AI Readiness Assessment

An AI readiness assessment is only as sound as the working reality behind it, and what people actually do day to day is what a survey and a room full of managers never quite reach.

For consultancies running AI readiness work: hear from every employee, reach the reality that never makes it into a workshop, and hand your client an assessment grounded in how their people really work today.

The question every client is asking right now

How do we make the most of AI,
and where does it put us at risk?

Where it breaks

AI potential cannot
be effectively assessed
from the top.

01

Today the potential is judged from a few conversations at the top.

02

The people whose work AI is meant to accelerate are never asked.

Senior stakeholders can describe the ambition, but not where AI would really save time. That lives in the daily work below them. To find it, the conversation has to reach the whole workforce, not a sample at the top.

A score is too shallow

The reality of every workday
shows exactly where the potential lies.

Checkboxes and rating scales give you a score, not the reason behind it. Where AI would really help lives in how people describe their own work, and a form has no way to ask.

Which repetitive tasks take up most of their week.

The manual steps they would gladly hand to a tool.

Where a small mistake by AI would cause real problems.

A survey measures,
it never listens.

And this is what you hear

What you can hear and analyse, at scale across the whole organisation.

The interviews go deeper than any form can. People describe their own work in their own words, and the interviewer follows up on every answer, digging into the why and the how. This gives you a strong foundation for your assessment and your recommendations.

Where does AI stand today?

The real state of adoption, not the official one.

"I pay for my own chatbot." "We quietly stopped using the official tool." "No one ever asked, so I never said." "IT does not know we use it."

You can tell the client where AI is already in use, where it stalled, and where data is leaving the building.

Where should AI go next?

The ideas people already have.

"Hours copying numbers by hand, every Monday." "A tool could just do this part." "I want a person to check client work." "Let me keep the client calls."

You can point to the tasks worth automating first, and where people want a human to stay in the loop.

Your assessment, better evidence

You write the roadmap. Cartorga gives you the evidence.

You still score the maturity, set the priorities, and lead the client conversation. Now that work rests on the whole organisation, not a handful of interviews at the top.

Why it holds up

People say what a workshop never hears.

Anonymous by design

No answer can be traced to a person, so people are honest about the unapproved tools, the data shortcuts, and the fear about their job. Will people open up to an AI?

Works councils tend to welcome it

Because nothing traces back, people see it as a real channel to be heard, not a way to be monitored. Do we need works council approval?

Nothing is invented

Every finding is backed by evidence from the actual conversations. If there is no evidence for it, it does not appear. How do you stop the AI making things up?

Every voice, not a sample

Everyone can take part at once, so the assessment rests on the whole organisation, not the few people a workshop can fit in a room. How many people can you reach?

The deliverable

Every conversation, turned into the analysis
you point it at.

Where AI would help most and where it already stands today, including the shadow tools people only admit in private, drawn from what the whole workforce described about their daily work.

You run the assessment.
Your interviewer reaches everyone.

Train it on how you run discovery, then see it on one of your own engagements.