What will AI change in your workforce?

Your company's stance on AI(applies to every family: sets the adoption speed)

Finance and controlling (FP&A)

ISCO-08 2411, 2413

Management controller, FP&A analyst, Financial analyst, Finance business partner, Budget controller, Industrial controller

AI exposure56%

Headcount need, in FTE

Exposure range
FTE
Need in 203085 FTE-15 FTE (-15%)
Need in 203570 FTE-30 FTE (-30%)
10080604020262028203020322035
How AI is used on these tasks todayIn AI conversations about this job's tasks: the AI does the task itself (automation) or helps the person do it (augmentation).Anthropic Economic Index, April and May 2026. Occupations: Financial and Investment Analysts, Budget Analysts. AEI
Average automation potential of the job's tasks. Range for this family: 43 to 68%.ILO occupations used: Accountants (51%), Financial Analysts (62%). ILO data
Your call: how much of this potential do you want to capture? Nobody can set it for you.
3. Adoption speed midpoint 2030
Inherits your company stance, adjustable for this family.
Default 55%: Executives ask for more scenarios and finer analysis once producing them gets cheaper, so a good part of the gain is reinvested.

Target AI skills

level 1 to 4
Foundation
Use AI assistants every day
Frame and phrase a request
Check and challenge AI outputs
Protect data and respect the rules
Applied
Rethink one's process with AI
Analyse data with AI
Produce content with AI
Delegate to and supervise AI agents
Expert
AI governance and risk management

Job skills

Growing in value

  • Scenario modelling and driver-based forecasting
  • Challenging operational assumptions with managers
  • Presenting trade-offs to the executive committee
  • Consistency checks on model outputs

Losing value

  • Collecting data from multiple ERP extracts
  • Spreadsheet restatements and reconciliations
  • Writing standard monthly variance comments
  • Building recurring reporting packs

How the job will change

In most finance departments, the monthly cycle is still built on extracting data, restating it in spreadsheets, checking it against the ledger and writing variance comments. AI assistants inside planning and reporting tools now draft those comments, flag anomalies and rebuild forecasts from operational drivers, which cuts the time needed to produce a monthly pack or a budget iteration.

The role moves closer to the business. Controllers will spend more time testing assumptions with plant managers or sales directors and turning several scenarios into a clear decision. The good controller tomorrow is the one a business unit head calls before deciding: someone who can explain why the forecast moved and who notices when a model output makes no sense.

2026-2027
Assistants draft variance comments and speed up reporting packs.
2028-2030
Rolling forecasts largely automated; budget cycles get shorter.
2031+
Smaller teams focused on scenarios and business partnering.
Watch out

Many current controllers were hired for their spreadsheet skills, not for their influence with operations. The main risk is a skills gap in the business partner role rather than a headcount surplus. See the seniority outlook below.

What if you hired fewer juniors?

Your 2036 seniors are the juniors you hire today.

Seniors available in 2036-5%2 FTE short
Gap above 5% from2036
Your seniority mix today
Mid-level (3 to 10 yrs in the profession, the remainder)45%
For
Advanced settings
If every company makes the same bet, senior profiles will be scarce and expensive.
80601002026203020342040Senior need (held stable)Seniors available
Seniority mix, % of today's headcount
Juniors25%Mid-level42%Seniors28%

2026 2036

Free guide

The AI Cookbook 2026

albert's guide to cut through the noise around generative AI and turn it into workforce decisions.

  • What AI actually changes in jobs and skills
  • Why the junior pipeline matters more than most companies realise
  • How to integrate AI into workforce planning
Download the AI Cookbook
The AI Cookbook 2026, albert

Run these scenarios on your actual workforce

AI Impact Diagnostic: 6 to 8 weeks, your data in albert, three costed scenarios and the projected seniority mix for each job family.

Book a call

How the numbers are built

Every headcount figure combines four assumptions. Three come pre-filled from public research and job family defaults. The strategic ceiling is yours to set.

Public researchExposureAverage automation potential of the job's tasks, from the ILO's 2025 task-level scores.
Your decisionStrategic ceilingHow much of that potential you choose to capture. Your decision, not ours.
Your companyAdoption speedHow fast your company moves, set once for the whole company.
Job family defaultConversion to headcountHow much of the productivity gain becomes fewer people rather than more output.
Headcount effect

My simulation

Add the job families you want to compare. Your PDF report covers every family in your simulation, with the assumptions you saved.

albert

Get your AI impact report

A PDF built from the families and assumptions you set. It covers every family you adjusted.

Your settings are saved with your request, so whoever calls you starts from your own assumptions.