GetAIAudit assesses your business across eight weighted pillars. Each pillar is scored from its underlying signals, then combined into a single 0–100 readiness score and one of five bands. The framework is grounded in recognised standards and peer-reviewed research — including the NIST AI Risk Management Framework, ISO/IEC 42001, the OECD AI Principles, and published AI-readiness studies (see references below).
Select any pillar's signals to read, in plain language, what it measures and what a strong score looks like.
Each pillar explains what we look at and why it counts, so you can see exactly where AI will pay off for your business and where to shore up first.
Data Foundations 20%
How organised, accurate, and reachable your business data is — the fuel everything else runs on.
Every AI tool you’ll ever use is only as good as the data behind it. This pillar looks at where your data lives, how clean and accurate it is, how easily your team can reach it, how far back your records go, and who’s responsible for keeping it right. Get this wrong and even expensive AI hands you confident, unreliable answers; get it right and every tool you add works better. That’s why it carries the most weight.
What good looks like: Data kept in central, consistent systems; records that are accurate and up to date; staff can find what they need quickly; several years of history to learn from; and a named owner accountable for data quality.
Signals we score: data storage, quality & accuracy, accessibility, historical depth, governance & ownership
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Strategy & Leadership 15%
Whether your leaders understand AI and have a real plan and budget behind it.
AI projects succeed or stall based on what happens at the top. This pillar checks whether your leadership genuinely understands what AI can — and can’t — do, whether there’s a written plan rather than vague enthusiasm, whether money has actually been set aside, whether one person is accountable, and how urgently your market is pushing you to act. The businesses that win treat AI as a decision, not an experiment — this shows you how close you are to that.
What good looks like: Leaders who can speak sensibly about AI; a short written strategy with clear goals; a real budget line; a named owner; and a clear-eyed view of competitive pressure.
Signals we score: AI understanding, written strategy, budget allocation, named accountability, competitive urgency
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Workforce & Culture 12%
How ready and willing your people are to work alongside AI.
Tools don’t transform a business — people using them well do. This pillar measures how comfortable your team is with digital tools, how anxious they are about AI, whether staff are already using it unofficially (“shadow AI”), whether you offer any training, and how well departments work together. That hidden AI use is happening in most businesses already — turn it into a managed advantage and adoption flies; ignore it and even the best tool gathers dust.
What good looks like: A digitally confident team; openness rather than fear about AI; sanctioned (not hidden) AI use; some formal training; and departments that share information freely.
Signals we score: digital comfort, AI anxiety, shadow AI use, formal training, cross-functional collaboration
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Process & Workflow 12%
How well-documented and consistent your day-to-day work is.
AI automates processes — so it helps to actually have processes. This pillar looks at whether your standard ways of working are written down, whether everything stalls when one key person is away, whether you know your bottlenecks, how much is already automated, and whether you measure how work performs. Mapping this doesn’t just make you “AI-ready” — it reveals the exact bottlenecks where automation pays back fastest.
What good looks like: Written procedures for core tasks; no single points of failure; known bottlenecks; some existing automation; and basic performance measurement.
Signals we score: SOP coverage, key-person dependency, bottleneck awareness, automation level, process measurement
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Technology & Infrastructure 13%
Whether your existing technology can actually support AI tools.
AI doesn’t run in a vacuum — it plugs into the software and systems you already use. This pillar assesses whether you have the right software, how much you’ve moved to the cloud, whether your systems talk to each other, how solid your cybersecurity is, and your track record of adopting new tech. Modern, connected systems make AI fast and affordable to add; ageing, disconnected ones quietly turn every “simple” project into an expensive one — better to know which you have before you buy.
What good looks like: Good software coverage for core needs; cloud-based systems; tools that integrate; sound security practices; and a history of adopting new technology successfully.
Signals we score: software coverage, cloud adoption, system integration, cybersecurity posture, technology adoption track record
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Use-Case Opportunity 13%
How much realistic, high-value work AI could take on in your business.
Some businesses simply have more for AI to do than others — and most owners are guessing about theirs. This pillar estimates your opportunity: how much repetitive work your team does, how many customer interactions you handle, how document-heavy you are, how much you rely on data to decide, and how widely AI is already used in your industry. A high score here means AI can pay off quickly — and tells you where to start.
What good looks like: Plenty of repetitive tasks to automate; high volumes of customer contact; lots of documents to process; data-driven decision-making; and an industry where AI is already proving its value.
Signals we score: repetitive task volume, customer interaction volume, document intensity, data-driven decisions, industry AI adoption
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Risk, Governance & Compliance 10%
Whether you can use AI safely, fairly, and within the rules.
Using AI responsibly protects you from legal, ethical, and reputational trouble. This pillar checks whether you have a privacy policy, whether you’re aware AI can be biased, whether you can explain how AI-driven decisions are made, whether you vet your vendors, and whether you have a plan for when something goes wrong. It matters most in regulated areas like finance, health, and law — where one unguarded mistake can cost more than years of AI savings. The fix is usually a few sensible guardrails, and this shows you which you’re missing.
What good looks like: A clear privacy policy; awareness of bias and fairness; the ability to explain AI decisions; due diligence on vendors; and an incident-response plan.
Signals we score: privacy policy, bias & fairness awareness, AI explainability, vendor due diligence, incident response
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Resources & Investment Capacity 5%
Whether you have the money, people, and time to actually deliver AI.
A great plan needs fuel. This pillar looks at how much you spend on technology, whether you can call on outside AI expertise, what technical skills you have in-house, whether you assess return on investment before committing, and whether your team has spare capacity for new projects. It’s the lightest-weighted pillar because resources can be added — but knowing your honest starting point stops you committing to a plan your team can’t deliver, and points to the smallest investment that gets you moving.
What good looks like: A realistic technology budget; access to external advisors; some in-house technical skill; a habit of checking ROI before committing; and team bandwidth to implement.
Signals we score: technology spend, external AI advisor access, in-house technical capacity, ROI assessment practice, implementation bandwidth
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A free chatbot gives generic advice based on what you tell it. GetAIAudit applies a structured, weighted framework, benchmarks you against businesses of similar industry and size, injects jurisdiction-specific regulatory context, and calibrates every recommendation to your team's capacity — then hands you a single, prioritised first move.
Framework version: v2.0 — Initial release.
Tool pricing verified: 2026-06-14. Updated quarterly.
Reports are AI-generated and informational only — not professional, legal, financial, or regulatory advice.
The eight dimensions, their weights, and the question bank are grounded in the sources below. All verified against primary materials (access date 2026-06-30). NIST and OECD frameworks are freely available; academic papers are accessible via DOI.