MxD AI Readiness Test

What is the CEO AI Readiness Test?

The CEO AI Readiness Test is a free online self-assessment from MxD Digital, a B2B growth marketing agency. It is designed for CEOs and executive teams that want a structured starting point for deciding where AI can be used in the business. The page positions the test as a three-minute executive assessment that produces a directional snapshot rather than a detailed audit.

The assessment reviews six readiness categories: strategy, data, team, infrastructure, ROI and governance. Its stated purpose is to help users find the main constraint, choose where to invest first, and leave with a practical first move. The result is presented as a six-part breakdown with practical next steps, not as a peer benchmark or an independent audit.

How the CEO AI Readiness Test works

The assessment consists of 12 multiple-choice questions, with two questions in each of the six dimensions. Responses are worth 0–3 points. Each dimension is scored out of six, and the total is converted to a percentage. Before viewing the result on screen, users enter their name and email.

The scorecard preview on the page shows how the six categories can be displayed. It also illustrates how a low governance score beside a stronger strategy score can indicate that tool adoption may become a business risk, with a suggested first move to set approved-use and human-review rules for the first workflow. The page describes this as a directional snapshot based on the user’s answers.

MxD also offers a free strategy call after the assessment. According to the page, the score is used to identify the strongest use cases, the weakest operating layer, and the 90-day moves that should come first.

Main features

• A 12-question executive assessment estimated at three minutes.
• Six readiness categories: strategy, data, team, infrastructure, ROI and governance.
• Two multiple-choice questions per category, worth 0–3 points each.
• Dimension scores out of six and a total percentage score.
• A six-part scorecard with a detected top gap and example first moves.
• Guidance framed around finding the real constraint, choosing where to invest first, and leaving with a first move.
• A free strategy call option for discussing use cases, operating-layer gaps and 90-day priorities.
• A scorecard preview that shows illustrative scores by category.

Pricing

The CEO AI Readiness Test is presented as free. The page also offers a free strategy call. No pricing for MxD Digital’s broader marketing or AI services is published on the supplied pages.

Common use cases

• Giving a CEO or executive team a quick, structured snapshot of AI readiness.
• Identifying which operating layer may be holding back AI adoption.
• Comparing readiness across strategy, data, team, infrastructure, ROI and governance before selecting tools.
• Surfacing governance gaps that could turn tool adoption into business risk.
• Preparing for a strategy call about AI use cases and early priorities.
• Choosing a practical first move, such as defining approved-use and human-review rules for a first workflow.

Limitations

The test is self-reported and directional. MxD explicitly describes it as a starting point, not a peer benchmark or an independent audit. With only 12 questions, two per dimension, it offers a high-level view rather than a deep diagnostic of data quality, system architecture, team capability or governance maturity.

Users must enter their name and email before viewing the result. The assessment covers six broad categories but does not publish industry-specific benchmarks or detailed scoring methodology beyond the point system. It should not be treated as a substitute for technical due diligence, security review or a full AI readiness audit. Pricing for MxD’s broader services is also not disclosed on the supplied pages.

Summary

The CEO AI Readiness Test is a lightweight, free executive assessment for organizations that want an initial view of where AI may fit and what may be blocking progress. Its six-category scorecard and suggested first moves make it useful for framing early AI conversations, while its self-reported and directional nature means it should be followed by deeper validation before major investment decisions.