What does the AI readiness audit actually check?

It reviews your workflows, data availability, team adoption capacity, ownership readiness, governance needs, and whether the business can measure a useful before-and-after signal for each candidate use case.

Do we need clean data before starting the audit?

No. The audit is designed to reveal whether your current data is usable, what is missing, and what needs to improve before a pilot can be trusted. Data readiness is one of the outputs, not a prerequisite.

Does the audit produce an implementation plan?

It produces a practical next-step roadmap. If implementation makes sense, the roadmap defines the first pilot, owner, success signal, and risk boundaries. If readiness is too low, it tells you what to fix first.

How long does the audit take?

Typically one to two weeks, depending on business complexity, access to workflow data, and leadership availability for the review conversation.

What happens after the audit?

You get a decision brief with a clear recommendation: move to a pilot, address readiness gaps first, or wait. If a pilot is recommended, the brief connects directly to the implementation service.

AI Readiness Audit

Luxembourg SMEs

Before tools, test readiness

Know what AI can actually do for your business.

Find where AI can realistically help, what needs to be in place first, and which opportunities are worth pursuing.

Discuss if readiness fits

For SME leaders•Practical•Confidential•Results-focused

Readiness radar

six dimensions

Where you are

Curious but not committed

The team has AI ideas, vendor emails, and internal pressure, but no clear answer on what to do first.

The decision

Before budget, before tools

You need to know which AI opportunity is real, which is premature, and what must be fixed before a pilot can succeed.

What you leave with

A first-pilot recommendation

A scored shortlist of use cases, a readiness verdict, and a 30-to-90-day action path tied to measurable outcomes.

Quick check

How ready is your business for AI?

Four questions. No signup. You get a readiness signal and a clear next step.

This is a conversation starter, not a diagnosis. The full audit maps six dimensions across every candidate workflow in your business.

Quick check

Four questions to gauge your AI readiness

Answer honestly. This is not a test of your business. It is a fast way to see where the gaps are before the audit begins.

Can you point to a specific workflow where AI would reduce friction or save time?

Is the data that AI would need already captured somewhere in your business?

Can you name one person who would own the AI pilot and its results?

Could you measure whether the first AI project worked within 90 days?

Answer all four questions to see your readiness signal (0/4 done).

Audit process

Four steps from uncertainty to a pilot-ready decision.

The audit maps what is real, scores what is ready, and produces one recommendation the leadership team can fund and own.

01

Map friction points

Identify the workflows, decisions, and repeated tasks where AI could realistically reduce drag or improve output.

02

Score readiness dimensions

Rate business value, workflow stability, data availability, ownership, adoption risk, and governance needs for each candidate.

03

Prioritize first pilot

Select the use case with the strongest readiness signal, clearest owner, and most measurable before-and-after.

04

Define success signals

Set the specific metric, timeline, owner, and governance boundary the pilot will be judged against.

What the audit produces

Decision-ready output, not a slide deck.

Everything a leadership team needs to fund, own, and execute the next AI move.

Readiness score across six dimensions for each candidate workflow

Prioritized use-case shortlist with go, wait, and stop verdicts

Recommended first pilot with owner, success metric, and risk boundary

Data-gap and governance notes specific to your operating context

30-to-90-day action roadmap: audit, pilot, or automate

Decision brief for leadership: what to fund, what to postpone, what to skip

Realistic expectations

Leadership sees where AI is useful, where it is premature, and what success should look like before a single tool is evaluated.

Safer first pilot

The first project is chosen because it has a workflow, owner, inputs, and a measurable business case, not because it sounds innovative.

Less wasted motion

Tool discussions become faster because the business need, data gaps, and governance boundaries are already defined.

Fit check

Is this the right starting point for your business?

Good fit

Pursue

Founders, CEOs, COOs, and department leads exploring AI adoption for the first time
Businesses with many AI ideas but no clear first workflow or owner
Teams that want a practical 30-to-90-day direction before committing implementation budget

Start elsewhere

Pause

Teams that have already validated a use case and only need build support
Businesses looking for a generic maturity scorecard without operating detail
Projects where leadership wants a report but no decision or accountable owner

Related thinking

Read before the first pilot.

These articles cover the readiness, data, and governance foundations the audit is built on.

AI

AI readiness for Luxembourg SMEs

AI

AI data readiness for Luxembourg SMEs

AI

AI governance before the first pilot

Explore all AI services Move from readiness to implementation

Questions leaders ask

Before the audit begins

Know before you commit.

The audit reveals which AI opportunity is real, what needs to be fixed first, and whether your business is ready to pilot or should wait. Take the four-question check above, or explore all AI services.

Explore all AI services