AI Readiness Assessment — Starter

How to Use This Assessment

Answer each statement based on your best current understanding of the organization or business unit. Where uncertainty exists, responses should reflect the organization’s current operating reality rather than aspirational goals.

The assessment is intended to provide directional insight to support leadership discussion and decision-making.

Scale: 1 = Strongly Disagree · 2 = Disagree · 3 = Neutral · 4 = Agree · 5 = Strongly Agree
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Strategic Intent & Value Clarity Section 1 of 5 · Rate 1–5
The organization has clearly defined where AI is expected to create business value, aligned to specific outcomes.
AI initiatives are explicitly linked to business priorities and strategic objectives, rather than driven by technology availability.
There is clarity on which decisions or processes AI is intended to augment, automate, or improve, and why those decisions matter.
Senior leadership shares a common understanding of the role AI should play and supports its use consistently.
The organization has a deliberate investment posture toward AI (timing, scope, funding), rather than opportunistic spending.
Decision Ownership & Governance Section 2 of 5 · Rate 1–5
There is clear accountability for who owns AI-related decisions, including approval, prioritization, and oversight.
A defined governance structure exists to oversee AI initiatives, including alignment with strategy, risk, and compliance requirements.
Ethical, legal, and responsible AI considerations are explicitly considered when AI is introduced or scaled.
There are clear mechanisms to escalate, pause, or stop AI initiatives if risks or unintended outcomes emerge.
AI-related decisions involve appropriate cross-functional input (business, IT, risk, legal, HR), not a single function.
Data Readiness for AI-Driven Decisions Section 3 of 5 · Rate 1–5
Data required to support priority business decisions is available, accessible, and usable across the organization or business unit.
Data used for decision-making is accurate, timely, and trusted by business leaders.
Clear ownership exists for data quality, definitions, and accountability, including mechanisms to resolve issues.
Data from key systems can be combined or reconciled to provide a coherent view for decision-making.
Decision-makers can understand where data comes from, how it is transformed, and its limitations.
Technology Enablement (Foundational, Not Tools) Section 4 of 5 · Rate 1–5
Core digital systems and infrastructure are reliable, scalable, and able to support increased data and automation demands.
Systems supporting key business processes can exchange data and integrate effectively, rather than operating in isolation.
Appropriate security, privacy, and access controls are in place to support AI-enabled use of data without increasing risk exposure.
Technology standards and architectural principles exist to guide the introduction and scaling of AI-enabled capabilities.
The organization can monitor, support, and sustain AI-enabled systems once deployed (reliability, support, issue resolution).
Change Capacity & Organizational Readiness Section 5 of 5 · Rate 1–5
Senior leaders actively sponsor AI-related change and reinforce its importance through consistent actions, not just messaging.
The organization demonstrates the ability to adopt new ways of working, including changes to roles, processes, and decision-making.
The organization has a track record of executing complex change initiatives and sustaining outcomes over time.
Key stakeholder groups are identified, engaged, and prepared to support AI-related changes.
The organization has sufficient capacity and resilience to manage AI-related change alongside other strategic priorities.
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This assessment is designed for leaders and transformation teams with visibility into strategy, operations, and governance.