The 35-step AI adoption strategy for CEOs who don't want regrets

AI's gone from experimental to existential since I published my last guide - so start here (now)

I still believe there are only two types of companies: those that go AI-first (now), and those that will go bust.

Things have moved fast since I published my 25-step AI adoption guide (already helped over 1,000 CEOs get their head around AI) in February 2025. Since then, AI has shifted from experimental to existential (for businesses at least) - and that’s forced a complete rethink of how every company should approach it.

This updated 35-step strategy (watch the YouTube version) is the clearest, most practical place for any CEO to start - or recalibrate - right now.

AI Starts at the top

1. The CEO must be ready to lead

   If the CEO is delegating the AI strategy to anyone else in the organisation, they’ve fundamentally misunderstood what’s going on here. If the business is simply adding AI to its list of things to deal with, it’s already on its way to irrelevance. AI will rewrite the entire list - which is why it needs to be the CEO’s top priority, and it needs to be visibly so. (If your CEO needs help getting this, you can book me for 1:1 coaching - I bring a mix of psychology, CEO+board experience and AI expertise).

2. The board must be ready to rally
   AI will touch every business function and move every metric - revenue, risk, productivity, customer experience. This is not an IT initiative. It’s a business-critical transformation that needs to happen at speed and probably repeatedly. The board needs to understand that - and rally behind the AI strategy. If your board still sees AI as a tech trend, a future consideration or a single item on the board meeting agenda, you’ve got a serious alignment problem.

3. Assess the board’s AI competence. And restructure if necessary
   You can’t govern what you don’t understand. In February (when I published my first AI strategy guide), I wrote that at least one board member must be able to challenge, probe, and shape the AI strategy with real insight. I no longer believe that. Every board member now needs those skills.

   If they don’t have them (or aren’t able to acquire them fast) the board must be restructured. That’s challenging, and it falls to the chairman to make this move. But ignoring this puts the board at risk of breaching its fiduciary duty.

   Board members who can’t meaningfully participate in AI discussions, who don’t have the depth of knowledge to challenge assumptions, or who are overly impressed by what AI appears to do - those individuals create material risk. For the business. And for the board.

4. Ethics must be understood and owned
   The CEO, the board, and the leadership team all need a working understanding of AI ethics. That includes transparency, data use and management, explainability, change management - what’s fair, what’s legal, and what’s just smart business.

   Someone should be formally accountable for AI ethics inside the organisation. But everyone at the top needs to be ethics-literate enough to spot when something’s off and know when to raise a red flag - or pull the brake entirely.

   This isn’t a side conversation. It’s central to trust, risk, and long-term resilience - and it’s moved to near the top of my list.

Benchmark where you are now

5. Audit shadow AI use
   Your team is obviously already using AI - whether they tell you or not. You need to find out what tools are being used, how they're being used, and what risks that presents. This should be done anonymously and thoroughly, because shadow AI can reveal both opportunity and vulnerability.

6. Gauge AI literacy - and do it regularly
   You can’t upskill your team without knowing where their skills currently stand. You need to survey and test your people to understand who’s using AI, how they’re using it, where the confidence gaps are, and how that’s changing over time. Pay close attention to overconfidence - it’s more dangerous than ignorance.

7. Map your team’s emotional response
   Where are people excited about AI? Where are they fearful? You need to understand the emotional landscape across the business - because it’s directly impacting AI adoption and everything else. Who will need reassurance? Who will need to be reined in? Coaching and support can then be targeted rather than generic. (I offer coaching to help people manage their emotions through the AI maze - you can contact me here).

8. Audit your tech stack
   This should be a regular exercise, led by leadership in collaboration with IT. Review every tool the business is paying for. What are their AI capabilities? Are they still fit for purpose? Are there overlaps? What’s missing? You don’t want to just layer new tools on top. Evaluate, consolidate, and design a stack that makes sense for what you’re building.

9. Audit your data
   This is absolutely critical to the success of your AI strategy. What data do you have? Where is it stored? How clean is it? How accessible? What’s genuinely proprietary and valuable? You can’t do anything strategic with AI if your data is disorganised, duplicated, or stuck in systems no one can access.

10. Audit your skills
    AI literacy is just one skillset - but AI is changing the game entirely. What unique skills, capabilities, and knowledge does your business hold that competitors don’t? Where is your advantage? Who are the people that think differently? Pay particular attention to creativity, empathy, critical thinking, and curiosity - these are your AI-resilience skills, and they need investment. But you also need to take a hard look at the skills you’re currently paying for that you might not need in future. Then decide what to do about that.

11. Audit your tasks
    What actually gets done in your business every day? List it. Break it down. Then categorise every task by how easily it could be automated, sped up or improved with AI. This will reveal where the real opportunities are, where your human advantage lies, where you’re wasting resource and where to focus next.

12. Audit your change readiness
    Where are you rigid? What’s stopping your business from being more nimble? Do this audit honestly. You can’t lead through a transformation if the organisation’s default mode is caution, delay, or fear of disruption.

Build your tech stack

13. Start with your ideal-state list
    If money and resources weren’t constraints, what would your tech stack look like? Which tools would you deploy? Who would use them? What would the benefit be? Starting here gives you a benchmark for what’s possible - and makes the next step easier (and more likely to be effective).

14. Refine and select your tools
    Now that you’ve mapped out the ideal, get practical. What’s realistic based on your priorities, budget, and internal capabilities? What tools will deliver the most value today without creating long-term chaos? Select what makes sense - but don’t let short-termism drive every decision (I’ll be running a session on tool selection for AI Edit members in October - find out more about membership options).

15. Implement and integrate
    Once you’ve selected your tools, get them up and running - properly. That means implementation support, onboarding, internal training, and integration with your current systems. This isn’t about dumping new software on your team.it’s about making the stack usable, sustainable, and scalable.

Define your position on AI

16. Outline your strategic positioning
    You don’t want to be the company that just reacts to whatever AI throws at it. You want to be the company that makes a deliberate decision about how it’s going to handle this shift. That might mean taking a bold AI-first approach, like Shopify or Fiverr. It might mean going human-first and using AI to support your team. It might mean moving cautiously and watching the market.

    Whatever your stance, it needs to be clear and it needs to be agreed at the top. The board and CEO should own this decision together. Because once it’s made, it has to be communicated consistently. Your customers, your employees, your suppliers, your investors - they’ll all want to know where you stand.

17. Communicate your position
    Once your AI position is clear, you need to talk about it. Loudly and consistently. Internally, your team needs to understand what it means for their roles, the business, and what’s expected of them. Externally, your customers, partners, and stakeholders will all be watching - and making decisions based on what they hear.

    If you don’t tell your story, someone else will fill in the gaps. Make sure your position is understood, and make sure it reflects what you’re actually doing.

Hone your change management strategy

18. Be clear on what this means for your team
    Once you’ve set your position on AI, share it with your people. They need to know what changes as a result and how quickly. Your job is to remove ambiguity and make sure the message lands across every level of the business.

19. Define and embed your AI policy
    Set clear guidelines: what’s allowed, what’s not, and what’s actively encouraged. Don’t leave it vague. Educate people repeatedly, through multiple channels, so there’s no confusion. Your AI policy isn’t just compliance - it’s a signal of intent.

20. Get training
    If you’re serious about AI adoption, you need a structured training programme. Ongoing, role-specific, and practical. People need to know how to use the tools and how AI will change the way their role works.

21. Offer coaching and mentoring
    Training alone isn’t enough. People need space to ask questions, try things, and get support. Some will fly. Others will freeze. Coaching is how you help them fly higher and close that gap. (if you’d like to speak to me about coaching, contact me via my the AI Edit website).

22. Update your prompt library (or build one if you haven’t got one)
    Encourage your team to document and share effective prompts. Make the best ones easy to find and improve. This builds institutional knowledge fast - and helps avoid people reinventing the wheel in isolation. I still recommend this, even as the art of prompting is becoming less relevant (as models become better at interpreting your instructions). It’s incredible basic training on how to engage with AI - a skill everyone will need.

23. Showcase internal use cases
    Give your teams visibility into how AI is being used successfully inside the business. Real examples beat abstract potential. Share what worked, what didn’t, and what others can try.

24. Anticipate and remove hurdles
    Adoption will stall if you don’t address the blockers. Tools that don’t work, policies that are unclear, people who are resistant - these all need to be surfaced and handled. The faster you fix small things, the faster you build momentum. Keep your eyes open and be ready to jump in.

25. Hold people accountable
    This isn’t optional. Track who’s engaging and who’s not. If someone consistently disengages, it’s up to leadership to check in. Not to punish, but to understand why, and whether they’re still a fit for the direction you’re going (that’s a scary thought I know but you need to think it).

26. Keep feedback loops alive
    Make it easy for people to share what’s working and what’s not. Feed that insight back into your strategy. Use 1:1s, team meetings, AI suggestion boxes - whatever gives you signal. Don’t assume silence means success.

27. Make AI part of your operating rhythm
    Weekly leadership updates, monthly team check-ins, regular reporting cycles - AI can’t be a side project. Bake it into how you run the business. That’s how you sustain focus and build capability over time.

Move from adoption to strategy ($$$)

Steps 1-27 are foundational. But they’re just the start. Once you’ve embedded AI into the business, now it’s time to zoom out.

28. Create a culture of experimentation - and celebrate failure
    Innovation doesn’t come from playing it safe. You need to build a culture where teams are encouraged to test ideas, break things (safely), and learn quickly. That means setting boundaries, yes. But also celebrating well-reasoned failures. The companies that get this right will move faster than everyone else.

29. Insist that department heads pioneer AI strategy
    Your department leads need to take ownership. They should be speaking to clients, reviewing competitors, mapping internal use cases, and identifying opportunities. Then they should be expected to pitch ideas - clearly and regularly - to leadership.

30. Build a strategic AI team
    You need a group that pulls all the threads together: department input, customer insights, competitive intelligence, product direction, emerging tech. This team should be made up of digitally literate, business-smart people who are curious, strategic, and well-connected internally. Their job is to help shape the overall AI direction and report directly to the board.

31. Do a deep dive into what your data can unlock 🧈
    You’ve already audited your data. Now go further. What can you build with it? Internal tools? Customer-facing products? Proprietary models? This is the foundation of your future competitive advantage - don’t outsource the thinking.

32. Separate internal and external AI strategies
    You need two tracks: one for how AI improves your internal operations, and one for how it changes what you sell, build, or offer externally. Treat them differently - they move at different speeds and require different skills and investments.

33. Get much closer to your customers
    Trust is going to be the currency that matters most in the AI era. If you don’t already have a strategy for deepening customer loyalty and visibility, you need one now. This will shape your reputation, your ability to sell, and your company’s valuation. Assign clear ownership.

34. Build your profile and authority
    You need to become a recognised expert in your space. You need to be building credibility as a thought leader in your domain. As AI levels the playing field in execution, your perspective, experience, insight, and influence become real differentiators.

35. Create a rhythm for strategic work
    Set a regular cadence for hackathons, strategy sprints, working sessions - whatever suits your culture. This keeps momentum going and gives space for new ideas to emerge. Don’t leave strategy to chance or squeeze it into spare time.

    Good luck CEO - you can do this. And if you do, you’ll thank me in 12 months. And if you want me in your corner while you put this into practice, then contact me via my website to discuss my AI coaching.