# AI Readiness Checklist
Practical AI readiness checklist aligned to the Data Maturity Pyramid and enterprise diagnostic dimensions. Printable checklist, free with a quick email.
# AI Readiness Checklist

     Rodan · Maturity pyramid + enterprise dimensions · guides.rodan.io

   Rodan · Resources · Maturity

# AI Readiness Checklist

   Practical checks before you buy copilots, agents or predictive models. Foundations first: you cannot skip a level on the pyramid.

## What is inside

- Pyramid-level gates from collection through AI-driven insights

- Enterprise dimensions: quality, governance, infrastructure, analytics, AI readiness, commercial alignment

- Go / no-go prompts for connecting LLMs to operational data

- Links to the short scorecard and the eighteen-question enterprise tool

     Email unlocks the full printable checklist. Free to access, we just ask for an email.

     Print checklist **
    [AI Readiness Scorecard](/maturity/assess)

## Pyramid gates (Data Maturity Pyramid™)

     Work top-down only after the level below is honest. Tick what is true today, not aspirational.

### Level 1 · Data collection

- Critical business events are captured somewhere, even if fragmented

- You know which teams hold the master copies of customer, order and finance data

- Shadow spreadsheets are acknowledged, not ignored

### Level 2 · Data quality

- Core entities have agreed definitions (customer, order, SKU, margin)

- Different reports for the same metric are reconciled or retired

- Someone owns quality issues when numbers disagree

### Level 3 · Data integration

- Key systems connect without weekly manual extract theatre

- A central store or warehouse exists for the metrics leadership actually uses

- Join keys (customer ID, order ID) are stable enough for analysis

### Level 4 · Data analytics

- Repeatable reporting exists on a defined cadence

- Teams can answer “what happened?” without a hero analyst every time

- Dashboards have owners; unused reports are culled

### Level 5 · AI-driven insights

- Leadership has named commercial outcomes for AI, not tool FOMO

- Classified data and access controls exist before models touch personal or confidential data

- Human review paths exist for material automated decisions

## Enterprise diagnostic dimensions

     Aligned to the six dimensions in the [Enterprise Data Maturity](/tools/data-maturity) tool.

### Data quality

- Definitions documented for board and operating KPIs

- Automated checks exist for at least the top revenue and margin feeds

- Known bad fields have owners and fix dates

### Governance

- Systems register and classification scheme in use

- DPAs and Article 30 match reality for processors in the AI path

- Access is named-user with MFA on systems that would feed a model

### Infrastructure

- Data can be reached without copying to personal laptops

- Environments separate enough that experiments cannot overwrite production

- Logging and backup cover the stores AI would read

### Analytics capability

- Analysts spend more time on insight than on stitching extracts

- Metric dictionary stops “two versions of truth” in meetings

- Prioritised backlog of questions exists, not only a tool wishlist

### AI readiness

- Use cases ranked by commercial value and data feasibility

- No LLM or agent has blanket access to unclassified customer data

- Vendor AI features are treated as processors, with DPIA where risk is high

- Evaluation criteria exist before pilot spend (accuracy, latency, cost, risk)

### Commercial alignment

- Named executive owner and budget for data / AI work

- Success metrics are commercial (margin, cycle time, conversion), not vanity model scores

- Change management for the teams who must use the output is planned

## Hard no-gos before connecting an LLM

- No systems register or classification on the data the model would see

- Shared admin credentials on the source systems

- Unresolved dual sources of truth for the metrics the model would cite

- No lawful basis / DPA coverage for processors in the path

- No human escalation for outputs that affect customers, pricing or employment

      [Enterprise maturity tool](/tools/data-maturity)
      [Short AI Readiness Scorecard](/maturity/assess)
      [Read the pyramid](/maturity)
HTML: https://rodan.io/resources/ai-readiness-checklist