AI · STRATEGY
Know where AI fits in your business before you spend on it
A clear, prioritised plan that tells your board where AI will save time or make money, what it will cost, what the risks are and who owns each part.
Too many ideas, no single plan
In most companies AI arrives piecemeal. Marketing tries one tool, someone in finance tries another, a supplier offers a chatbot, and the board hears about all of it second-hand. Nobody is sure what is being used, what data is going where, or which ideas deserve real budget.
An AI strategy puts that in order. We look at your business area by area, collect the ideas already in circulation, add the ones we see from outside, and score each one for value, effort, risk and readiness. You get a short list of initiatives in a sensible order, each with an owner, an indicative cost and a way of measuring it.
It is written for directors, not engineers: plain English, honest about uncertainty, and specific to your business rather than a summary of what AI might do in general.
What’s included
Current-state review
Interviews with leaders and team members, plus an inventory of the AI tools already in use, officially or otherwise, and the data they touch.
Opportunity scoring
Each candidate use is scored for business value, effort, risk and data readiness, so priorities are argued from evidence, not enthusiasm.
Risk and governance
Data protection, confidentiality, accuracy and supplier risks set out plainly, with a draft AI usage policy and clear ownership.
Roadmap
A sequenced plan of quick wins and longer projects, each with an owner, an indicative budget range and the measure that will show it working.
Board presentation
A concise session with your leadership team to walk through the findings, challenge them and agree the first steps.
AI AT WORK
Where AI does the work
AI DOES
- Summarises interview notes and internal documents so recurring themes and conflicting views are easy to see
- Produces a first inventory of possible use cases for each department, which our consultant then tests against your reality
- Drafts sections of the roadmap and policy from the agreed scoring, for a person to rewrite and approve
YOUR SPECIALIST DECIDES
- Your director interviews your people and makes the judgement calls on what is realistic
- Priorities, budgets and owners are agreed with your leadership team, not set by a model
- Every recommendation in the final document is checked and signed off by a person
How we work
- 01MandateWe agree the scope, the people we will speak to, the questions the strategy must answer and the deadline, in writing.
- 02DiscoveryInterviews, a short staff survey and a review of systems, data and the AI tools already in use.
- 03AssessmentWe score each opportunity and risk, test the promising ones with quick, small experiments where useful, and draft the roadmap.
- 04AgreementWe present to your leadership, take the challenge, and revise until the plan has owners and a first quarter of actions.
HOW WE MEASURE
How we measure it
A strategy is only useful if it is acted on. We define a measure for every initiative in the roadmap and, if you wish, review progress against it at agreed intervals.
- Initiatives started and completed against the roadmap
- Measured time or cost saved by each initiative
- Staff AI usage within the agreed policy
- Data protection or quality incidents linked to AI
Is this right for you?
- Several AI ideas are competing for attention and nobody owns the overall picture
- Your board wants a single, costed plan before approving spend
- You suspect staff are using AI tools you have not approved
- You want an outside view that is independent of any software supplier
An indication, not a quote.
Questions we are asked
What does an AI strategy include?
A review of how AI is used in your business today, a scored list of opportunities, a plain account of the risks, a draft usage policy and a sequenced roadmap. Each initiative in the roadmap has an owner, an indicative budget range and a measure. The work finishes with a session where your leadership challenges the findings and agrees the first actions.
How is this different from AI process optimisation?
Strategy looks across the whole business and decides what to do first. Process optimisation takes one specific process and rebuilds it with AI. Many clients start with a strategy and then use process optimisation, training or chatbots to deliver the top priorities. If you already know exactly which process to fix, you can go straight to that.
Are you tied to any AI software supplier?
No. Polignac is an independent agency, and our recommendations are not linked to commissions from software suppliers. We recommend the tools that suit your data, budget and existing systems, including tools you already pay for. Where several options are reasonable, we set out the trade-offs and let you choose.