What a genuine AI strategy looks like — and what separates a useful one from a document that gathers dust.
An AI strategy is not a 50-page document full of diagrams and frameworks. It's a clear, practical answer to four questions: what problems will we solve with AI, in what order, with what resources, and how will we measure success?
The businesses that get the most from AI don't necessarily have the most sophisticated AI strategies — they have clear ones that everyone in the organisation understands and that actually guide decisions.
A clear articulation of the specific business problems AI will address — not generic aspirations ("become more innovative") but specific, measurable problems with a cost you can quantify. "Our quote generation process takes 3 hours per quote and produces errors 15% of the time" is a starting point for a strategy. "We want to be more data-driven" is not.
A ranked list of AI opportunities, with each ranked on business value, implementation feasibility and strategic fit. The first item on that list should be something you'll actually implement in the next 90 days — not a theoretical future state.
An honest view of your current data assets — what you have, what quality it's in, where it lives and what you'd need to do to make it AI-ready. Every AI strategy lives or dies on data.
Who will own AI implementation? What budget is available? Will you build internal capability, partner externally or both? What's the governance structure for AI decisions?
Specific, measurable outcomes for each AI initiative — time saved, error rate reduction, revenue impact, cost reduction. Without these, you can't evaluate whether your AI investments are working.
The test of a good AI strategy is simple: can every person involved in AI implementation read it and immediately understand what you're trying to do, why, and how you'll know if it's working? If yes, it's a good strategy. If not, simplify it.
We deploy commercially available AI products. We don't build bespoke AI, and we don't run standalone training workshops.
A structured planning engagement producing a prioritised 12–24 month roadmap of commercial AI products to adopt, in what order, at what cost, and with what expected outcomes.
Our core service. We select, deploy, configure, and integrate commercially available AI products — Microsoft 365 Copilot, ChatGPT Enterprise, Claude for Business, Gemini, Salesforce and HubSpot AI features — into your existing systems. We do not build custom AI.
Workflow automation using commercial platforms — Zapier, Make, n8n, Power Automate — often with AI steps included. Scoped, built, tested, and handed over with documentation.
A monthly retainer for ongoing support of your deployed AI stack. Delivered predominantly by our own AI assistant with human escalation. From $500/month.
A free, no-obligation discovery call to understand your business, identify where AI can help, and explore what working together might look like.
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