Sector and country matter for how AI changes work
The report compares logistics and healthcare in two European and two non-European countries and shows that impacts on work organisation and industrial relations are not the same everywhere.
Knowledge Hub
Knowledge becomes useful when it can be found, understood, verified and applied.
The Knowledge Hub brings together research, policy proposals, methodologies and learning from pilots. Every item states its audience, evidence status, version, authorship, funding and recommended use.
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How is AI changing work? How do we design a fair pilot? How can job quality be measured? How should institutions respond to questions? What supports professional transition?
Use policy
Materials may be used under the stated licence and attribution requirements. Methods include limitations and context; they should not be treated as universal recipes.
Knowledge becomes useful when it can be found, understood, verified and applied.
The benefits are real, but so are the risks to job quality
The report identifies benefits such as streamlined processes and efficiency, but also serious concerns about job quality and intrusive surveillance.
Algorithmic management is already a reality beyond platforms
The joint ILO/JRC report shows that algorithmic management is already widespread in traditional sectors such as logistics and healthcare.
Risk assessment should begin at the design stage
JRC and EU-OSHA recommend worker consultation, OSH considerations from the design stage and a holistic risk assessment.
The “always-on” culture is a systemic, not a personal, problem
The report warns that digital technologies can intensify workloads and encourage an always-on culture.
Digitalisation brings both benefits and new psychosocial risks
The joint JRC/EU-OSHA report stresses that automation and digitalisation can bring ergonomic and OSH benefits but can also reduce autonomy and increase mental-health risks.
Continuous tracking can raise stress and accident risk
EU-OSHA warns that continuous tracking and pressure to maximise productivity can lead to stress, burnout, accidents and musculoskeletal problems.
Key risks include reduced control, less autonomy and higher pressure
EU-OSHA links AIWM to lower job control and higher work intensity, which are well-known risk factors for stress.
AI-based worker management is already present across many sectors
EU-OSHA notes that these systems are used in warehousing and logistics, manufacturing, healthcare, cleaning, retail, customer service and banking.
AI-based worker-management systems collect data and make or support management decisions
EU-OSHA describes AIWM as systems that gather real-time data on the workplace, workers and tasks in order to make automated or semi-automated management decisions.
Data & methods
The data & method repository will be filled once real materials pass editorial review and receive a licence. We do not publish materials before verification.