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 impact
• How the “Summer of AI” initiative reached 16,000 participants across 14 countries
• The role of digital ninjas in driving cultural change
• How AI is augmenting professionals rather than replacing them
• Why KPMG is focused on curated knowledge and client-specific intelligence
• Lessons learned from early adoption, including why managing expectations matters

James 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 lifecycle
• How AI is improving forecasting, testing, and early-stage product screening
• The power of external innovation strategies like acquisitions and licensing
• Why speed matters, but discipline matters more
• What established firms can learn from startups without falling for the “fail fast” trap
• Real-world examples from litter robots to autonomous aircraft landings

Whether 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.