Redesign roles for AI
Your roles have already changed. Your job descriptions haven’t.
AI moves tasks inside a role faster than any architecture project can describe them. Turn the roles you have into standards that say what the work requires now, what each level expects, and the AI readiness the role needs, then see who is ready for the new version.
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Solutions Engineer
Medior · role standard, this version
Approved by you
What the work now requires
AI judgment & boundaries
Added this cycle
R3
AI workflow design
Added this cycle
R2
Client consulting
Unchanged
Carried over
Manual report preparation
Removed from the role
Retired
12 people in this role · 5 meet the new standard
See the gaps
The shift
What AI actually changes inside a role.
Whole jobs rarely disappear. Tasks move, the work that remains gets harder, and new requirements appear that no job description mentions. The role keeps its title and stops meaning the same thing.
Talentpilot does not predict which roles AI will change. Your organisation decides that. This is about describing and measuring the result.
Tasks move, not whole jobs
AI takes parts of a role and leaves the rest. The org chart looks identical while the work inside it has been rearranged.
What remains gets harder
When the routine part is automated, judgment, verification and exception handling become the job. The level required goes up, not down.
New requirements appear
Knowing what to delegate to AI, designing the workflow around it and building something reusable are part of the role now. None of them are in the job description.
Everyone decides privately what good looks like
Without a stated standard, each manager sets their own bar. That surfaces later as inconsistent hiring, development and promotion.
The problem
Redesigning the role is the easy half. Knowing who can do it is the other one.
Architecture projects deliver a snapshot.
Months of work produces a document describing the roles as they were when the project started, and nothing that keeps it current.
Nobody knows who is ready for the new version.
The redesigned role exists on paper. Whether the twelve people currently in it can do the work is still a conversation between managers.
AI capability is measured by attendance.
Completion rates tell you who sat through the training. They do not tell you who can exercise judgment about AI output in front of a client.
A role you cannot describe is a role you cannot staff, develop or hire for.
How it works
Describe the new role, then find out who can do it.
The standard is written once and kept current. People are measured against it from evidence rather than assumption, and each gap becomes practice. Three capabilities, one record.
Your redesigned role standard, including AI readiness
Capability 01
AI-native Job Architecture
The roles you have become structured standards: what the work requires, what each level expects, and AI readiness on three fixed dimensions. Where you have already redesigned a role, it takes your version.
How job architecture works →
Capability 02
Skills & Capability Mapping
Everyone in the role is measured against the new standard from evidence of what they have demonstrated, so readiness is a count of criteria met rather than an opinion.
How capability mapping works →
Capability 03
Development & Reskilling
Each remaining gap becomes practice in the flow of work with Niko, the AI coach. Progress is recorded against the same standard, so the readiness picture moves as people develop.
How development works →
Then reused
The same standard decides who you redeploy into the new role and who you hire for it, so the redesign does not stop at the document.
Start with the role AI changed most.
Send the job description you have today. We will show you the standard it becomes and how many of your people already meet it.
Proof
Running at the scale a redesign actually needs.
NOTINO
“It brings objectivity to the subjective assessment of candidates or employees. This makes employee development significantly more relevant and individualized.”
Michal Daniel, Chief People and Legal Officer
100,000+
people on the platform
100+
companies across job architecture, skills, development, redeployment and hiring
Where the line sits
What Talentpilot does not do.
Redesigning work around AI is a leadership decision, not a software output. Being precise about the boundary is what makes the rest usable.
It does not predict which roles AI will replace
Nothing here forecasts your headcount or tells you which jobs go away. A vendor claiming that is selling a projection, not evidence.
It does not design your operating model
Which tasks move to AI, which stay human and how teams are shaped is your decision, taken with your business leaders.
It does not approve the new standard
HR validates each standard with the business before it becomes the reference point. The AI structures; the company decides.
Enterprise control & governance
Redesign at scale, without losing the thread.
Review before rollout
Every standard is validated with the business before it becomes the reference point for hiring, development or redeployment.
Local nuance where it matters
One structure across the organisation, with room for genuine differences between functions, markets and business units.
Evidence you can inspect
Every readiness signal traces back to the standard it was measured against, so a decision about a person can be explained.
Frequently asked questions
Does Talentpilot decide which roles AI will change?
No. Your organisation decides how work should be redesigned and which tasks move. Talentpilot takes the roles and the decisions you have made and turns them into structured standards you can hire, develop and redeploy against. It structures; you decide.
What is AI readiness, specifically?
Three fixed dimensions defined per role and per level: AI judgment and boundaries, AI workflow design, and reusable and shareable solutions. Because the dimensions are the same everywhere, a person is comparable across roles and teams, and a role is comparable across countries.
Do we have to rewrite every job description first?
No. Talentpilot starts from the job descriptions, role families and levels you already have. Where you have already redesigned a role, it takes the new version. Where you have not, it structures the current one so you can see what is actually there before you change it.
How is this different from an AI skills taxonomy?
A taxonomy lists skills. It does not tell you what a specific role requires at a specific level, or what any individual can demonstrate. Talentpilot produces a standard per role and measures people against it from evidence, which is what a redeployment or hiring decision needs.
Where do people actually build the new capability?
Gaps become practice with Niko, the AI coach, in the flow of work rather than a course catalogue. Progress is recorded against the same standard, so readiness updates as people develop instead of at the next review.
