How we assess AI's impact on jobs
Unlike simplistic approaches that give a single automation percentage, we distinguish two fundamental dimensions of AI's impact on each task.
Measures to what extent AI can perform this task independently. An 80% index means AI produces an equivalent result in 80% of cases, without human intervention.
Ex: Data entry, email sorting, standard report generation
Measures the potential for AI augmentation. A high index means AI can significantly improve human productivity or work quality.
Ex: AI-assisted diagnosis, augmented writing, data analysis
The two indicators are combined in a 4-zone quadrant that visualizes a job's position relative to AI.
Low AI alone, low augmentation. Jobs minimally impacted by current AI (e.g., plumber, nurse).
Low AI alone, high augmentation. AI amplifies human capabilities (e.g., doctor, lawyer, developer).
High AI alone, high augmentation. AI transforms key tasks in this job — this is the priority transformation zone (e.g., accountant, data entry operator, designer).
High AI alone, low augmentation. AI can perform these tasks without providing complementary value to the worker (e.g., telemarketer, industrial sorter).
Our V5 method distinguishes two types of AI assistance and integrates human verification cost for more realistic indices.
V5 Formula
Effective_assistance = (E1 + E2 × tool_adoption) × (1 - verification_cost)Index = Elimination + (1 - Elimination) × Effective_assistanceE1 measures standalone LLM help (writing, analysis, translation). E2 measures LLM combined with external tools (code agents, RPA, CRM). Verification cost (workslop) reduces effective assistance since humans must still verify.
| Job | AI alone | Augmentation | Transformation Index |
|---|---|---|---|
| Data Entry Operator | 85% | 10% | 87% |
| Web Developer | 20% | 60% | 68% |
| Nurse | 5% | 15% | 19% |
Not all tasks in a job carry the same weight. We use two criteria to weight their impact on the overall index.
From marginal (1) to critical (5) for the job. A critical task weighs more in the final index.
From rare/annual (1) to continuous/daily (5). A frequent task impacts daily work more.
Weight calculation
Weight = Importance × FrequencyLLMs can give variable responses. To ensure index reliability, we use a multi-run approach.
We use a large language model in a frozen version to ensure the reproducibility of the indices over time.
We apply corrections based on job category to fix systematic LLM biases.
Accountant, secretary, call center agent
Engineer, lawyer, doctor
Plumber, electrician, driver
Nurse, caregiver, educator
Designer, artist, writer
Salesperson, sales rep, real estate agent
Manager, project manager, HR
Our analysis is based on the most comprehensive job reference frameworks and leading scientific studies.
French job classification (France Travail). 532 job sheets, 11,000 titles, detailed tasks.
US Department of Labor database. 1,000+ occupations with skills, tasks and work context.
European multilingual classification. Harmonization of jobs and skills at EU level.
Eloundou, T., Manning, S., Mishkin, P., & Rock, D. (2023).
GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models.
OpenAI Research. arXiv:2303.10130
openai.com/research/gpts-are-gpts →Frey, C. B., & Osborne, M. A. (2017).
The future of employment: How susceptible are jobs to computerisation?
Technological Forecasting and Social Change, 114, 254-280.
doi.org/10.1016/j.techfore.2016.08.019 →Briggs, J., & Kodnani, D. (2023).
The Potentially Large Effects of Artificial Intelligence on Economic Growth.
Goldman Sachs Global Economics Research.
goldmansachs.com →International Labour Organization (2024).
Generative AI and Jobs: A global analysis of potential effects on job quantity and quality.
ILO Working Paper 96.
ilo.org →Nedelkoska, L., & Quintini, G. (2018).
Automation, skills use and training.
OECD Social, Employment and Migration Working Papers, No. 202.
doi.org/10.1787/2e2f4eea-en →Microsoft Research (2025).
New Future of Work Report 2025.
Microsoft Research Technical Report.
microsoft.com/research →Our indices are calibrated against 42 reference jobs covering 7 categories, with targets derived from 7 leading academic studies.
Technical index: what AI CAN theoretically do
Realistic index: what IS actually happening, after country/sector adoption coefficient and regulatory friction