What is an AI readiness assessment?

An AI readiness assessment evaluates how prepared your organization is to adopt and benefit from artificial intelligence. It examines key dimensions like data infrastructure, process maturity, technology stack, team skills, strategic alignment, and budget. The LAXIMA assessment uses 24 research-backed questions across 6 dimensions to produce an overall readiness score and actionable recommendations.

How long does the AI readiness assessment take?

The LAXIMA AI Readiness Assessment takes approximately 5-8 minutes to complete. It consists of 24 multiple-choice questions organized into 6 dimensions. You can navigate between dimensions freely and change your answers before viewing results.

Is this AI readiness assessment free?

Yes. The LAXIMA AI Readiness Assessment is 100% free — no sign-up, no email required, no paywall. All scoring runs entirely in your browser. You can share your results via a unique URL and retake the assessment as many times as needed.

What dimensions does the assessment measure?

The assessment evaluates 6 critical dimensions: (1) Data Infrastructure — data quality, accessibility, and governance; (2) Process Maturity — documentation, digitization, and measurement; (3) Technology Stack — modernization, integration, and security; (4) Team & Skills — AI literacy, technical talent, and change readiness; (5) Strategic Alignment — vision, leadership buy-in, and use case identification; (6) Budget & Resources — investment, timeline, and change management planning.

What do the readiness levels mean?

The assessment places you in one of four tiers: Early Explorer (0-30%) means you are in the early stages and should focus on fundamentals; Building Foundation (31-55%) means you have some elements in place and should prioritize data quality and team upskilling; AI Ready (56-78%) means you have a strong foundation and should start pilot projects; AI Leader (79-100%) means you are well-positioned for advanced AI and should focus on scaling and differentiation.

How accurate is the AI readiness score?

It is a structured self-assessment, so it is exactly as accurate as your own answers about your own organization — which means it reliably surfaces a gap you already half-suspected and does not settle an internal disagreement. It is not a benchmark: answers never leave your browser, so there is no dataset ranking you against other companies. Self-reporting also skews high, so where you are torn between two answers the lower one is usually the true one. Read the per-dimension breakdown rather than the headline number.

What should I do after getting my results?

Start with your lowest-scoring dimension — that is the binding constraint, and improving a strong dimension further rarely changes what you can attempt. Each dimension comes with its own recommendation based on how you scored it. If the low score is in data or process, that work comes before any tooling decision. If it is in strategy or budget, the gap is a conversation rather than a project. Once the groundwork looks solid, the AI ROI calculator is the natural next step for sizing a specific automation.

Can I share my assessment results?

Yes. Click the "Share results" button to copy a unique URL that preserves all your answers and scores. Anyone who opens the link will see the same results page. This is useful for sharing with leadership, team members, or consultants.

Free AI Readiness Assessment — Is Your Business Ready for AI?

How the AI Readiness Assessment Works

24 questions, six dimensions, four questions each. Every question offers four answers worth 1 to 4 points, where 1 describes the least mature situation we see and 4 describes a team that has the thing genuinely handled. Your score is the points you collected as a percentage of the 96 available — so a score of 60 means you answered at roughly the third option on average, not that you got 60 of anything right.

The reason the questions are split evenly across six dimensions is that the total is the least interesting output. Two organisations can score 55 with completely different problems: one with excellent data and no executive interest, another with a committed leadership team and everything stored in spreadsheets. Those two need opposite next steps, which is why the result breaks the score down per dimension and the recommendations are generated per dimension rather than from the total.

How the score is banded

Readiness tiers and their score ranges
Score	Tier	What it means in practice
0–30	Early Explorer	Focus on building data fundamentals, documenting key processes, and raising AI awareness across your team. Small pilot projects can help demonstrate value and build momentum.
31–55	Building Foundation	Prioritize data quality improvements, tool integration, and team upskilling. Identify 2-3 high-impact use cases for initial AI implementation to prove ROI.
56–78	AI Ready	You are well-positioned to implement AI across multiple functions. Focus on launching pilot projects, scaling successful automations, and building an AI center of excellence.
79–100	AI Leader	Focus on advanced AI applications, competitive differentiation through AI, and continuous optimization. Consider building proprietary AI capabilities and scaling across the enterprise.

The band boundaries are judgement calls, not thresholds derived from outcome data. They are set where the useful advice changes: below roughly 30 the honest answer is that groundwork beats pilots, and above roughly 78 the constraint is usually ambition rather than capability. A score two points either side of a boundary means the same thing — read the dimension breakdown, not the label.

The 6 Dimensions of AI Readiness

Data Infrastructure

The foundation of AI. Evaluates data storage, quality, accessibility, and governance. Without clean, accessible data, even the best AI models underperform.

Process Maturity

Measures how documented, digitized, and measurable your workflows are. Well-defined processes are dramatically easier and cheaper to automate.

Technology Stack

Assesses infrastructure modernization, system integration, existing AI usage, and security. Modern, connected systems enable faster AI deployment.

Team & Skills

Evaluates AI literacy, technical talent, change readiness, and training culture. People determine whether AI initiatives succeed or fail.

Strategic Alignment

Checks whether AI is part of leadership vision, if use cases are identified, and how technology success is measured. Strategy guides where AI creates the most value.

Budget & Resources

Reviews investment allocation, vendor processes, timeline readiness, and change management. Adequate resources turn AI strategy into reality.

Why readiness is usually the binding constraint

You will find a widely circulated statistic claiming that some large majority of AI projects fail, usually attributed to a major analyst firm. We are not going to repeat it, because the versions in circulation have drifted a long way from whatever was originally published and none of them survive being traced back. The underlying observation does not need a number to be useful: AI projects mostly stall on organisational problems rather than on model capability, and those problems are visible in advance.

The recurring ones are unglamorous. Nobody can say which process should go first. The data exists but not in a form anything can query. A pilot works, and then no one owns it. Budget is approved for tooling and not for the six weeks of process work that has to happen first. None of those are solved by choosing a better model, and all of them are cheaper to find now than after a procurement cycle — which is the entire argument for scoring readiness before spending.

What this score is and is not

This is a structured self-assessment. Every input is your own judgement about your own organisation, which makes it a good way to surface a gap you already half-suspected and a poor way to settle an internal disagreement. Three limits worth naming:

It is not a benchmark. Your score is not compared against other organisations, because we do not collect answers — the scoring runs entirely in your browser and nothing you select is sent to us. There is no dataset here to rank you against, and we would rather say that than imply one.

Self-reporting skews high. People assess their own data quality and process documentation generously. If you are between two answers, the lower one is usually the accurate one. A useful trick is to have two people fill it in separately — where their answers diverge is often the real finding.

Six dimensions is a simplification. Regulatory exposure, procurement speed, and the political question of who sponsors the work all matter and none of them get a question. A high score means no obvious blocker in the six things we ask about.

Used for what it is — a structured prompt to have a specific conversation with specific people — it is worth the eight minutes. Read as a verdict, it is not.

Want to go deeper?

This assessment shows where you stand. Turn your results into next steps with our guides on AI strategy, data readiness, and rolling out AI agents.

Read the guides

Want to see the financial impact of AI? Try our free AI ROI Calculator to estimate annual savings and 5-year ROI for your business.

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