Скачать или смотреть From Cost-Cutting to Customer Growth: A Smarter AI Strategy – with McKinsey partner Tey Bannerman

In this episode of the CX Iconoclast podcast, Richard Owen speaks with Tey Bannerman, a McKinsey partner focused on deploying AI in large enterprises to improve customer retention and growth. Bannerman emphasizes that AI should solve real human and business problems rather than just serve as a technological novelty. He critiques the reflexive use of AI for cost-cutting and job elimination, urging companies to instead prioritize long-term value creation and enhanced customer experience. He shares a compelling case study of a B2B payments company that shifted from cost-cutting to a customer-centric strategy using predictive analytics to reduce churn, highlighting the importance of engaging frontline employees in AI design and adoption.

Their conversation also covers the dual challenges of employee resistance and leadership skepticism when adopting AI. Bannerman notes that fear of job loss and poorly designed tools can undermine adoption unless employees are engaged as co-creators. At the executive level, the challenge is often a cultural reliance on instinct over data, especially when dealing with AI-generated predictions. Bannerman advocates a balanced approach where leadership combines intuition with data to scale decision-making. As he says, "Predictive data gives leaders scale. Intuition alone can’t reach 100,000 customers."

Both he and Owen agree that the way AI is communicated, taught, and integrated - especially through accessible, language-based interfaces - will determine whether organizations succeed or fall behind in what they call one of the most transformative shifts in business history.



Tey Bannerman is a Partner at McKinsey & Company and the former Head of McKinsey Design Europe, where he blends software engineering, human-centered design, and strategic leadership to help major organizations implement AI solutions that deliver real business value. With over two decades of experience, spanning roles as a code‑writing software engineer, startup product designer, and digital agency leader, he has led AI‑powered transformation projects across sectors including banking, retail, fashion, and fintech, always anchored in human needs, ethical design, and tangible outcomes, rather than chasing technological novelty



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