Featured Guide · AI Readiness
AI readiness checklist for small business (2026)
A 29-item checklist across 10 categories — clarity, data, tools, workflows, security, website, people, measurement, budget, and next step — with a simple scoring rubric so you can see if your small business is actually ready to adopt AI, or if you need to shore up the basics first.
How to use it
- Read each item and mark it done or not done — no half credit.
- Add up the checked items across all 10 sections.
- Score: 0–10 = not ready, fix the basics first · 11–20 = pilot-ready, pick one workflow · 21+ = ready to scale AI across the business.
01 · Business clarity
You know what you're trying to fix
AI amplifies the process you already have. Fuzzy goals produce fuzzy pilots that never graduate.
☐ Named the top 3 tasks that eat the most hours per week.
Why it matters: Every good AI pilot maps to a specific, painful task — not 'use AI more'.
☐ Written a one-sentence outcome for each: 'save X hours' or 'add $Y revenue'.
Why it matters: Without a target, you can't tell a working pilot from a fun demo.
☐ Owner-level buy-in on which task to attack first.
Why it matters: Small teams can only run one AI pilot at a time without stalling.
02 · Data
Your data is reachable, not perfect
You don't need a data warehouse. You need the answers, invoices, notes, and transcripts to live somewhere an AI tool can read.
☐ Customer records live in one CRM (not just email + memory).
Why it matters: AI copilots need a canonical customer list to enrich or draft against.
☐ Past proposals, SOPs, and FAQs are in shared docs (Notion, Drive, Docs).
Why it matters: This is the corpus your custom GPT or RAG bot will actually use.
☐ Call recordings or transcripts exist for sales and support.
Why it matters: Meeting AI (Fathom, Granola, Fireflies) turns calls into training data.
03 · Tools & accounts
You have the accounts you need — and no more
Most small teams don't need more AI subscriptions. They need one paid seat per operator and a plan to consolidate.
☐ At least one paid ChatGPT / Claude / Gemini seat per operator.
Why it matters: Free tiers throttle context and file uploads — the two things that matter.
☐ An automation tool set up (Zapier, Make, or n8n).
Why it matters: AI without automation stays a chat window. Automation is how it hits your CRM.
☐ Audited existing SaaS for AI features you already pay for.
Why it matters: HubSpot, Notion, Gmail, and Canva ship AI you might be double-paying to replicate.
04 · Workflows
You've mapped one process end-to-end
Pick one workflow — lead intake, proposal, onboarding — and diagram every step before you introduce AI.
☐ Diagrammed the current workflow with owners and hand-offs.
Why it matters: AI is only useful at specific steps; a fuzzy map hides where to insert it.
☐ Marked which steps are rules-based vs judgement-based.
Why it matters: Rules-based = automate. Judgement = draft-then-edit. Different tools.
☐ Chosen 1–2 steps as the pilot — not the whole workflow.
Why it matters: Automating one step in week one beats automating none in month six.
05 · Security & privacy
You know what you can and can't paste into an LLM
AI adoption stalls the fastest on a security review. Get ahead of it with clear rules and a paid tier that doesn't train on you.
☐ Using a paid business tier that excludes your data from training.
Why it matters: ChatGPT Team, Claude for Work, and Gemini Business all offer this — free tiers don't.
☐ Written rules for what data types are OK to paste (and what isn't).
Why it matters: Staff need a one-pager, not tribal knowledge, before you scale usage.
☐ Reviewed vendor DPAs / subprocessors if you handle PHI, PII, or regulated data.
Why it matters: HIPAA, GLBA, and California CCPA all constrain which AI vendors you can use.
06 · Website & content
Your site is legible to AI crawlers
ChatGPT, Perplexity, and Claude increasingly cite websites in answers. If your site is a JS shell with thin copy, you don't get cited.
☐ Every important page renders real HTML (not just a client-side shell).
Why it matters: AI crawlers read HTML the way Google used to — no HTML, no citation.
☐ A public `/llms.txt` or clear content map exists.
Why it matters: Gives AI crawlers a curated list of the pages you actually want them to read.
☐ Long-form service and industry pages exist — not just a homepage.
Why it matters: Answer-engine citations reward pages that answer one specific question well.
07 · People & skills
One person owns AI on the team
You don't need a Head of AI. You need one accountable operator with 2–4 hours a week.
☐ One named owner for AI experiments (with time carved out).
Why it matters: AI projects without a single throat to choke drift and die.
☐ Team has done at least one hands-on prompt-writing session.
Why it matters: Prompting is a skill; two hours of practice beats a year of reading tips.
☐ Comfortable saying 'the AI wrote a draft, I edited it' to clients.
Why it matters: AI adoption stalls when staff feel they have to hide it.
08 · Measurement
You'll know if the pilot worked
If you can't measure the pilot, you can't defend the spend or scale what works.
☐ Baseline metric captured before the pilot starts.
Why it matters: Hours per week, response time, or close rate — pick one and write it down.
☐ A weekly 15-minute review scheduled for the first 6 weeks.
Why it matters: Short, frequent checkpoints catch drift before it becomes a wasted quarter.
☐ A kill criteria decided in advance ('if X hasn't improved by week 4, we stop').
Why it matters: Pre-committing to stop prevents sunk-cost pilots that limp for months.
09 · Budget
You've sized the real cost, not just the sticker
Software is the smallest line item. Setup time and change management usually cost more than the seats.
☐ Budgeted setup time in hours, not just SaaS dollars.
Why it matters: Most AI pilots need 10–40 hours of process + prompt work up front.
☐ Set a 90-day spend ceiling and reviewed it with the owner.
Why it matters: AI tools are cheap individually, expensive in aggregate — cap it early.
☐ Comfortable with a 3–6 month payback window, not 30 days.
Why it matters: Well-scoped pilots pay back in a quarter or two — not instantly.
10 · Next step
You have a first pilot picked
The whole checklist collapses to this: is there one concrete thing you'll try in the next 30 days?
☐ One pilot task, one owner, one deadline in the next 30 days.
Why it matters: Momentum matters more than perfection. Start small, ship, then expand.
☐ Booked a review at day 30 to score it against the baseline.
Why it matters: A scheduled review is the difference between a pilot and a hobby.
FAQ
What does 'AI readiness' actually mean for a small business?
AI readiness is a short, honest check that the basics are in place — clear goals, reachable data, paid tools, one owner, a security stance, and a way to measure — so that an AI pilot can actually stick instead of dying as a fun demo.
Do I need a data warehouse or IT team before adopting AI?
No. Small businesses succeed with AI when their customer list is in a CRM, past proposals and SOPs live in shared docs, and call recordings are captured. You don't need a warehouse — you need the data to be reachable.
How do I score this checklist?
There are 29 items across 10 categories. Count each checked item. 0–10 = not ready, start with data and clarity. 11–20 = pilot-ready, pick one workflow. 21+ = ready to scale AI across the business.
What's the fastest first AI pilot for a small business?
Lead triage or meeting recaps. Both use tools you likely already have (ChatGPT + Zapier or Fathom), pay back within weeks, and don't touch client-facing deliverables — so the risk of going wrong is low.
Want us to score your business?
Free 15-minute intake. We'll walk this checklist with you, score it live, and hand you a one-page AI-readiness plan with the first pilot to run.
Book the free intake →