10 key AI transformation steps: why storytelling is the real agent of change.

Two words summarise what the AI industry thinks about humans: you’re redundant.

It’s brutal, right?

Let’s put aside fears of AI robots taking over the world and look at what’s really going on. Human nature teaches us we don’t like change, yet history proves we are all remarkably adaptable and resilient.

In my speaking and coaching work, I meet leaders who embody this drama. They’re curious and concerned – able to hold two feelings simultaneously.

It’s quite healthy, for a while. The trouble is we humans can’t tolerate uncertainty for too long. So when we think about the AI-driven workforce, certainty – not fear – is your best friend.

I’ve been writing and speaking about this issue (check out my keynote, Humans Required), and the more I reflect on audience feedback, the more I’m convinced this dynamic underpins the complexity of AI transformation and change management.

Conflicting stories

Part of the problem is we don’t really know where all this is going.

There’s one narrative which says AI transformation is a giant waste of time and money.

An MIT study famously found 95 per cent of organisations recorded no measurable ROI from their generative AI investments, despite around US$30–40 billion invested by enterprises globally.

McKinsey’s most recent report echoes that finding. Just 37 per cent of companies attribute at least some EBIT impact – and that number hasn’t moved in a year.

But get this: 80 per cent of respondents surveyed by McKinsey said AI has made them better at their jobs.

What’s the real story?

It’s a fascinating insight. We’ve not yet fully realised the financial benefits, but individual employees are giving AI the thumbs up.

So what’s going on? In short, we’ve got a human storytelling problem. We’re hoarding our AI insights, lessons and skills in pockets across the workforce. We’re failing to communicate well with our colleagues and, as a result, change is much slower than necessary.

One of the world’s most famous case studies that proves my point is JPMorgan Chase.

More than 200,000 of its roughly 318,000 employees now use an internal AI platform because they got the story, and the storytelling strategy, right.

Up first, management communicated a new vision of “a fully AI-connected enterprise.” With permission and sponsorship from on high, teams were then told any displaced people would be offered new jobs – and total headcount actually rose.

Then came the fun bit. Employees started telling each other stories about their individual efforts. The proof started spreading sideways. JPMorgan kicked off an opt-in program, supported by dashboards showing who was using AI (a FOMO generator), and teams launched other clever initiatives like a ‘prompt-of-the-week’ email to foster curiosity and experimentation.

In short, the story scaled first and the technology followed.

It’s a fascinating example that got me thinking. Surely there must be other examples and research out there documenting how to scale AI success stories throughout an organisation?

Long story short, it turns out there is. I’ve compiled below the top 10 steps experts and real-world users recommend for helping your AI transformation story to spread sideways.

10 keys to spreading your AI story sideways

1. Humans are required. Don’t believe the doom narrative from Silicon Valley. Real social and economic value is created when real humans are actively engaged.
   
2. Expertise and value are trapped in your teams. Don’t launch another pilot – get individual success stories moving throughout the organisation.
   
3. Remember: stories spread sideways. Forget top-down mandates and compulsory learning modules. One curious, engaged team member sharing their success story with another is the heartbeat of change.
   
4. Success stories must be true. Don’t forget that people will fact-check an AI story against cold, hard reality. Are they seeing evidence of that success in everyday work?
   
5. Name the fear story first. Tell the truth about jobs. JPMorgan did, and they got ahead of the story.
   
6. Managers must give teams permission. Researchers followed 25,000 Danish workers – when a direct manager encouraged use of AI, adoption jumped from 47 to 83 per cent. Turns out you don’t need budget approval to communicate one sentence that doubles AI adoption rates.
   
7. Your best people are sitting on a gift. Best practice spreads when someone captures their insights and tells the story well. Here’s one example published by Stanford GSB and MIT researchers: when AI learned what top customer-service agents did and handed those insights to juniors, the less experienced agents improved their performance by 34 per cent.
   
8. Redesign workflows, not apps. Great storytelling between teams won’t change anything unless people adopt new ways of doing work.
   
9. The key to great storytelling is what I call the ‘so-what.’ Always tell people how your insight or newly developed skill delivers value. You’ll lose people if you spend too much time on the backstory.
   
10. Follow this path. Curiosity is the spark, stories are the current and connection is human.

What’s next

My challenge is this: what success stories are you fostering in your organisation?

Have you set up a psychologically safe environment where curious AI learners can turn their spark of progress into stories that connect with others in real, meaningful ways?

The real enemy in this story isn’t AI robots – at least not yet! – but confusion and fear.

Storytelling’s role in this dynamic is therefore not a magical antidote, but a powerful expression of humanity that has a way of destroying harmful myths and inspiring positive change.

Just ask the people over at JPMorgan. Turns out they’re not redundant after all.

Book Mark to speak on storytelling for AI
Mark’s keynote, Humans Required, shows leaders how storytelling is the key to AI transformation success. Let’s chat about your event.