How to Build an AI Strategy Without a Chief AI Officer
Most businesses cannot afford a Chief AI Officer and do not need one. They need a practical AI strategy that a founder or operations lead can develop and execute — without a dedicated AI function, without a research team, and without an enterprise budget. This is that strategy.
The Right Scope
An AI strategy for a 5 to 50 person business is not a comprehensive digital transformation roadmap with 47 workstreams and a 3-year implementation plan. It is a clear answer to five practical questions: what business problems are we trying to solve, which of those problems are best addressed by AI, which AI tools and platforms will we use, who owns the implementation and ongoing management, and how will we know if it is working?
The document that answers these five questions is your AI strategy. It fits on 2 to 3 pages. It has a 90-day action plan attached. It is reviewed quarterly and updated based on what has been learned. A strategy you can execute is worth infinitely more than a comprehensive strategy that exists only in a presentation.
The One-Day Workshop
Morning: Problem inventory and prioritisation (3 hours)
Gather the leadership team or your key operational stakeholders for a focused morning session. Activity 1: Problem inventory (60 minutes) — each person lists every operational pain point in their function. No filtering at this stage — volume first. Activity 2: AI suitability filter (45 minutes) — for each pain point, assess: is this problem primarily about processing volume, consistency, or speed? (AI-suitable) Or is it primarily about judgment, relationship, or creativity? (AI less suitable). Activity 3: ROI ranking (45 minutes) — for the AI-suitable problems, rank by the combination of time currently consumed and the expected improvement from AI. The top 5 problems are your AI strategy targets.
Late morning: Platform and tool selection (90 minutes)
For each of the top 5 target problems, identify the right platform: is this an automation problem (Make.com), a CRM or sales problem (GoHighLevel + Make.com), a custom application problem (Bubble.io), or a content and analysis problem (Claude API directly)? For each target problem and platform selection: estimate the build cost (reference the cost guides from Post 323 and Post 305), the implementation timeline, and the expected monthly ROI. This becomes the AI strategy investment plan — the specific projects, their costs, their timelines, and their expected returns.
Afternoon: Ownership assignment and 90-day plan (2 hours)
For each of the 5 selected AI implementations: assign an owner (the person accountable for the implementation — not the person who will do every task, but the person who is responsible for it being done), define the success criteria (specific and measurable — what metric will you check at 60 days?), and establish the first action (what is the specific thing that happens in the next 7 days to begin this implementation?). The 90-day plan: implementation 1 begins in weeks 1 to 4, implementation 2 begins in weeks 3 to 8, implementation 3 begins in weeks 7 to 12. Each implementation is staggered to prevent the team from building too many things simultaneously.
Review cadence: Monthly check-in, quarterly strategy update
The AI strategy is a living document. Monthly: a 30-minute check-in on active implementations — are they on schedule, are the early indicators positive, what needs adjustment? Quarterly: a 2-hour strategy review — did the completed implementations deliver their expected ROI, what did we learn, what are the next 5 implementations based on the updated problem inventory? The quarterly strategy review is where the AI programme compounds — each cycle of implementation and learning improves the quality of the next cycle’s selection.
📌 The most important element of an AI strategy for a small business is not the strategy document — it is the first implementation. The strategy gives you direction; the first implementation gives you momentum. A business with a clear first implementation running within 30 days of the strategy session will develop faster AI capability than a business with a perfect strategy document that takes 6 months to produce and 3 months to begin acting on. Bias heavily toward implementation speed over strategy perfection.
How is an AI strategy different from a digital transformation strategy?
Digital transformation is the broader programme of adopting digital tools and processes across the business. AI strategy is the specific subset that concerns AI-powered capabilities. The two overlap but are distinct: a digital transformation strategy might include implementing a CRM, moving to cloud storage, and building a website — none of which are AI. An AI strategy is specifically about the applications of language AI, machine learning, and automation that require AI capabilities. For most small businesses: start with the AI strategy (faster, more focused, more measurable) before broadening to a full digital transformation programme.
What if I discover during the strategy process that AI is not the right solution for our top problems?
This is a valuable outcome, not a failure. If the top operational problems are primarily about processes that are poorly defined (fix the process before automating it — Post 283 principle), or relationships that require genuine human investment (AI cannot substitute), or data quality issues (clean the data before building AI on top of it), then the right strategy may be to address those foundational issues before investing in AI implementation. The strategy process produces clarity; sometimes clarity reveals that the highest-ROI investment is not AI.
Want Your AI Strategy Built and Executed?
SA Solutions facilitates AI strategy sessions for growing businesses and executes the implementation plan — from strategy workshop through first implementation to quarterly reviews.
