Session
The Execution Gap: Why Your AI Strategy Will Fail (And How to Build One That Won't)
Friday 24 July
14:00 – 15:00
Accelerator
Back to agenda
Last year, every CTO had an AI strategy. This year, most of them have expensive technical debt instead.
The pattern is painfully familiar: boards mandate transformation, CTOs promise results, teams get handed tools they can't integrate. We saw it with multi-cloud adoption - companies spent millions on "vendor independence" and built infrastructure so complex their own engineers couldn't operate it. Now we're watching it repeat with AI, except faster and at larger scale.
Here's the uncomfortable truth: AI isn't failing. Your execution model is.
In this session, I'll show you why smart CTOs keep buying strategies their teams can't deliver—and the decision framework that breaks this cycle. You'll learn:
- The Multi-Cloud Lesson: Why last year's AI+cloud investments became this year's operational nightmares (and what the pattern reveals about your organization)
- The Execution Gap Diagnostic: How to identify whether you're building genuine capability or just performing strategy theater for the board—before you waste millions finding out
- AI as Amplifier, Not Magic: Why AI magnifies whatever you already are. If your processes are inefficient, AI makes you inefficiently faster. If your teams can't execute, AI gives them more sophisticated ways to fail.
- The Capability Audit: Five questions that reveal whether your organization can actually execute what you're about to buy (works for AI, multi-cloud, or the next shiny object from Harvard Business Review)
- Leverage vs. Theater: How to use AI to buy back your team's time and amplify value creation - instead of creating another layer of complexity that requires headcount to manage
AI is like money or a fork: it nourishes or it hurts, depending on how you wield it. Most organizations are about to stab themselves. This session gives you the framework to do otherwise.
What you'll walk away with: A decision model you can apply Monday morning to evaluate whether your AI strategy (or any technology strategy) is building leverage or debt. No vendor pitches. No "it depends" consulting theater. Just honest pattern recognition from someone who's cleaned up after these disasters.
Who should attend: CTOs and technical leaders tired of watching transformation initiatives turn into expensive complexity. Engineering leaders drowning in tools they didn't choose. Decision-makers who suspect their current approach is performative but don't know how to fix it.
Who should skip this: Anyone looking for AI evangelism or validation that their current strategy is working. This session challenges assumptions—constructively, but directly.
Session Note: Thursday or Friday Please xD
The pattern is painfully familiar: boards mandate transformation, CTOs promise results, teams get handed tools they can't integrate. We saw it with multi-cloud adoption - companies spent millions on "vendor independence" and built infrastructure so complex their own engineers couldn't operate it. Now we're watching it repeat with AI, except faster and at larger scale.
Here's the uncomfortable truth: AI isn't failing. Your execution model is.
In this session, I'll show you why smart CTOs keep buying strategies their teams can't deliver—and the decision framework that breaks this cycle. You'll learn:
- The Multi-Cloud Lesson: Why last year's AI+cloud investments became this year's operational nightmares (and what the pattern reveals about your organization)
- The Execution Gap Diagnostic: How to identify whether you're building genuine capability or just performing strategy theater for the board—before you waste millions finding out
- AI as Amplifier, Not Magic: Why AI magnifies whatever you already are. If your processes are inefficient, AI makes you inefficiently faster. If your teams can't execute, AI gives them more sophisticated ways to fail.
- The Capability Audit: Five questions that reveal whether your organization can actually execute what you're about to buy (works for AI, multi-cloud, or the next shiny object from Harvard Business Review)
- Leverage vs. Theater: How to use AI to buy back your team's time and amplify value creation - instead of creating another layer of complexity that requires headcount to manage
AI is like money or a fork: it nourishes or it hurts, depending on how you wield it. Most organizations are about to stab themselves. This session gives you the framework to do otherwise.
What you'll walk away with: A decision model you can apply Monday morning to evaluate whether your AI strategy (or any technology strategy) is building leverage or debt. No vendor pitches. No "it depends" consulting theater. Just honest pattern recognition from someone who's cleaned up after these disasters.
Who should attend: CTOs and technical leaders tired of watching transformation initiatives turn into expensive complexity. Engineering leaders drowning in tools they didn't choose. Decision-makers who suspect their current approach is performative but don't know how to fix it.
Who should skip this: Anyone looking for AI evangelism or validation that their current strategy is working. This session challenges assumptions—constructively, but directly.
Session Note: Thursday or Friday Please xD
