Advanced robotics, artificial intelligence and the automation of tasks: definitions, uses, policies and strategies and Occupational Safety and Health
This report by the European Agency for Safety and Health at Work (EU-OSHA) sets the scene for its four-year research programme on digitalisation, examining types and definitions of AI-based systems and advanced robotics for task automation. It maps current and potential uses across cognitive and physical task domains, reviews sectoral distributions, and provides an overview of relevant EU and national policies, strategies, programmes, gaps, and needs in relation to occupational safety and health (OSH).
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
This report is for policy-makers, researchers, occupational safety and health professionals, and workplace stakeholders seeking a comprehensive mapping of the intersection between digitalisation, task automation, and worker safety.
What the document contains
The report covers definitions and taxonomies for AI-based systems and advanced robotics, maps their current and potential uses across cognitive and physical tasks, analyzes sectoral distributions, and provides an overview of relevant EU and national regulations, policies, strategies, initiatives, and OSH gaps and needs.
The document does not provide a legally binding regulatory text or an enforceable code of practice, focusing instead on a research-oriented overview of definitions, uses, and existing policy landscapes.
- Task automation affects specific functional tasks within broader jobs rather than entirely replacing whole jobs.
- AI-based systems for cognitive tasks and advanced robotics for physical tasks introduce new physical, psychosocial, and organizational OSH challenges.
- Routine, highly codifiable tasks are currently the most vulnerable to displacement by automation technologies.
- European and national policy frameworks increasingly emphasize a human-centric approach, transparency, accountability, and the 'human-in-control' principle.
- There is a notable gap between high-level regulatory frameworks and practical workplace implementation, alongside a need for specialized training for labour inspectors.
· 1 Introduction and objectives · 2 Methodology · 3 Types and definitions of AI-based systems for the automation of tasks · 4 Mapping of current and potential uses · 5 Overview of policies and strategies · 6 Summary and Conclusion · 7 References · 8 ANNEX
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
3/5Clear responsibility for AI outcomes
Mechanisms should be put in place to ensure responsibility and accountability for AI systems and their outcomes.
5.1.2 Strategies, programmes, initiatives and campaigns
screening score · 2026-10-25
Fairness
3/5Non-discrimination and equitable treatment
AI systems should be designed in a way that respects the rule of law, human rights, democratic values and diversity
5.1.2 Strategies, programmes, initiatives and campaigns
screening score · 2026-10-25
Transparency
4/5Openness about how AI systems work and are used
The principle that finds the highest agreement is system transparency, which is addressed in nearly every initiative
5.1 European level
screening score · 2026-10-25
Enforcement
3/5Consequences and compliance mechanisms with real force
Within Europe there are currently two main pieces of legislation that apply to technology and workplaces and therefore also build the legislative basis for AI-based systems and advanced robotics for the automation of tasks.
5.1.1 Regulation
screening score · 2026-10-25