AI Readiness Assessment

Score the foundation before choosing the roadmap.

Use this assessment to understand practical AI readiness: what is working, where gaps exist, and which roadmap should come next.

Section 1

Company profile

Establish business context before scoring readiness.

Scoring scale

Rate each pillar from 1 to 5.

1Not in place
2Informal
3Developing
4Mature
5Scalable
Data: Clean it / Democratize itQuestions
  • Key business data is accurate, current, and trusted by the teams that use it.
  • We know where important data lives across systems, files, databases, and applications.
  • Major data sources have clear owners.
  • Data is organized well enough for reporting, analytics, automation, or AI use cases.
  • Teams can access needed data without excessive exports, spreadsheets, or workarounds.
  • Sensitive data is classified, protected, and only available to the right people.
  • We can connect data from multiple systems to answer business questions or power workflows.
People: Skill them / Empower themQuestions
  • Employees understand practical ways AI could help them in daily work.
  • Leaders understand the difference between AI tools, copilots, automation, and agents.
  • Employees have guidance or training on responsible AI use.
  • Teams know which AI tools are approved for company work.
  • Teams are encouraged to identify repetitive or low-value work that could be improved.
  • Managers are equipped to redesign workflows rather than add AI to old processes.
  • We have internal champions who can help others adopt AI.
Platform: Secure it / Connect itQuestions
  • We have a clear inventory of core business applications and systems.
  • Systems can connect through APIs, integrations, data exports, or automation platforms.
  • Identity and access controls are modern and consistently used.
  • We have a secure environment where AI tools can be tested.
  • IT understands which AI tools are currently being used across the business.
  • Cybersecurity controls can support broader AI adoption.
  • We have visibility into software costs, overlapping tools, and consolidation opportunities.
Governance: Guardrails / AccountabilityQuestions
  • We have an AI usage policy or acceptable-use guidance.
  • Employees know what data should not be entered into public AI tools.
  • There is an approval process for new AI tools or AI-enabled software.
  • AI governance, risk, and compliance have assigned ownership.
  • We understand legal, regulatory, privacy, or contractual constraints.
  • AI-generated outputs are reviewed before use in sensitive decisions.
  • Our governance approach allows responsible experimentation rather than blocking AI entirely.
Adoption: Pilot / ScaleQuestions
  • We have identified specific AI use cases that could create business value.
  • AI opportunities are prioritized by value, feasibility, risk, and effort.
  • We have run at least one structured AI pilot.
  • We know how to measure whether an AI pilot is successful.
  • We have a process for moving successful pilots into production.
  • AI work is tied to business outcomes rather than random experimentation.
  • We have budget for pilots, tools, training, or implementation support.
Process: Map / RedesignQuestions
  • Important business processes are documented.
  • We know where work slows down because of manual handoffs, approvals, or rekeying.
  • We understand which workflows are rules-based, judgment-based, or knowledge-based.
  • We have identified processes where AI could assist, summarize, classify, or execute tasks.
  • We are willing to redesign workflows rather than automate inefficient processes.
  • We can estimate the time, cost, or error rate associated with key manual work.
  • Process owners can help evaluate and improve workflows.
Leadership: Mandate it / Own itQuestions
  • The executive team agrees that AI is strategically important.
  • We have a clear business reason for adopting AI.
  • Senior leaders are actively learning about AI and its business implications.
  • An executive owner is assigned for AI strategy or transformation.
  • There is a decision process for selecting AI priorities.
  • We have a cadence for reviewing AI progress, risks, and results.
  • Leaders communicate clearly about how AI will affect employees, customers, and the business.

Score request

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What happens nextReviewed score

Diffingo reviews the assessment responses and prepares a readiness score with the most important gaps and next steps.

Recommended outputRoadmap focus

Your score can be paired with a recommended roadmap across data, people, platform, governance, adoption, process, and leadership.

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