See how AI has impacted your roles
Upload the job descriptions you already have and get a full role-by-role analysis: which tasks AI takes on, which skills are emerging, and where the opportunities sit.
Available now · 24h post-ingestion
Role titles tell you nothing. Tasks tell you everything.
Most of the public conversation about AI and jobs happens at the wrong altitude. Headlines say forty per cent of jobs are exposed to AI. Analyst decks say your industry will be disrupted. None of it helps you make a single decision on a Tuesday, because none of it says which of your roles, doing which of their tasks, changes in what way, starting when.
A role is not a unit of work. It is a bundle of tasks, and AI does not take jobs, it takes tasks: unevenly, at different speeds, with very different consequences for the person in the seat. When you score every task independently, with cited market evidence behind each score, the pattern is almost never what the headline said. The role rarely disappears. It compresses, it shifts, and hours open up inside it, and what you do with those hours is the entire transformation question.
AI does not take jobs. It takes tasks, and no two roles lose the same ones.
The organisations that get this right share one habit: they measure before they move. Not with a benchmark borrowed from a report about somebody else's workforce, but with a baseline built from their own roles, confirmed by their own people. Everything defensible that follows, restructures, tool decisions, reskilling budgets, starts from that baseline. Everything regrettable starts from a guess.
That is what this programme builds: a task-level read of your actual organisation, with the evidence visible behind every score, in about twenty-four hours from the moment your roles are in. Not a prediction about the economy. A map of your own ground.
What this programme does.
Every role is broken into its atomic tasks, and every task is independently scored for AI displacement potential with a structured rationale and cited market evidence. No black boxes: you can see exactly why each score is what it is.
Scores roll up into hours freed per week per role, projected across time horizons: what is automatable now, what is coming in six months, and what remains distinctly human.
From kickoff to landed.
Available now · 24h post-ingestion
Your roles go in
Upload job descriptions in whatever state they are in, paste them, describe them, or pick from the library. The engine breaks each role into its atomic tasks and proposes the map.
Your team signs off the task maps
A confirmation gate, not a black box: your people check the proposed tasks against what the work actually is, and correct anything the documents got wrong.
Every task scored, with evidence
Each task is independently scored for AI displacement potential with a structured rationale and cited market evidence, then rolled up into hours freed per week, per role, across time horizons.
Walk the results with our team
Growth Reports per role, Manager Briefs per team and the AI Activation Plan land in the platform, and we walk your leaders through what the evidence means before anyone acts on it.
What you get.
Living documents, not slideware: every deliverable stays connected to the graph and updates as the analysis moves.
Growth Report per role
What is changing, which skills to build, and the development path for the person in the seat.
Manager Brief per team
The conversation guide for leading a team whose work is shifting.
AI Activation Plan
Which tasks to hand to AI first, and the capacity that frees.
What you need.
- Your roles: upload job descriptions, paste them, describe them, or pick from the library
- Rough team sizes so capacity rolls up correctly
- Nothing else: the engine proposes the task maps for you to confirm
The questions teams ask about this programme.
How is this different from published AI job-exposure studies?+
Published studies score generic occupations against generic task lists. This programme scores your roles, as your job descriptions and your people define them, and every score carries a structured rationale with cited market evidence. The output is a decision tool for your organisation, not a talking point about the economy.
What do we need to provide to start?+
Your roles, in whatever form exists: job descriptions uploaded or pasted, a rough description, or picks from our library. Rough team sizes help capacity roll up correctly. Everything else the engine proposes for your team to confirm.
Our job descriptions are messy and out of date. Is that a problem?+
No, and it is one of the most common starting points. The engine drafts the task maps from what you have plus a library of current market job data, and your team corrects them at the confirmation gate. Most clients end up with living job descriptions that finally match the real work.
Is this a redundancy analysis?+
No. The output is a capacity instrument: which tasks AI absorbs, which hours open up, and which skills to build. What you do with freed capacity is a leadership decision, and the Transform programmes exist to model those decisions as scenarios before anything is committed.
How can we trust the scores?+
Every task score shows its rationale and its cited evidence: no black boxes. Nothing rolls up into a report until your team has confirmed the task maps at the gate, and every analysis version is audited so you can always see what changed and why.
Programmes compound.
Each programme deepens the same graph the next one runs on: nothing is re-gathered, nothing starts from zero.
Redesign your org to be AI-first
Once you can see where AI changes the work role by role, the next question is what the organisation should look like around it.
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Start with this programme, on one department.
Know exactly where AI changes the work before you spend on tools or restructure a team.



