Free Self-Assessment

AI Readiness Checklist

50 questions across 5 dimensions. Check what's true for your organization. Get your AI readiness score and personalized recommendations - free, no email required.

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1. Data Foundation

AI is only as good as the data it learns from.

We have a clear inventory of all our data sources
Critical business data is clean, accurate, and up-to-date
Data is accessible to the people who need it (not trapped in silos)
We have a single source of truth for key metrics
Data ownership and governance are clearly defined
We comply with relevant data privacy regulations (GDPR, etc.)
Data is automatically integrated across our key systems
We can pull custom reports without depending on one person
Customer/user data is properly structured for analysis
We have a plan to fix our biggest data quality issues

2. Team Skills & Capacity

Best tools fail without trained, willing teams.

Most of our team uses AI tools (ChatGPT, Claude, Copilot) regularly
Our team can write effective prompts to get useful AI output
Our team knows when AI output is wrong or hallucinated
We have at least 1-2 internal AI champions driving adoption
Leadership uses AI tools personally (not just talking about it)
Our team is open to changing workflows for AI
We've invested in formal AI training in the last 12 months
We document and share AI prompts/workflows that work
People feel safe experimenting with AI (no fear of being replaced)
We have a budget allocated for AI training in 2026

3. Tools & Infrastructure

The right tools, not all the tools.

We have an inventory of all AI tools currently in use
We track our total monthly AI spend
AI tools integrate with our CRM/main systems (no copy-paste workflows)
We use enterprise versions of AI tools (data isn't training public models)
We have eliminated duplicate or unused AI tools
Tools are evaluated by ROI, not novelty
Our infrastructure can handle AI integrations without breaking
We have automated workflows that combine multiple AI tools
Security/IT has approved our AI tool stack
We review and refresh our AI tool stack quarterly

4. Strategy & Governance

Without strategy, AI adoption is chaos.

We have a documented AI strategy aligned with business goals
There's a written AI use policy everyone knows about
Confidential data is never pasted into public AI tools
We've considered AI bias and ethics in our use cases
We have clear decision rights: who decides AI vs. human judgment
There's a defined process for proposing/approving new AI tools
We measure AI's actual ROI (not just "we use it")
Leadership reviews AI initiatives quarterly
We comply with industry AI regulations (if applicable)
Customers/users are informed when AI is used in services

5. Use Case Identification

"Adopt AI" is meaningless. Specific use cases matter.

We've mapped our top 10 business pain points
We can name 3+ specific AI use cases delivering value today
Each AI use case has a measurable success metric
We've calculated time savings from current AI use
We have a backlog of AI use cases prioritized by ROI
We sequence implementations (foundation → quick wins → scaled)
We've launched at least 1 AI initiative in the last 6 months
Failed AI experiments are documented as learnings (not buried)
We share AI wins across teams to drive cross-pollination
Our AI roadmap extends at least 6 months ahead
Your AI Readiness Score
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