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Don’t Automate Chaos: Why Most AI Transformations Fail
Episode title options
Episode summary (listing copy)
Primary recommendation (sharp + timely):
“Don’t Automate Chaos: Why Most AI Transformations Fail”
Alternatives (more/less provocative):
- “Rocket Boosters on Paper Planes: The AI Implementation Trap”
- “AI Isn’t the Problem—Your System Is”
- “Agentic AI, Real Risk: How to Avoid Scaling Dysfunction”
- “The 80% AI Failure Rate: What Leaders Keep Missing”
- “AI Transformation ≠ IT Project: The Systems Approach”
Episode summary (listing copy)
Companies are spending thousands — even millions — on AI. And then… confusion. Worse outcomes. More complexity. More opacity. Sometimes, real reputational or legal blowback.
In this episode of How to Build a Growth System, Colin and Chris unpack why so many AI rollouts are failing to deliver measurable value — and why the “race to AI” is pushing organisations into a dangerous pattern: automating broken systems.
Drawing on widely reported failure rates (including claims that ~80% of organisations see no measurable positive impact), they argue the core issue isn’t the model, the vendor, or whether GenAI “works.” It’s that leaders are treating AI like just another tool rollout, when it’s actually a business transformation problem.
The conversation explores:
- Why AI often becomes “a rocket booster on a paper aeroplane”
- How agentic AI can amplify risk when goals, rules, and context are unclear
- Real-world cautionary tales (including public failures like AI drive-thru ordering and misguided regulatory chatbots)
- The systemic causes behind bad outcomes: broken processes, contradictory information environments, weak governance, and unclear ownership
- Why “move fast and break things” becomes far more dangerous with autonomous systems
- The missing ingredient: systems education at the executive level
And crucially, they outline what to do instead: treat AI as a transformation programme, understand and redesign the underlying system first, and only then layer intelligent automation on top — with governance that enables speed through clarity, not just legal risk mitigation.
The takeaway is simple: AI can be a force multiplier — but only for organisations with foundations solid enough to multiply what works, not what’s broken.
View all episodes
By rev.spaceEpisode title options
Episode summary (listing copy)
Primary recommendation (sharp + timely):
“Don’t Automate Chaos: Why Most AI Transformations Fail”
Alternatives (more/less provocative):
- “Rocket Boosters on Paper Planes: The AI Implementation Trap”
- “AI Isn’t the Problem—Your System Is”
- “Agentic AI, Real Risk: How to Avoid Scaling Dysfunction”
- “The 80% AI Failure Rate: What Leaders Keep Missing”
- “AI Transformation ≠ IT Project: The Systems Approach”
Episode summary (listing copy)
Companies are spending thousands — even millions — on AI. And then… confusion. Worse outcomes. More complexity. More opacity. Sometimes, real reputational or legal blowback.
In this episode of How to Build a Growth System, Colin and Chris unpack why so many AI rollouts are failing to deliver measurable value — and why the “race to AI” is pushing organisations into a dangerous pattern: automating broken systems.
Drawing on widely reported failure rates (including claims that ~80% of organisations see no measurable positive impact), they argue the core issue isn’t the model, the vendor, or whether GenAI “works.” It’s that leaders are treating AI like just another tool rollout, when it’s actually a business transformation problem.
The conversation explores:
- Why AI often becomes “a rocket booster on a paper aeroplane”
- How agentic AI can amplify risk when goals, rules, and context are unclear
- Real-world cautionary tales (including public failures like AI drive-thru ordering and misguided regulatory chatbots)
- The systemic causes behind bad outcomes: broken processes, contradictory information environments, weak governance, and unclear ownership
- Why “move fast and break things” becomes far more dangerous with autonomous systems
- The missing ingredient: systems education at the executive level
And crucially, they outline what to do instead: treat AI as a transformation programme, understand and redesign the underlying system first, and only then layer intelligent automation on top — with governance that enables speed through clarity, not just legal risk mitigation.
The takeaway is simple: AI can be a force multiplier — but only for organisations with foundations solid enough to multiply what works, not what’s broken.