The 25-step AI adoption strategy that every CEO wishes they had started last year

There are two types of companies: those that embrace AI now, and those that will be irrelevant within two years.

We all want to be the former, but most businesses don’t know how. In the past week alone, I’ve spoken to three CEOs who were asking where to start on AI implementation. The urgency around building a structured AI strategy is ramping up, but few leaders have a clear path forward.

If you’re only starting to think about this now—it’s not too late, but it will be soon. The best time to launch your AI strategy was a year ago. The second best time is today. Here’s how you do it in 25 detailed steps.

1. AI starts at the top.

The CEO must make AI a top priority. She needs to be the figurehead, relentlessly driving the message. If AI doesn’t have executive sponsorship, everything else will underperform. The CEO should not only talk about AI but also integrate it into strategic plans and measure progress regularly.

2. The board must buy in.

AI will influence every business metric, from revenue and costs to risk and customer satisfaction. If your board isn’t already pushing for AI adoption, you have a knowledge gap that needs urgent addressing.

3. Assess the board’s AI competence.

Boards dominated by industry veterans who lack AI expertise will struggle to provide sufficient oversight. You need at least one non-executive director or advisor who understands AI’s impact on strategy, operations, and risk. Board members carry fiduciary responsibility—which means ignorance is no excuse. If your board hasn’t raised questions about AI yet, that’s a sign they need education or new members.

4. Understand your AI tech stack.

Work with your IT and internal comms teams to audit which AI tools employees are already using and which they want access to. This should ideally be done anonymously to get honest responses. Employees may already be using AI tools to automate parts of their workflow without leadership knowing and they might be uncomfortable sharing this.

5. Provide secure access to AI tools.

Your team will use AI whether you control it or not. Provide secure access through approved platforms. Most major AI providers offer corporate tools that ensure compliance with data security policies, or you could build your own access where you own the data.

6. Run an AI literacy survey.

Assess AI adoption levels across your workforce. Identify who’s already using AI, their confidence levels, and where training is needed. Understanding the current AI competency across the company will shape your training strategy.

7. Define AI usage policies.

Set clear guidelines on what’s allowed, what’s not, and why. Keep it simple and communicate it repeatedly through multiple channels. Employees need to know which AI tools are permitted, how data security is maintained, and what ethical considerations apply.

8. Prioritise AI training.

Book training sessions monthly for the next 12 months. Consider online courses, in-house experts, and external providers. Ensure employees understand how to integrate AI into their daily tasks and workflows.

9. Build your AI team strategically.

Include influential people from all departments, not just tech. AI transformation is about leadership, governance, customer service, marketing, and finance—not just IT.

10. Launch an AI suggestion box.

Anonymously collect feedback on concerns, ideas, and training needs. Employees who use AI daily often have the best insights into practical applications and risks. And you just never know where the best ideas might come from.

11. Task department heads with AI exploration.

Each department must identify the following and report to the CEO:

• Current AI usage.

• Efficiency gains AI could unlock.

• New creative possibilities.

• Barriers to AI adoption.

• What they need from leadership.

• Potential changes to their KPIs due to AI use.

12. Hold cross-department AI workshops.

Department heads must present their findings to the board. Boards must be sufficiently AI-literate to challenge suggestions - a board lacking deep AI expertise will be impressed by any AI strategy (because AI is impressive). They cannot execute their fiduciary duty if they cannot think critically about what is proposed.

13. Structure AI team meetings weekly.

Agenda:

• Review suggestion box feedback.

• Share AI learnings.

• Identify quick wins.

• Evaluate long-term strategies.

• Prioritise actions.

14. Monthly AI reports to the CEO.

The AI team must provide updates on actions taken, proposed next steps, and report on any blockers. These reports should focus on measurable impact and highlight both risks and opportunities.

15. Biweekly company-wide AI updates.

Senior leaders must visibly engage. Sessions should include:

• AI team updates.

• A use case presentation.

• Open discussion on learnings and challenges.

16. Hold employees accountable.

If someone skips two AI updates in a row, the CEO should personally check in. Engagement is non-negotiable and the CEO is the best person to signal this.

17. Create a prompt library.

Document effective AI prompts and make them easily searchable. Encourage feedback and iteration. Employees should be able to learn from each other’s prompts.

18. Monthly AI case study presentations.

A different team member should showcase a successful AI implementation each month. The purpose is to inspire so ideas should come from any industry.

19. Develop an AI knowledge base.

Either a structured database (RAG Fusion model) or a Custom GPT chatbot where employees can get AI strategy answers. This can serve as a case study for building these types of models and employees should be encouraged to experiment with them in other domains.

20. CEO-led AI communications.

A weekly AI email from the CEO on wins and priorities keeps AI front-of-mind. Employees need to see AI as a central pillar of the company’s direction.

21. Open AI discussions on internal platforms.

Slack, Teams, or other comms tools should have dedicated AI discussion channels where employees can share insights and ask questions.

22. Ethics must be a core consideration.

Hold regular ethical roundtables on AI. Boards must actively engage with ethical risks, not treat them as an afterthought. AI policies must evolve to address issues like bias, privacy, and transparency.

23. Line managers must collect AI feedback.

Ensure AI adoption is discussed in 1-2-1s and fed back to leadership. AI strategy is a continuous process, and line managers need to be at the forefront of feedback loops.

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Beyond the basics: next-level AI strategy

Once the fundamentals are in place, it’s time to think bigger.

24. Run AI hackathons.

Give employees a structured environment to experiment with AI solutions. Provide guidance, resources, and clear objectives.

25. Encourage experimentation and reward failure.

Create an internal award for ‘best AI flop’—celebrating bold attempts fosters a culture of innovation. Fear of failure stifles creativity, but celebrating learning from failures encourages breakthroughs.

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AI represents a fundamental shift in how businesses operate. Companies that embrace AI methodically and proactively will lead. Those that don’t will be left behind.

The question is: which type of company will you be?