How might AI and automation reshape the work you do?
The Future-Proof Index looks at the capabilities, structure and human contribution involved in your work. It estimates where AI may overlap with your current work, where automation may be more feasible, and where human judgement, relationships or physical-world capability remain important.
Tell us a little about your current work.
Answer based on what your current work actually involves — not what you think your role should involve. These details stay in this browser during Phase 1 testing.
Work elements most exposed to change
Human advantages to strengthen
Adaptation priorities
Suggested Maentae learning directions
These are broad learning domains/sub-domains for testing. They do not favour a specific provider or course.
Methodology, research basis & limitations
The Future-Proof Index is a Maentae-developed research-informed assessment. Its AI Exposure logic uses the nine OECD AI Capability Indicator domains and a fixed V1.0 capability baseline. The OECD indicators use five-level scales and are published in beta form so that they can evolve as AI capability changes.
Automation Potential is based on task characteristics such as repetition, rules, predictability, digital execution, standardisation and codifiability, reduced by the extent to which work depends on exceptions and judgement. Human Advantage combines direct human-dependent work with gaps between current AI capability and the complexity required by the respondent's work.
Augmentation Opportunity and Transformation Priority are Maentae-derived composite indicators. They are not probabilities, forecasts of job loss, or official OECD/ILO indices. V1.0 thresholds are provisional and should be recalibrated after testing.
OECD AI Capability Indicators
OECD AI Exposure Measure
ILO–NASK refined GenAI occupational exposure index