In a recent episode of the CX Iconoclast (From Cost-Cutting to Customer Growth: A Smarter AI Strategy) , Richard Owen sat down with McKinsey partner Tey Bannerman to explore how AI is reshaping enterprise customer strategy. Bannerman’s key takeaway was clear: 

“Predictive data gives leaders scale. Intuition alone simply can’t reach 100,000 customers.” 

It’s a simple truth, but one with profound implications for how leaders manage customers, careers, and growth in the AI era. 

Why Intuition Falls Short 

Executives have long relied on instinct and experience to make decisions. Pattern recognition and “gut feel” earned many a seat in the boardroom. But Bannerman argues that when companies manage tens or hundreds of thousands of accounts, instinct alone collapses under the scale of complexity. 

Prediction changes the equation. With predictive AI, leaders can see churn and expansion risks 12–18 months ahead—well before they surface in dashboards or surveys. That foresight gives leaders the leverage to act at scale, while intuition guides the “how” and “why” of those actions. 

From Cost Cutting to Growth Creation 

Too often, enterprises view AI through the lens of efficiency: how many jobs or costs can be eliminated. Bannerman highlights a different path. In one B2B payments case study, the company reoriented its AI deployment around retention and growth, not cost reduction. 

• Predictive models flagged at-risk customers. 

• Prescriptive tools recommended the best time and reason to reach out. 

• Frontline employees were engaged as co-designers of the system, ensuring adoption. 

The result: AI didn’t displace employees—it empowered them to deliver better outcomes. 

The Human Side of Adoption 

Bannerman warns that fear of job loss and poorly designed tools can stall AI initiatives. Employees must see themselves as teachers of the machine, not victims of it. Leaders must communicate that Customer AI isn’t about replacing people, but about amplifying their expertise. 

This lesson mirrors what we teach in the Customer AI Masterclass: successful AI adoption depends as much on organizational design and engagement as it does on data science. 

Lessons from the Customer AI Masterclass 

The Bannerman conversation reinforces several modules of the Masterclass: 

• Lesson 2.3 – The Three Types of AI: Why predictive and prescriptive AI drive outcomes, while generative AI fills in the missing signals. 

• Lesson 2.4 – Mapping AI to Problems: How predictive foresight and prescriptive actions create measurable growth, not just efficiency. 

• Lesson 5.7 – Organizational Engagement: Why frontline employee involvement is critical for AI adoption and impact. 

These lessons converge on a single insight: AI elevates leaders when it is used to scale judgment, not replace it. 

The Career Imperative 

For CX, CS, and RevOps leaders, the professional message is direct: intuition may get you in the room, but predictive AI keeps you there. Executives who master AI-driven foresight and prescriptive playbooks don’t just manage customers—they drive strategy. 

That is why the Customer AI Masterclass was built: to equip professionals with the frameworks, tools, and fluency to become the leaders others follow.