future, I’m joined by Matt Strentz, co-founder of Iversoft, to unpack what the next wave of digital product development really looks like.Matt takes us inside Iversoft’s journey from a small mobile studio at the dawn of the iPhone era to an international innovation partner trusted by enterprises and startups alike. We explore why mobile-first, multi-platform strategies are now essential for gathering real-time user feedback and building products that truly stick.The conversation also dives into Iversoft’s process-driven consulting model, where transparency and quality assurance begin on day one. Matt shares how human-centered design and user experience must be baked into the foundation of every platform, and why AI should be treated as a practical productivity enhancer rather than a shiny buzzword.From adapting lessons across industries like healthcare, aviation, and construction to building long-term client partnerships based on trust, this episode highlights a pragmatic approach to digital transformation. If you want to understand how to prepare your business for emerging technologies without falling into endless pilot projects, this conversation is packed with insights.*********Visit the Sponsor of Tech Talks Network:Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careeristhttps://crst.co/OGCLA

When AI steps into the boardroom, it’s rarely a quiet arrival. Expectations are set high, with promises of sharper productivity, streamlined workflows, and measurable efficiency gains. But as Francesco Brenna, Global Leader of AI Integration Services at IBM Consulting, points out in this episode of Consulting the Future, the true opportunity lies in something far deeper than speed. It’s about reimagining the way entire businesses function.Recorded during a sweltering summer in New York, our conversation breaks down what “agentic AI” really means for leaders under pressure to make AI more than a buzzword. Francesco draws a clear line between the passive assistants many companies have experimented with and the next generation of intelligent agents that not only advise but act. This shift, he argues, demands more than dropping AI into an existing system. It calls for rebuilding processes from the ground up with business outcomes as the starting point.We dig into why data readiness remains the number one barrier to success, despite years of investment in platforms and governance. Francesco introduces the concept of “data products” to ensure AI agents operate with the right context and memory. He outlines IBM’s three-layer approach to agentic applications: user experience, orchestration, and data. He also explains why standards like Model Control Protocol (MCP) may be the key to integrating AI with legacy systems at scale without sacrificing security or trust.Francesco shares real-world results from IBM’s work in customer service, insurance, and pharma, where agentic AI has dramatically improved containment rates, reduced months of work to weeks, and enabled smarter decision-making for knowledge workers. He is candid about the human side of adoption, detailing how IBM uses hackathons, hands-on experimentation, and human-centered design to build confidence and capability across the workforce.For enterprise leaders grappling with how to move AI out of the pilot phase and into meaningful, measurable impact, this conversation offers a grounded, practical roadmap built on doing the right AI, and doing it right.

In this episode of Consulting the Future, I’m joined by James Osborne, Chief Digital Officer at KPMG UK, to explore how one of the world’s largest professional services firms is approaching AI with clarity, intention, and scale.James shares what he’s learned in his first year as CDO, including the rollout of Ava, KPMG’s internal generative AI assistant now used by over 11,000 employees. We unpack how Ava is surfacing firmwide expertise, why adoption is about people before platforms, and how KPMG’s Trusted AI Framework is helping to embed ethical, human-centric principles into every use case.We also dig into:The mindset shift required to move from AI hype to real-world impactHow the “Summer of AI” initiative reached 16,000 participants across 14 countriesThe role of digital ninjas in driving cultural changeHow AI is augmenting professionals rather than replacing themWhy KPMG is focused on curated knowledge and client-specific intelligenceLessons learned from early adoption, including why managing expectations mattersJames also reflects on how AI can be both revolutionary and familiar, referencing the 1966 ELIZA chatbot as a reminder that hype cycles always have history. His advice to other organisations is simple: don’t wait to get started. Start small, stay pragmatic, and bring your people with you.

Why do up to 90% of new product launches still fail, even in the age of AI?In this episode of Consulting the Future, I’m joined by Stuart Jackson, Vice Chair of L.E.K. Consulting and author of Predictable Winners, a new book that distills nearly four decades of innovation strategy into a practical framework for reducing failure rates in product and service development.Stuart shares the hard truths behind failed innovation efforts, from siloed thinking and unmanaged risk to the myth of the “big idea.” He also reveals what top innovators do differently and how AI is beginning to play a critical role in spotting demand signals, identifying unmet needs, and shaping smarter bets.We explore:Why many great ideas still fail without systems to manage risk across the innovation lifecycleHow AI is improving forecasting, testing, and early-stage product screeningThe power of external innovation strategies like acquisitions and licensingWhy speed matters, but discipline matters moreWhat established firms can learn from startups without falling for the “fail fast” trapReal-world examples from litter robots to autonomous aircraft landingsWhether you're building a startup, leading R&D, or navigating innovation inside a Fortune 500, this episode is packed with grounded insights to help you innovate with more clarity, more precision, and a lot less waste.If you want to shift from product guesswork to a repeatable innovation strategy, this is the place to start.

In this episode of Consulting the Future, I sit down with Brad Herndon, a partner in PwC’s Customer Transformation practice, to unpack the real-world challenges and opportunities at the intersection of customer data, AI, and marketing strategy.Brad draws on over 20 years of experience in data and analytics to explain why businesses still struggle to use their data effectively, what’s changing in the way customer information is collected and applied, and how organizations can evolve their personalization strategies without crossing into territory that risks trust. He also reflects on the shift from isolated data silos to more unified, audience-level insights that still respect privacy and consent.This conversation offers a clear-eyed look at the practical uses of AI, the limits of over-personalization, and the technologies helping companies move toward more relevant and respectful customer engagement. Brad also shares his thoughts on the value of slowing down, citing Cal Newport’s book Deep Work as a personal and professional inspiration for navigating this complex digital landscape.If you want to understand how customer-centric strategies are evolving inside real enterprises, and how firms like PwC are helping shape that future, this is the episode to hear.

In this episode of Consulting the Future, I sit down with Varun Bijlani, Global Managing Partner for Hybrid Cloud Services at IBM Consulting, to unpack the real-world challenges and opportunities facing enterprise leaders today.Varun shares candid insights on why the shine has come off many digital and cloud transformations and what needs to change to deliver measurable returns. We discuss the pitfalls of being hybrid by default and how a hybrid by design strategy can radically shift how businesses deploy AI, manage data and keep costs in check.Drawing from global client examples, Varun outlines how companies are moving from generic IT spending to targeted investments that protect margins, speed up time-to-market and unlock new value from AI-driven innovation. We also touch on the future of infrastructure, from embedded security and energy efficiency to the evolving role of agent-based AI.If you are navigating the next phase of your company’s cloud journey or questioning how to align IT architecture with financial results, this conversation will give you a clear-eyed perspective from someone helping shape transformation at scale.Listen in and join the discussion on how consulting, design thinking and practical frameworks can turn technology promises into real business performance.

What does reinvention look like inside a global consulting firm with nearly $20 billion in revenue? In this episode of Consulting the Future, I speak with Mohamad Ali, Senior Vice President at IBM Consulting, about how the company is navigating the shift toward generative AI—one practical use case at a time.Mohamad brings a rare blend of experience across cybersecurity, data, and enterprise software, shaped by leadership roles at IDG, Carbonite, and now IBM. This conversation unpacks how that background is informing IBM Consulting’s current transformation, including how teams are working differently, where AI is being applied effectively, and why an open ecosystem matters now more than ever.We look closely at how generative AI is already changing day-to-day consulting work. From improving decision speed to redesigning complex workflows, Mohamad shares examples of client engagements that show real outcomes rather than hypothetical benefits. There’s a strong focus on using AI to amplify human expertise, not displace it—a theme that carries through his approach to upskilling and workforce development.As consulting shifts toward more software-driven models, Mohamad outlines how IBM is adapting its own culture and mindset to stay relevant in a digital-first environment. That means faster iteration, deeper client collaboration, and new ways of thinking about what consulting looks like in the age of automation.If you're wondering how to build an AI strategy that works in the real world—not just in pilot programs—this conversation offers grounded insights from inside one of the largest consulting organizations on the planet. It also raises a broader question that every leader should be asking: how do we make AI something that empowers, rather than replaces, the people at the heart of our businesses?Listen in to learn how IBM Consulting is approaching the future—not as a trend to chase, but as a challenge to shape.

Inside the Accenture Tech Vision Report and the Future of AI-Driven BusinessWhat does it really take to turn AI from hype into value? In this episode of Consulting the Future, I sit down with Mary Hamilton, Global Lead for Accenture's Connected Innovation Centers, to unpack the key findings from Accenture’s 25th Tech Vision report and explore how artificial intelligence is reshaping business.We discuss how AI is moving beyond automation to become a true collaborator in the enterprise. From generative design to intelligent agents and robotics, Mary explains how technology is evolving from instruction-led tools to systems that understand intent and adapt in real time.Topics we cover include:Why trust is the foundation for AI adoption and how to build it rationally and emotionallyHow organizations can inject personality into AI to avoid sounding the same as everyone elseThe concept of cognitive digital brains and how multi-agent systems are transforming operationsHow robotics are becoming more flexible and applicable across logistics, manufacturing, and healthcareThe importance of experimentation, upskilling, and making employees part of the AI journeyHow to measure AI success using adoption, engagement, customer satisfaction, and ethical alignmentMary also shares how Accenture is helping clients bring these ideas to life through its innovation centers and how leaders can start turning AI into meaningful impact.If your organization is thinking seriously about how to scale AI, build trust, and stay competitive in an increasingly autonomous world, this episode offers a practical, research-backed roadmap to help guide your next steps.Is your business ready to treat AI as a partner rather than just a tool? Let’s find out.

In this episode of Consulting the Future, we explore how Generative AI is quietly reshaping the consulting profession, not through bold predictions, but through real-world experimentation and measurable outcomes.Recorded as part of the Tech Talks Network, this conversation features Vladimir "Vlad" Lukic from Boston Consulting Group (BCG), who unpacks findings from a major research collaboration between BCG, Boston University, and OpenAI’s Economic Impacts team. The study set out to measure how GenAI tools like Enterprise ChatGPT with Advanced Data Analysis perform in the hands of consultants tasked with complex data science assignments.What they found is already shifting how professional services firms think about productivity, talent, and technical capability. Vlad explains how BCG consultants with no prior coding experience were able to complete predictive modeling and statistical analysis tasks at 86 percent of the performance benchmark set by experienced data scientists, and even did so 10 percent faster on average. But the implications go far beyond speed.We discuss what happens when AI becomes an exoskeleton for knowledge workers, why over-reliance on tools can create new learning gaps, and how firms can design workflows that balance automation with skill retention. Vlad shares how GenAI is being used at BCG to transform onboarding, speed up ideation, and even shift the number of hires needed on high-volume projects.This is not about replacing consultants. It’s about enhancing their capabilities and rethinking how expertise is developed and deployed. Vlad also touches on how these insights extend beyond the office, from helping his kids understand entrepreneurship to reimagining family travel planning through AI-assisted decisions.Whether you're leading a consulting practice, working in enterprise transformation, or simply looking for a grounded understanding of how GenAI is being applied today, this episode offers a candid look inside a firm that is already putting it to work.What will GenAI change in your workflow? And how are you preparing your teams to not just use these tools, but think with them?Join the conversation and let us know what the future of consulting means to you.

What does enterprise security really look like in 2025, especially as AI, cloud-first architecture, and hybrid work models converge to reshape the perimeter? In this episode of Consulting the Future, recorded live at IGEL Now & Next 2025 in Miami, I am joined by Marissa Schmidt, Senior Director Analyst at Gartner, for a grounded conversation that cuts through the noise.Marissa brings deep insight into the evolving role of endpoint security in today’s distributed enterprise. With responsibilities spanning cloud networking, application security, and generative AI, she offers a rare vantage point into how these threads are coming together and where businesses need to refocus.Together, they explore the growing complexity of multi-cloud environments, the operational challenges of managing dozens of disconnected security tools, and why visibility, segmentation, and zero trust architecture are no longer optional. Marissa explains how the operating system layer is quickly becoming a strategic linchpin in endpoint resilience and why preventive security needs to move closer to the edge.The discussion also covers how AI is being used not just for threat detection, but for integrating disparate security signals and automating next-step actions in complex environments. Marissa shares what Gartner is seeing in the field, from the practical challenges of implementation to the cultural shifts required to adopt scalable security strategies.Beyond the technology, we hear about her keynote reflections, the importance of authenticity and adaptability in leadership, and how research-backed guidance can empower IT decision-makers to move from theory to execution.For business and technology leaders navigating cloud transformation, endpoint strategy, or zero trust implementation, this episode offers clear, research-informed direction.Are your endpoint and cloud strategies designed for the future or still solving yesterday’s problems?

In a financial world increasingly shaped by automation and machine learning, how can businesses stay one step ahead of AI-driven fraud?In this episode of Consulting the Future, I sit down with Bradley Niedzielski, Audit and Assurance Partner for Digital Transformation at Deloitte, to explore how generative AI is transforming the fraud landscape and what that means for finance leaders. As synthetic identities, forged documents, and deepfake impersonations grow more convincing, traditional defenses are no longer enough.Bradley draws on Deloitte’s research, revealing that AI-driven fraud in the United States could exceed 40 billion dollars by 2027. Over one in four organizations have already encountered deepfake fraud, yet only a small percentage place technology at the center of their defense strategy. We explore the reasons behind this disconnect and the urgent need to modernize fraud risk management.From AI governance and scenario planning to embedding intelligent automation in core finance functions, Bradley offers a clear-eyed view of what’s changing, what’s at stake, and how businesses can adapt. He explains the role of agentic AI in automating end-to-end workflows, accelerating financial close processes, and freeing finance teams to focus on strategy. But with that acceleration comes risk, especially when poor data quality or blind trust in AI goes unchecked.We also discuss how organizations can prepare their people for this shift. Upskilling, transparency, and cross-functional collaboration are no longer optional—they are essential to safely navigate an AI-powered future.If your organization is experimenting with AI or already embedding it into finance operations, this conversation offers timely insights into managing risk, building resilience, and ensuring technology adoption aligns with long-term goals.

How does a firm with over a century of audit history stay ahead in a world shaped by exponential technologies? In this episode of Consulting the Future, we spotlight how EY is reinventing the audit profession from the inside out. Joining the conversation are Marc Jeschonneck, EY's Global Assurance Digital Leader, and Paul Goodhew, EY's Global Assurance Innovation and Emerging Technology Leader.Recorded against the backdrop of rapid change in the assurance industry, this conversation unpacks the strategy behind EY’s $1 billion investment in audit technology. Marc and Paul offer a behind-the-scenes look at how EY is integrating AI, blockchain, and cloud-native tools to transform complex, high-volume audit processes into more streamlined, intelligent systems. Whether it’s using machine learning to surface anomalies or applying blockchain to verify digital asset transactions, the goal is clear: higher audit quality with greater efficiency and trust.But innovation isn’t just a tech play—it’s also about people. The episode explores EY’s focus on user experience, microlearning, and its federated development model that empowers teams to build tools tailored to their specific needs. We also discuss how intuitive design is helping auditors embrace new systems faster, and why fostering a culture of continuous learning is key to keeping pace with technological disruption.Looking ahead, Marc and Paul share how quantum computing, AI agents, and smart contracts could influence the next chapter of the profession. This episode offers valuable insights for anyone involved in risk, compliance, digital transformation, or professional services, providing a clear view of how large consultancies are adapting to—and shaping—the future.Are traditional audit models compatible with tomorrow’s technology landscape? Tune in to find out, and join the conversation on what’s next for assurance in the digital age.

In today’s episode of Consulting the Future, we welcome Carla DeSantis, Partner in Operations Transformation at PwC, for a timely and thought-provoking conversation. Carla unpacks the key findings from PwC’s latest Trends in Digital Operations Survey, offering a rare, inside-out view of why so many companies are still struggling to achieve returns on their technology investments in supply chain and operations.Among the findings, one statistic looms large: 69% of companies report they are not seeing the expected benefits from their tech investments. Carla explores the underlying reasons, including the complexity of integrating new solutions with legacy systems, persistent data quality challenges, and a narrow focus on isolated pain points instead of holistic transformation strategies. She urges leaders to rethink how they approach operational change, emphasizing the need for systemic, end-to-end thinking that moves beyond siloed initiatives.A particularly fascinating part of our discussion centers around AI integration. While nearly all respondents to the survey are experimenting with generative AI, only 20% report widespread operational use. Carla shares what differentiates successful AI adoption efforts: clear, specific use cases that augment human capabilities rather than seeking to replace them. She addresses common misconceptions about AI, particularly the dangerous notion of AI as a silver bullet or a tool for workforce reduction, and highlights the risks that come with misaligned expectations.Carla also stresses the human element behind digital transformation. She advocates for reimagining workforce training as an ongoing journey of continuous learning rather than a one-off event. By involving detractors early and balancing encouragement with accountability, leaders can build a workforce that embraces, rather than resists, new technologies.Finally, Carla looks ahead, discussing how sustainability and evolving regulatory frameworks are becoming increasingly pivotal in shaping operations strategies. She invites listeners to explore PwC’s Digital Operations Report, which provides industry-specific insights and actionable recommendations for companies navigating today's digital complexities.How is your organization approaching digital operations transformation? Are you creating real, sustainable change or chasing short-term fixes? Tune in to gain deeper insights from Carla DeSantis and explore new ways to align technology, people, and strategy for lasting impact.

What does it take to build a digital foundation that supports innovation, profitability, and long-term resilience?In this episode of Consulting the Future, I speak with Andy Tay from Accenture to explore findings from their latest research, Reinventing with a Digital Core. As organizations face increasing pressure to modernize and compete in a tech-driven marketplace, this conversation brings clarity to what it means to evolve with purpose. Tay breaks down Accenture’s approach to building a strong digital core and why it remains one of the most important levers for business reinvention today.We examine three guiding principles that organizations can use to strengthen their digital foundation. These include re-engineering systems to support AI operations, customizing digital advancements to align with specific business goals, and striking the right balance between addressing technical debt and investing in scalable infrastructure. Tay shares how leading firms that raise their innovation investments by at least six percent each year are better positioned to introduce new products, redesign operations, and enter emerging markets with confidence.This episode also covers how a digital core connects critical functions across cloud, data, and cybersecurity, creating a more adaptive and responsive enterprise. With a recommendation to allocate around fifteen percent of IT budgets to manage technical debt, Tay outlines the importance of sustaining evergreen capabilities while embracing new technologies.We also discuss how top-performing companies are seeing up to twenty percent higher revenue growth and thirty percent more profitability by embracing these strategies. Tay emphasizes that responsible AI integration, iterative scaling, and an innovation-first culture are now essential components of any transformation effort.Whether you're in the early stages of rethinking your digital infrastructure or already leading large-scale change, this episode offers timely guidance from someone helping shape enterprise strategy on a global scale.

Can we accelerate our digital ambitions while still keeping a strong moral compass? In this conversation on Consulting the Future, Deborah Golden of Deloitte shares her frontline experiences shaping AI strategies that put ethics at the core, and she offers her predictions for a surge in M&A activity across AI, cloud, cybersecurity and even the nascent space economy. We balance the promise of breakthroughs (like AI‑driven drug discovery and zero‑trust architectures) with the real‑world challenges of bias audits, supply‑chain vulnerabilities and the skills gap. Deborah’s practical advice on blending deep industry know‑how with cutting‑edge technology leaves you equipped to both seize new growth and safeguard against unintended fallout. Where do you see the biggest opportunity or blind spot in today’s tech revolution? I’d love to hear your perspective.