Prof Gianvito Lanzolla: Strategy in the World of Data and AI

AI is changing the economics of business. But it is not rewriting the fundamentals of strategy.

In this episode of Scouting for Growth, I sit down with Professor Gianvito Lanzolla, Professor of Strategy at Bayes Business School, advisor to boards and CEOs, and co-author of Diversification in the World of Data and AI, to examine what actually creates competitive advantage when access to intelligence is rapidly becoming ubiquitous.

The uncomfortable truth is that better technology alone does not create a better strategy. Being early to AI can accelerate learning, but scaling before you understand how the technology creates value, how the organization captures that value, and what customer problem it solves can simply mean buying expensive learning. Gianvito makes an important distinction between being early for learning and being early for scaling.

We then explore why data in context matters more than data volume. Tesla's understanding of driving behavior can translate naturally into insurance because the data is relevant to risk. Tesco's knowledge of what customers buy did not automatically reveal what they wanted to watch. The strategic question is not how much data you hold, but what the data describes, how it was generated, and which decisions it can improve.

That same discipline applies to diversification and governance. Companies still need a credible right to win, supported by continuous data in context, domain expertise, and the ability to orchestrate an ecosystem. And as AI increasingly influences or makes decisions, governance cannot remain a sequence of static gates. Gianvito argues for adaptive governance built around monitoring, feedback loops, escalation mechanisms, and the ability to revisit decisions as the technology evolves.

Most importantly, the conversation brings strategy back to fundamentals. If AI ultimately becomes more like electricity than a source of differentiation in itself, advantage will come from the business model built around it. Gianvito leaves leaders with three questions: Value, Visibility, and Viability. What new customer problem can you solve? What can you see or do now that was previously impossible? And what can you organize and execute economically today that you could not before?

Because AI may change the context, the economics, and even the architecture of decision-making. But competitive advantage still depends on understanding where value is created, why you have the right to capture it, and how you build an orga