Turn AI adoption into results
Everyone has the tools. Few use them well.
Licences and courses tell you who has access. Talentpilot shows who actually uses AI well in their role, and Niko coaches everyone else on their real work until it sticks.
Request demoMicrosoft and LinkedIn, 2024 Work Trend Index: 31,000 knowledge workers across 31 markets.
AI adoption · Sales team
32 people
Evidence-based
32
have AI tools
29
completed training
11
hit the expectations
By dimension
AI judgment & boundaries
At standard
AI workflow design
Gap · 14 people
Reusable & shareable solutions
Gap · 19 people
White line = the standard for this role and level
Next · coaching on AI workflow design for 14 people
Start with Niko
The shift
Access is not adoption.
Most companies have bought the licences and run the training. What they cannot see is whether anyone now works differently, and whether the people who do are using AI well or just using it a lot.
Training is measured by attendance
Completion rates say who sat through the course. They say nothing about who can now judge AI output in front of a client.
Good use looks different in every role
What AI adoption means for a finance analyst is not what it means for a sales lead. One generic programme fits neither.
The best habits stay private
Your strongest AI users build workflows nobody else sees. Without a way to spot them, the know-how never spreads.
Usage happens off the books
People bring their own tools and work out their own habits. The company sees neither the good practice nor the risky one.
The problem
You can count the licences. You cannot count the capability.
There is no standard for good.
Nobody has written down what using AI well means in each role, so every manager decides privately and nobody can compare.
Nobody knows where the gaps are.
Without measurement, the AI budget goes to whoever asks loudest rather than to the teams and roles that are furthest behind.
Courses don’t change habits.
Judgment about AI is built by practising on real work, with feedback. A one-off course fades before the next quarter starts.
Buying AI is the easy part. Getting people to use it well is the challenge.
How it works
Define good, measure it, then build it.
AI adoption is set per role and level, measured from evidence of what people can demonstrate, and built up through coaching on real work.
Meet Niko, the AI adoption coach. Here is a typical first conversation.
Niko · AI adoption coach
Account manager
Everyone says we should use AI, but I honestly don’t know where it fits in my job.
Let’s find out together. Walk me through your week. What takes you the longest?
Client proposals. I rewrite an old one from scratch every single time.
That’s a great one to hand to AI. Open your company’s AI assistant and I’ll tell you how to draft from your CRM notes, then the two things to check before it goes out.
Starts from the person’s real work
No course catalogue. Niko asks about the role, the week and the tasks that take the longest.
Knows what great looks like
Which work AI handles well, which needs a human check, and which workflows the best teams in your company already rely on.
Works in your tools
Niko can connect to the AI tools you already license, so practice happens where the work does.
Makes it stick
Weekly follow-ups turn a first try into a habit, and the workflows that work get shared across the team.
Meet Niko
Works on its own
Add job architecture and capability mapping, and Niko coaches against the standard for each role, while you measure adoption company-wide.
The adoption report
See where adoption is real, and where it is stuck.
One view for the leadership team: who uses AI well, which teams are behind, and which workflows are worth spreading.
AI adoption report
Whole company · Q3 2026
412
people coached by Niko this quarter
+96 since Q2
38%
meet the adoption standard for their role
up from 21% in Q2
1,284
AI workflows in regular use
+310 since Q2
146
workflows shared across teams
9 adopted company-wide
Adoption by team
% meeting the standard · change vs Q2
Sales
54%
+18 pts
Customer support
49%
+15 pts
Marketing
41%
+9 pts
Engineering
36%
+6 pts
Finance
17%
+1 pt
Legal
12%
no change
Where to focus next
Finance · AI workflow design
23 people below the standard. Most use AI for search, not yet for the reporting work that takes their week.
Niko coaching plan started
Most reused workflows
Proposal draft from CRM notes
Sales
used by 38
Ticket summary and reply draft
Customer support
used by 31
Campaign brief from past results
Marketing
used by 17
Start with one team.
See where its AI adoption really stands today, and what it would take to close the gap.
Where the line sits
What Talentpilot does not do.
Measuring AI capability only works if people trust how it is measured. Being precise about the boundary is part of the product.
It does not replace your managers
Niko coaches the individual. Managers still lead the team, set priorities and own the conversation about performance.
It does not pick your AI tools
Talentpilot is vendor-neutral. It measures the capability to use AI well, which carries over from one tool to the next.
It does not replace your training
Your programmes stay. Talentpilot shows which of them change what people can do, and for whom.
Enterprise control & governance
Measure adoption without losing trust.
Private by design
Coaching sessions stay between the person and Niko. Managers see adoption and progress, never the conversation.
One standard, local nuance
The same three AI adoption dimensions everywhere, with required levels set per role, market and business unit.
Evidence you can inspect
Every adoption result traces back to what was demonstrated and the standard it was measured against.
Frequently asked questions
Do people need to know anything about AI to start?
No. The first conversation can be a single question: I don’t know how to use AI in my role. Niko asks about the job and the week, and starts from the task that would help most.
How do you see whether adoption is working?
Adoption is measured on three dimensions, set per role and level: AI judgment and boundaries, AI workflow design, and reusable and shareable solutions. Because the dimensions are the same everywhere, you can compare teams, roles and countries, and see which ones are moving.
We already run AI training. Why do we need this?
Training tells you who attended. Adoption tells you who now uses AI well in their actual job. Talentpilot sits alongside your programmes and shows which of them are moving the numbers, and for whom.
Which AI tools does it work with?
All of them. Talentpilot is not tied to a vendor. It measures the capability to use AI well, which transfers between tools, rather than proficiency in one product.
Where do people actually build the capability?
With Niko, the AI adoption coach, on this week’s real tasks rather than a course catalogue. Every session adds evidence, so adoption updates as people improve instead of at the next review.
