Why Most AI Projects Fail — McKinsey's Tey Bannerman on Trust, Design & Adoption
May 27, 2025
In this episode of Advising the Advisors, we dive into creating differentiated value with AI in consulting.
🔍 Topics Covered:
• The critical role of human-centered design in successful AI adoption
• Why technology-first approaches often fail to deliver value
• Strategies for building trust and driving user adoption
• How consulting business models are evolving with AI
• The importance of domain expertise in an AI-enabled future
🎧 Listen now to hear Tey Bannerman of McKinsey & Company share actionable insights from leading enterprise AI implementations.
Most AI tools fail — not because of bad tech, but because no one uses them.
In this episode of Advising the Advisors, McKinsey’s Tey Bannerman reveals why AI adoption requires 5x more investment than development — and how design thinking drives real transformation in enterprise AI.
What You’ll Learn:
In this episode of Advising the Advisors, McKinsey’s Tey Bannerman reveals why AI adoption requires 5x more investment than development — and how design thinking drives real transformation in enterprise AI.
What You’ll Learn:
- Why successful AI implementation requires 5x more investment in adoption than technology
- How to blend human-centered design with AI strategy to ensure solutions actually get used
- The framework for building trust in AI tools through user feedback loops and internal evangelism
- Why boards need to shift from viewing AI as a technical initiative to a business transformation opportunity
- How consulting firms are evolving from project-based work to AI-powered continuous partnerships
Tey Bannerman is a Partner at McKinsey & Company and Head of McKinsey Design Europe, specializing in the intersection of AI implementation and human-centered design. With a background in computer science, economics, and design, he leads cross-functional teams helping large organizations successfully scale AI solutions across banking, retail, and fintech sectors. Tey brings a unique triple-threat perspective, combining business strategy, technical expertise, and user-centered design, to help enterprises navigate AI adoption and digital transformation.
Episode Highlights:
- [05:30] Why Design Needs to Lead AI Strategy
To build successful, scalable AI solutions, start with human needs, not just technology. Tey highlights that cross-functional teams are essential, but the design lens plays a critical role from the very beginning. It's about asking where people need help. Understanding user needs first and combining that with what's technically possible and viable for the business helps to ensure that what you build gets adopted and delivers real value.
- [11:44] Why 5x Your AI Budget Should Go to Adoption
Most tech projects fail not because the tools don't work, but because people don't use them. To drive adoption, you need more than just dashboards and predictive models; you need people, programs, and trust. That means investing in UX researchers, building feedback loops into the product, showing users how the tool helps them day-to-day, and socializing wins across the team. When adoption becomes part of the build, not an afterthought, you create something people want to use, not just something they could use.
- [21:32] A Designer at the Top of Consulting
Designers have a vital and growing role in management consulting, but it's still rare to see them in senior positions. Tey's journey at McKinsey shows how bringing together design, tech, and business fluency can reshape how consulting firms build value for clients. Starting from human needs, designers can drive a deeper, more relevant impact. But to do that, they need a seat at the table.
More Highlights from this Episode:
- [03:53] Building AI for Humans, Not Hype
- [08:19] Why AI Should Feel “Boring”
- [19:53] AI Is Not an IT Project
- [27:06] How AI Is Reshaping the Consulting Model
If your business is investing in AI but struggling to see real impact, this episode is for you. Discover the hard lessons, the breakthroughs, and the strategies that separate AI success from failure.
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Episode Resources:
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