Knowledge base
AI strategy
Where AI fits in your business, and where it does not. Readiness, roadmaps, return on investment, vendor choices, and what the EU AI Act means for a small business.
64 articles
Articles in AI strategy
AI and GDPR: data protection impact assessments explained
When an AI project needs a data protection impact assessment, what one contains, and how a small business can produce a useful one.
4 min read
AI and pricing strategy: can you charge for AI features?
Whether customers will pay extra for AI features, what they actually pay for, and how AI changes the pricing of services whose delivery has become faster.
4 min read
AI and your customers: what they expect and what annoys them
What customers of small businesses want from AI in service and communication, what they resent, and how to keep their trust.
4 min read
AI cost forecasting: how usage grows and how to cap it
AI usage grows in steps, not lines. How to forecast a year from a month of logs, the growth patterns to expect, and the caps that make it safe.
3 min read
AI ethics for practical people
The ethical questions that actually come up when a small business uses AI, framed as decisions you have to make rather than principles you have to admire.
4 min read
AI for competitive advantage: realistic for small businesses?
Whether AI can give a small business a lasting edge, and where the advantage actually comes from when it does.
4 min read
AI governance for small businesses: light, but real
Governance sounds like committees. For a small business it is five things written down and one accountable person. What they are.
3 min read
AI maturity model for small businesses
Five stages from scattered personal use to AI running as a managed part of the business, with the signs of each stage and what moves you to the next.
4 min read
AI policies: what your company should write down
An AI policy answers the questions staff actually have. Nine sections that fit on two pages, and the mistakes that get policies ignored.
3 min read
Risk register for AI: the ten risks we discuss with every client
What could go wrong, how likely, how bad, and what you do about it. Ten AI risks that apply to nearly every small business, with a control each.
3 min read
AI security as part of strategy, not an afterthought
The security questions an AI strategy has to answer: what the systems can reach, what untrusted input can make them do, and how a compromise would be noticed.
4 min read
AI strategy checklist: 20 questions before you spend a euro
Twenty questions that turn AI enthusiasm into a plan: what problem, whose data, who owns it, what it costs and what could go wrong.
4 min read
AI strategy for e-commerce
Where AI belongs in a small or mid-sized online store over the next two years, in what order, and which fashionable uses to skip until the basics are earning.
4 min read
AI strategy for education providers
How a school, training provider or course business should approach AI: administration first, teaching support with care, and assessment as the hardest question.
3 min read
AI strategy for healthcare providers
How a clinic or care provider should approach AI: administrative gains first, clinical support within regulation, clinicians in charge.
4 min read
AI strategy for hospitality
Where AI helps a hotel, restaurant or venue: bookings, guest communication, reviews, forecasting and staffing, and where the human welcome must stay human.
4 min read
AI strategy for logistics
Where AI pays in a transport, freight or warehousing business, and what the master data must look like first.
4 min read
AI strategy for manufacturing SMEs
Where AI realistically helps a small manufacturer: quoting, planning, quality, maintenance and documents, and why the shop-floor data usually decides the order.
4 min read
AI strategy for municipalities and public organisations
How a municipality or public body should approach AI: internal gains first, citizen-facing uses under strict conditions, and transparency as the default.
3 min read
AI strategy for non-profits
How a charity should approach AI with limited budget and high accountability, and why beneficiary decisions are never automated.
4 min read
AI strategy for professional services
How a law, accounting or consulting firm should approach AI: where it changes the work, and what it must never touch.
4 min read
AI strategy for real estate developers and property managers
Where AI belongs in development and property management: documents, maintenance, tenant service and portfolio data, and where the regulated edges are.
4 min read
AI strategy glossary: 30 terms in one sentence each
The thirty strategy, governance and investment terms that come up when a business plans its AI work, each explained in one plain sentence.
5 min read
AI strategy workshops: what a good one produces
What should come out of a day spent on AI strategy, who needs to be in the room, and how to tell a useful workshop from an expensive awareness session.
4 min read
Bias in AI systems: how it happens and how to check
Where bias enters an AI system a small business might use, and the practical checks that catch it before it reaches people.
4 min read
Budgeting for AI: one-off, recurring and hidden costs
AI budgets fail because they contain one line. The three columns a real budget needs, and the hidden items that appear in month four.
3 min read
Building AI products versus using AI internally
The difference between using AI to run your business better and selling something with AI in it, and why the second is a different company.
4 min read
Business continuity when an AI vendor changes the rules
Models are retired, prices change, terms are rewritten. What to prepare so a vendor's decision is an afternoon of work, not an outage.
3 min read
Case pattern: a public organisation that started with document search
A composite pattern showing how a public body began its AI work with internal document search, why that was the right first project, and what it enabled.
3 min read
Case pattern: a service business that automated intake
A composite pattern showing how a small service business automates enquiry intake, what it takes, what it returns, and where it nearly went wrong.
4 min read
Case pattern: a shop that used AI for support without losing customers
A composite pattern showing how an online store put AI on first-line support, what it answered, where it handed over, and what changed as a result.
4 min read
Change management: why people resist automation and what to do
Automations fail in adoption more than in code. Five reasons people resist, what each tells you, and how to turn resistance into ownership.
3 min read
Cloud providers and AI: avoiding a dependency you did not choose
How AI features arriving inside the cloud and software platforms you already pay for create dependencies nobody decided on, and how to keep the choice open.
4 min read
Data ownership: who owns what your AI learns from
What happens to your data when it flows through AI tools and vendors, which rights you keep, which you may be giving away in the terms, and how to keep control.
4 min read
Explainability: when you must be able to explain a decision
When a business must explain an AI-influenced decision, what an adequate explanation contains, and how to design for it.
4 min read
From strategy to first project in 30 days
A strategy that does not produce a project in a month becomes a document. The four-week plan: decide, baseline and scope, prove, launch a pilot.
3 min read
Human oversight: designing decision points
Oversight is deciding in advance which decisions a system may take alone and which need a person. Four decision types and how to place them.
3 min read
In-house AI team or external partner?
Hiring for AI is slow and expensive; outsourcing it all leaves no knowledge inside. The honest comparison and what must stay in-house.
3 min read
Legal risks of AI: copyright, liability and contracts
The legal exposures a business takes on when it uses AI: rights in inputs and outputs, responsibility, and the contract terms that allocate both.
4 min read
Measuring AI success: metrics that are not vanity
Usage counts make AI look successful; business metrics tell you whether it is. The four layers of measurement and the vanity traps.
3 min read
Model choice as a strategic decision
Why which AI model you use matters less than how you structure around it, and the few cases where the choice genuinely is strategic.
4 min read
Open-source AI models: what they are and when they make sense
What open-weight models offer a small business, what running one actually involves, and the three situations where they beat calling a commercial provider.
4 min read
Our take: strategy is a list of things you will not do with AI
Why an AI strategy is defined by its exclusions, what a useful list of refusals contains, and how it makes the rest of the decisions easy.
4 min read
Pilots, proofs of concept and production: the three stages
Three words used interchangeably that mean different things, with different budgets, durations and exit questions. What each stage is for.
3 min read
Quarterly AI reviews: what to measure and adjust
One hour a quarter keeps AI owned, measured and honest. The fixed agenda, the scorecard, the decisions, and when to switch a system off.
3 min read
The AI hype cycle: how to read vendor claims
Every AI product is sold in the same superlatives. How to turn claims into checkable statements, and the evidence a serious vendor can show.
3 min read
Responsible AI: what it means when you are not a big tech company
What responsible use of AI means for a small business: the handful of commitments that matter and how to keep them.
4 min read
Talking to your board or investors about AI
What a board actually needs to hear about AI, how to present progress without hype, and the questions to be ready for.
3 min read
Ten AI strategy mistakes worth avoiding
The ten mistakes that appear in small business AI efforts again and again, what each one costs, and the specific correction for each.
4 min read
The EU AI Act: risk categories in plain terms
The four risk levels the AI Act uses, what falls into each, and how to classify your own uses without a legal degree.
4 min read
When to say no to AI
Not every process improves with a model in it. Eight situations where the answer is no, or not yet, and how to say it well.
4 min read
Why AI projects stall after the demo
The demo impressed; months later nothing is in use. The gap between a demo and production, and the five questions nobody asked in the room.
3 min read
AI readiness: data, processes, people
Readiness for AI is not about technology. It is whether your data is reachable, your processes are written down, and your people know the rules.
3 min read
AI strategy in one page: the template we use
The one-page AI strategy we write with clients: six boxes, no vision statement. The template, an example, and how to fill it in one afternoon.
3 min read
Building an AI roadmap for twelve months
A roadmap is a sequence of small projects, each earning the next. How to lay out four quarters and keep the plan honest when the tools change.
3 min read
Choosing AI vendors and partners: the questions to ask
Every vendor demo works. The questions that reveal what happens with your data, what it costs at ten times the volume, and what you keep if you leave.
3 min read
Data quality: the unglamorous work that decides whether AI helps
Every AI project stands on data. Five dimensions of quality, how to measure them in an afternoon, and the fixes that pay off before any model.
3 min read
Do you need an AI strategy? A plain-language test for small and mid-sized businesses
A small business needs a page of decisions, not a strategy document. Seven questions that tell you which one you are, and what the page contains.
3 min read
How to find AI opportunities: follow the repetitive work
Follow the repetitive work. A one-week method to find AI and automation opportunities in your business, rank them, and pick the first one to build.
3 min read
Prioritising AI projects: impact, effort, risk
Ten candidate projects and budget for two. A scoring method on impact, effort and risk that gives an order, a first project, and reasons for the rest to wait.
3 min read
Training your staff for AI: what to teach and what to skip
Most AI training teaches prompts. What a small business needs is judgement: when to use it, how to check it, what never to paste in.
3 min read
What an AI strategy for a small business actually contains
Six decisions, one owner, three projects and a review date. What a small business AI strategy contains, and what belongs in procedures instead.
3 min read
Where AI fits in your business, and where it does not
AI fits where work is frequent, text-heavy and tolerant of a checked draft. It does not fit where a mistake is expensive and rare. A map of your business.
3 min read
Your data is not ready, and that is normal
Every business finds its data messier than expected once AI starts. Why that is the rule, which projects need clean data and which do not, and where to begin.
3 min read