Free framework · 20 minutes
AI Readiness Assessment for UK Small Businesses
Find out if your business is ready to use AI safely, usefully, and without wasting money. Seven pillars, plain English, no jargon.
What it is
An AI readiness assessment is a 20-minute review of whether your business is set up to use AI well. It scores seven areas (strategy, data, skills, workflows, tools, governance, adoption) and tells you the one thing to fix first.
The framework
The seven pillars
Read all seven, or jump to the one most relevant to your business. Each pillar has a short explanation, the assessment questions, and a worked example from a UK small business.
Pillar 1 of 7
Strategy
Do you know what you would use AI for?
A strategy answer is not "we want to use AI for marketing". It is a specific job with a measurable outcome: "we want to reply to overnight enquiries within five minutes during peak season" or "we want to forecast stock for Christmas". The narrower the answer, the better the chance of getting somewhere.
This pillar checks whether you have a defined use case worth pursuing.
Ask yourself
- Can you name three workflows where you have thought about using AI?
- For each, can you describe the current pain in plain English?
- Is there an obvious save-time or save-money measure you would use to know if AI worked?
- Have you tried using ChatGPT or Copilot on any of these workflows yet?
Pillar 2 of 7
Data
Is your business's information findable and clean?
This pillar is not about big data. It is about whether your AI assistant can find the customer record, the order history, the brand guidelines, the standard operating procedures. Could a new hire find your top twenty documents without asking? If not, neither can an AI tool that depends on them.
This pillar checks the readability of the information your business already holds: readable by another human, never mind AI.
Ask yourself
- If a new hire joined Monday, could they find your top twenty documents without asking?
- Is your customer information in one place, or scattered across email, phone notes, and one person's memory?
- Do you have written processes for the things you do most often?
- How much of your business's knowledge would walk out the door if your most senior team member left?
Pillar 3 of 7
Skills
Who on the team can actually use these tools?
Skills here are practical, not theoretical. Can someone open ChatGPT, Claude, or Copilot, write a useful prompt, and get a reliable output? Can they show a colleague how to do the same thing? Your team needs rules, examples, and confidence, not a lecture.
This pillar checks whether AI capability is concentrated in one person (risky) or distributed across the team (durable).
Ask yourself
- Is at least one person on your team comfortable using ChatGPT, Claude, or Copilot for real work?
- If that person left tomorrow, would anyone else know the prompts they use?
- Are you the only person in the business who has tried AI tools so far?
- Has anyone documented the AI prompts that work, so the team can reuse them?
Pillar 4 of 7
Workflows
Which processes are mappable and worth automating?
A mappable workflow has a clear trigger (an enquiry arrives), a sequence of steps (look up history, draft reply, send), and a clear output (a sent email and a tracked record). The job in this pillar is to separate workflows that fit that pattern from workflows that do not.
The principle worth remembering: automate the admin, not the judgement. The packing of a Christmas hamper is a judgement call about gift presentation. The printing of the label is admin. AI should touch the second, not the first.
Ask yourself
- Could you draw the steps of your quoting process on a single page?
- Are there steps you skip when you are tired, or duplicate when you forget?
- Which workflows are automate-the-admin (safe) and which are automate-the-judgement (do not)?
- Where do bottlenecks form when the business gets busy?
Pillar 5 of 7
Tools
Do you have the right software stack?
This pillar is not about expensive enterprise software. It is about whether you have a system of record (CRM), a way to capture work (project tool), a way to communicate (email or chat), and a way to store documents that the rest of the team can find.
This pillar checks whether your foundation is shaped for AI to attach to.
Ask yourself
- Where is your customer information? (One name only.)
- Where is your project or job tracking? (One name only.)
- Are your tools connected, or do you copy-paste between them?
- Have you accumulated three tools that do the same job and never picked a winner?
Pillar 6 of 7
Governance
How will you handle risk, privacy, and AI mistakes?
Governance is not a fifty-page policy document. It is a few clear rules: what AI is allowed to see, what AI is allowed to send, and who reviews AI output before it goes to a client. UK GDPR applies. The ICO publishes specific guidance on AI and data protection for UK organisations.
This pillar checks whether you can use AI safely under UK GDPR and your own client commitments.
Ask yourself
- Do you have a one-page rule for what client data can be put into ChatGPT or Claude?
- Is there a human-reviews-this-before-it-sends step on AI-generated client communication?
- Have you signed any client contracts that mention AI use or restrict it?
- If your AI tool sent something incorrect to a client tomorrow, who would notice, and how quickly?
Pillar 7 of 7
Adoption
Will your team actually use what you build?
Adoption is not training. It is making the AI version the default path: faster, more useful, embedded in the tool your team already opens. For businesses too busy to become AI experts, this matters more than the model choice.
This pillar checks whether you have the operational habit to embed a new step in your working week.
Ask yourself
- When you have added a new tool before, did the team adopt it within a month?
- Is there a person whose job includes making sure we actually use the new thing?
- Are you willing to drop a tool that does not earn its place?
- How will you know within four weeks whether the new AI workflow is being used?
The quick scorer
Take the assessment
The framework above is the slow read. The quiz below is the quick scorer. Twelve questions about your business, two to three minutes, and you get a tier (Not ready, Partially ready, or Ready) plus an estimate of the hours per week AI could save your team.
Want the £-quantified version? Try the 8-minute audit →
How this compares
How this framework compares
Other frameworks reach the same destination by different routes. Microsoft's is deeper on enterprise governance. Cisco's leans on infrastructure (which they sell). TDWI's 75 questions are essential if you have a data team to answer them. Naheed et al.'s academic model carries peer-reviewed credibility. This framework is the shortest and the most directly written for owner-operators who do not have a CTO and do not want a fifty-page PDF.
| Framework | Dimensions | Origin | Cost | Best for |
|---|---|---|---|---|
| You are here This framework | 7 pillars: Strategy, Data, Skills, Workflows, Tools, Governance, Adoption | UK SME consultant, Devon | Free | Owner-operated UK SMEs, 10-100 staff |
| Cloud Adoption Framework for AI | 6 steps: AI Strategy, AI Plan, AI Ready, Govern AI, Manage AI, Secure AI | Microsoft | Free (Azure context) | Enterprises adopting Microsoft and Azure AI |
| Cisco AI Readiness Index | 6 areas: Strategy, Infrastructure, Data, Governance, Talent, Culture | Cisco | Free (registration) | Large IT-led organisations |
| TDWI AI Readiness Assessment | 5 categories, ~75 questions: Organizational, Data, Skills, Operational, Governance Readiness | TDWI (1105 Media) | Free (registration) | Data-mature organisations with analyst teams |
| Multidimensional AI Readiness Model for SMEs | TOEH dimensions: Technology, Organization, Environment, Human | Naheed, Pinto & Pirola (2025), peer-reviewed | Free (academic PDF) | SMEs wanting academic rigour |
What to do next
What you do after the assessment
If you score 0 to 30 · Not ready
Most of your gaps are foundational. Read the field guides linked in the data, skills, and adoption pillars before spending money on AI tools. Save the time you would spend evaluating software, and invest it in fixing one foundation first.
If you score 30 to 60 · Partially ready
You have one or two strong pillars and a few weak ones. Book the AI Opportunity Audit. We will map your specific workflows, quantify the savings in pounds, and tell you whether AI is worth building before you spend a penny on implementation.
If you score 60 to 100 · Ready
Your foundation is set. The audit will focus on workflow prioritisation, not foundation repair. A faster path from assessment to first pilot: usually six to eight weeks rather than three to six months.
Questions about this assessment
The next step
Ready for a paid audit that quantifies the savings?
The AI Opportunity Audit maps your specific workflows, finds the AI savings, and delivers a prioritised roadmap. Yours to keep, even if you never hire me to build.