Culture Eats Bots for Breakfast

When I ask leaders whether they felt ready for AI, most answer with platform names, almost none mentioned culture. To me that’s backwards.

Management consultant and author Peter Drucker once said, "culture eats strategy for breakfast”, and in the AI Era, it will eat your bots and AI transformation efforts as well. 

The real differentiator between organisations set to merely survive and those that are set to thrive in the AI era is organisational readiness and AI leadership, not model specs.

AI needs to be treated as a leadership issue before becoming a technical one. Treat it as a strategic imperative. Empower your people. Foster a culture of learning and experimentation. Break silos. Use data end-to-end. Bake ethics into design.  

In short, leadership is culture-making. The question is how to make that culture. 

Here’s a playbook that braids three strands:

• Mindset and leadership
• AI-readiness and governance 
• Storytelling science  

Used together, these help teams do more than keep up with AI, they build something better.

1. Give Your Teams a “Why”

Without an emotionally resonant North Star, AI programmes stall. Research shows we learn, and change, through stories that strike a personal chord.  

Data speaks to the brain; stories speak to the heart. Kotter, Tichy and Denning all argue the same: leaders must craft a compelling narrative that moves people from the burning platform of today to a tomorrow worth striving for. 

How to do it:

• Identify problems your people care about that AI cna help, like freeing scientists from admin so they can do more bench work.
• Blend personal and organisational stories to unlock trust.
• Frame AI as a sidekick, not the star. If you position AI as a pure productivity tool, you invite resistance. Position it as a growth enabler, and you get engagement.

AI’s real power lies not in automation, but in augmentation – elevating what people can achieve.

Tip: Sketch a three-act story:

1. Today’s struggle
2. The AI-powered horizon
3. The first moves your team of heros could take.

Then tell it, often.

2. Diagnose Readiness Before Prescribing Solutions

If the story answers why; readiness answers whether. In Are You Set to Thrive or Survive?, I broke AI maturity into five pillars: leadership and culture, tech and data, risk appetite, ethics, and commercial value. Leaders often over-index on tech and under-invest in culture and ethics, the exact imbalance consultancies warn against. 

To identify key areas to focus on, try our AI-Readiness and Maturity Diagnostic. 

3. Govern for Trust, Not Just Compliance

Regulators will catch up. Your employees and customers already expect responsibility. In Governing AI Responsibly, I explored how ISO 42001 redefines governance, not as checklists, but as a living system.  

Clause 8’s Plan–Do–Check–Act cycle turns risk management into agile iteration. 

How to do it:

• Embed PDCA loops: Plan (risk assessments) → Do (controls) → Check (audits) → Act (course-correct).
• Set up a cross-functional AI council.
• Track not just accuracy, but user trust and response speed.

Tip: Draft an internal AI code of conduct. If people start quoting it back in meetings, you’ll know culture is shifting.

4. Build a Laboratory, Not a Cathedral

McKinsey data shows test-and-learn cultures scale AI faster. Deloitte calls it the “researcher’s mindset.” Up to 70% of change efforts fail because leaders over-plan and under-test. Storytelling, especially about small wins and smart failures, makes change stick. 

 How to do it:

• Pilot fast, narrate faster. Broadcast what worked, and what didn’t, in story form.
• Use BCG’s 10-20-70 rule: 70% of effort on people and process, 20% on data, 10% on tech.
• Carve out protected “AI lab hours.” No one experiments if their KPIs punish curiosity.

Tip: Ask teams to open sprint reviews with a two-minute hero’s journey. When people tell the story, they own the insight. 

5. Turn Middle Managers into Movement Makers

Executives set tone. Middle managers embed change. Cranfield research shows change only sticks when people “see the role of their actions in the unfolding drama.” Managers are the directors casting people in that drama. 

 How to do it:

• Coach, don’t command. As AI automates grunt work, the manager’s role becomes one of sense-making and capability-building.
• Equip managers with micro-stories, anecdotes that show what good looks like.
• Host peer demo days. Social proof spreads behaviour better than memos.

The STORY Framework

Bring it all together with a simple mnemonic: 
S – Set the stage. Tie AI to a meaningful purpose. 
T – Take stock. Diagnose readiness, honestly. 
O – Organise for trust. Treat governance as agile practice. 
R – Run experiments. Share stories, not just metrics. 
Y – Yield storytellers. Let middle managers carry the narrative. 

Final Thought

AI promises exponential capability. But capability without culture is just unused code. Leaders who master narrative, readiness, and responsible experimentation will turn AI from an existential question into a competitive advantage. 

As Stephen Denning once said: 

“Analysis might excite the mind, but it hardly offers a route to the heart.” 

Lead with both, and your teams won’t just survive, they’ll thrive.