AI Strategy
A documented plan covering which workflows to automate, in what order, on what architecture, with what governance, against which business outcomes, typically across a 12 to 24 month horizon.
How it works
An AI strategy is the difference between a coherent programme of automation and a scatter of point projects that do not compound. The questions an AI strategy answers: which processes are highest-value to automate first, what architecture supports the regulatory context, what governance covers data handling and model behaviour, what operating model holds the work together as it grows, and how value is measured. For UK SMBs and mid-market enterprises, the strategy horizon is typically 12 to 24 months with quarterly review. Ayoob AI builds AI strategy as part of the discovery phase of every engagement, with the strategy document feeding directly into the written scope.
Related terms
AI Retainer Model
A commercial arrangement in which a business keeps an AI engineering team working on its systems on an ongoing basis, for a predictable monthly cost agreed up front, rather than buying one project at a time or paying per seat.
AI Maturity Model
A framework for assessing where a business sits on the spectrum from no-AI to fully-integrated AI capability, used to guide investment, hiring, and strategy decisions.
Build vs Buy AI
The commercial decision between commissioning custom AI software (build) and licensing an off-the-shelf AI product (buy), with the right answer depending on workflow specificity, regulatory constraints, integration depth, and total cost of ownership.
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