ILO Working Paper 140 (2025): Generative AI and Jobs: A Refined Global Index of Occupational Exposure
Task-level occupational exposure framework for generative AI, built from expert input and model predictions.
OPEN SOURCE ↗Manual therapies (massage, acupuncture, reflexology) are physical interventions on a human body. They cannot be automated. Demand for complementary therapy is growing.
Manual complementary therapists — massage therapists, acupuncturists, reflexologists, aromatherapists — provide physical therapeutic interventions on the human body. The entire value proposition is physical human touch applied with therapeutic intent.
No technology exists that can replicate skilled therapeutic touch. Massage robots exist as prototype novelties; they cannot assess the specific tensions, restrictions, and responses of an individual client's body in real time and adapt accordingly.
Complementary therapy is not just about the physical intervention — the therapeutic relationship, the restful environment, and the human presence are integral to the experience. Growing wellness culture, stress-related health problems, and consumer spending on self-care are all driving demand for complementary therapists.
These are the genuine threats to this profession. They are real, but they are not sufficient to overturn the fundamental analysis. Here is why.
Put the case that Alternative Therapist (Acupuncture, Massage Therapy) will not survive AI displacement. The system responds with counterarguments from the research base. Strong arguments shift the score — up to a maximum of ±15 points. The system is not an AI. It is a structured argument engine.
This question layer is generated from the job verdict, the resistance case, the regional rollout logic, and the evidence status of this page. Use the filters to focus the discussion, or trigger a random question and work through the role from multiple angles.
Replace broad inference with occupation-specific literature, regulators, labour statistics, or professional-body evidence before publication-grade use.
TIER 1 review queue with 6 core sources and 1 framework signals.
This page is grounded in task exposure research and labour-market trend reports, then translated into a reasoned occupation-level argument.
This site now treats exact timelines, total job-loss counts, and regional speed as interpretive estimates unless a cited source states them directly. The argument on this page should be read as a structured forecast, not a guaranteed future.
These impact figures are site estimates for comparison and should not be read as official labour-market counts.
Task-level occupational exposure framework for generative AI, built from expert input and model predictions.
OPEN SOURCE ↗Finds clerical work is the most highly exposed occupational group and that augmentation is often more likely than full occupation automation.
OPEN SOURCE ↗Shows AI exposure is highest in many white-collar cognitive occupations, while manual occupations tend to have lower exposure.
OPEN SOURCE ↗Advanced economies are more exposed to AI because they have more cognitive-intensive jobs; infrastructure and skills limit adoption elsewhere.
OPEN SOURCE ↗Large-employer survey showing clerical roles among the fastest-declining and care, education, software and green-transition jobs among growth areas.
OPEN SOURCE ↗Argues advanced economies are better positioned to benefit from AI due to infrastructure, skills, and institutions.
OPEN SOURCE ↗