AI Readiness Assessment Template A Worked Workflow Example

The short answer

What is an AI readiness test?

An AI readiness test is a structured review of the prerequisites for using AI. This template evaluates one proposed workflow and turns the answers into scores, critical prerequisites and assigned next actions.

Use it when you can name a recurring task, the people doing it and the output that needs to improve. It suits an operations, IT or security leader preparing a scoped automation discussion. If you are evaluating an entire business unit, use the separate enterprise AI maturity scorecard.

GS Consulting develops secure AI automation across approved data, model processing and existing systems. This resource belongs to our enterprise AI guide series. For help choosing the workflow first, see how to identify workflows for AI automation.

What should an AI readiness assessment template include?

An AI readiness assessment template should include a defined scope, questions with a scoring rubric, supporting evidence, critical prerequisites and an action record with owners and review dates.

• Workflow scope. Use the Scope and decision tab to identify the trigger, inputs, expected output, operating owner, destination system and success criteria. Record the decision, restrictions and approval evidence after review.
• 24 questions. Four questions in each of six assessment dimensions, with response anchors from 0 to 4.
• Evidence and actions. Record a reference, responsible owner, next action and review date beside each answer.
• Separate scores. Compare opportunity with readiness without allowing strengths to hide a critical prerequisite.

Keep sensitive evidence in its approved repository. Use general labels and reference identifiers in the workbook rather than copying customer records, security findings or restricted data into it.

How to conduct an AI readiness assessment?

Define one workflow, gather evidence with its owners, answer the questions, review critical prerequisites and assign the work needed before a pilot decision.

1. 01

   Set the boundary

   Write down what starts the work, what information is used and what output reaches the next system. Identify the person who approves consequential actions.

2. 02

   Bring the evidence

   Review representative inputs, the current procedure, workload measurements, permissions and examples of acceptable output with the business, data and technical owners.

3. 03

   Complete the questionnaire

   Use the question specific response anchors in the Rubric tab. A zero is an actual selected answer. Leave an unanswered question blank and collect what is missing.

4. 04

   Read the prerequisites before the scores

   Check data authority, the ability to evaluate outputs, review before harmful action and accountable human ownership. A critical prerequisite takes precedence over the ordinary recommendation.

5. 05

   Assign the next decision

   Name who will resolve each gap, what evidence will demonstrate completion and when the team will review the workflow again. Approve a bounded pilot only through the appropriate human review.

Completed example

What does a completed AI readiness assessment look like?

A completed assessment connects each response to its supporting evidence and explains the next decision. In this fictional example, preparing host data for analyst review scores 84/100 for opportunity and 60/100 for readiness, but unresolved data authority prevents a pilot.

The architecture is informed by GS’s published private AI cyber-analysis implementation. Every assessment answer, score, effort estimate and evidence record below is illustrative. These are not the client’s historical assessment or measured results.

These are planning scores, not percentages of readiness or probabilities of success. The example remains on hold for AI data processing until authority is documented and the proposed scope is reviewed.

The worked copy includes an action for the data owner to document authority and an action for the technical owner to define the processing boundary. Review occurs when the required evidence is available; the example does not promise a delivery date.

How do you measure AI readiness?

Score each response from 0 to 4 using its own rubric, normalize the four questions in each dimension to 100, then calculate separate Opportunity and Implementation Readiness scores. Critical prerequisites override the score based recommendation.

The worksheet uses the same method as the live workflow readiness assessment. Expand a dimension below to see all 24 selected answers and their illustrative basis.

Each dimension is rounded before the weighted calculation. For example, Business Value totals 14 of 16 available points: 14 ÷ 16 × 100 = 87.5, rounded to 88. The four critical response checks are DR3, AS3, AS4 and SG4. A selected zero on any of those questions requires a critical prerequisite to be addressed. These four automatic checks are a limited aid. An unflagged result does not establish that every permission, security or operating requirement is satisfied.

These weights and thresholds are GS planning choices. They are not validated industry benchmarks, probabilities of success or an independent determination that a workflow is ready for production.

What are the five pillars of AI readiness?

One useful organizational grouping is strategy, data, technology, people and governance. Frameworks use different names and counts; there is no single mandatory five pillar structure.

For example, Microsoft’s organizational assessment describes seven pillars, while Cisco’s assessment uses six. The count matters less than whether the questions cover the proposed work.

The GS workflow template uses six dimensions. Business Value tests whether the work merits investment. Process and Knowledge examines repeatability. Data Readiness checks usable and authorized inputs. AI Suitability addresses output structure and evaluation. Security and Governance covers the processing boundary and accountability. Integration and Operations examines how the workflow will run and recover.

What are the five stages of AI readiness?

There is no universal five stage readiness standard. GS’s separate enterprise maturity planning model uses ad hoc, controlled pilot, operational, scaled and governed, and adaptive.

Those stages describe demonstrated organizational capability. They do not replace the workflow assessment’s question: does this proposed use have the prerequisites to proceed? An organization with mature shared services can still propose a workflow with unapproved data or an output nobody can evaluate.

Use the enterprise AI maturity guide and scorecard to compare business units or assess recurring practices. Use this template to prepare one proposed workflow for a decision.

What should you do after an AI readiness assessment?

Resolve critical prerequisites first, then assign the evidence and engineering work needed for a bounded pilot. Preserve the assessment so the next review can show what changed.

Is the AI readiness assessment template free?

Yes. Download the Excel workbook without a form or account. It includes the blank template, completed example, scope and decision record, and response rubric. You can also use the online assessment and view your results before choosing whether to request a review.