While much of the current debate focuses on artificial intelligence (AI) and skills, significantly less attention is paid to how skills are governed in contexts of algorithmically mediated work. Algorithmic management (AM)—the use of software, including AI, to fully or partially automate tasks traditionally carried out by human managers—has only recently gained prominence, further accelerated by the emergence of agentic AI. This ETF webinar examines how algorithmically mediated work is reshaping skills governance—from how skills are defined and measured to how they are anticipated within the platform economy and across increasingly digitalised and algorithmically mediated service sector (such as ICT, finance, and professional services).It will explore policy gaps and practical approaches to adapting VET and skills systems to increasingly data-driven labour markets in the Western Balkans and Türkiye.
Recent evidence shows that algorithmic management tools are already present across the EU, affecting approximately one quarter to one third of workers in various forms (JRC 2025). Their use is particularly pronounced in sectors such as food delivery and ride-hailing platforms, warehousing and logistics, call centres, and business process outsourcing (BPO). AM is transforming not only how work is organised, but also what counts as a skill, how it is assessed, and who controls it. Skills are increasingly datafied and operationalised through measurable indicators—such as ratings, response times, and task completion—shifting emphasis away from tacit knowledge towards quantifiable and codified performance. This intensifies standardisation, often narrows task discretion, and can contribute to deskilling by embedding decision-making into algorithmic systems.
At the same time, AM reshapes how skills are developed, signalled, and governed. Skills are continuously evaluated through ratings and automated feedback, becoming dynamic and reputational rather than anchored in formal qualifications. OECD (2025) also highlights limited employer investment in structured training under AM regimes, with learning often occurring informally through platform interfaces and trial-and-error. Control over skills increasingly shifts toward digital labour platforms and employers, weakening the role of VET systems, occupational standards, and collective bargaining in defining and certifying skills. This contributes to fragmented learning pathways and a growing disconnect between education systems and workplace requirements. Moreover, algorithmic systems can reinforce inequalities through biased ratings, opacity, and cumulative advantage dynamics—where higher-ranked workers gain more opportunities while others are filtered out. In this sense, AM does not merely measure skills—it actively reorganises skills ecosystems, redistributes power over skills governance, and shapes access to opportunities.
Key questions
This webinar shifts the focus from which skills are needed to understanding who defines them, how they are measured, and how they evolve in digitally mediated labour markets - platform economy and increasingly algorithmically mediated sector (such as ICT, finance, and professional services). As work becomes more fragmented, data-driven, and platform-based, traditional mechanisms of skills governance, anticipation, and matching face growing limitations. Understanding these shifts is critical for adapting VET systems, reskilling strategies, and emerging approaches such as micro-credentials.
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How do algorithmic systems reshape the definition, valuation, and visibility of skills?
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Who governs skills in AI-AM-mediated work (e.g. state institutions, employers, digital platforms, education and training providers, and social partners)?
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How can skills anticipation and foresight tools adapt to fragmented, project-based, and digitally mediated work?
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What are the implications for VET, reskilling strategies, and micro-credentials?
Objectives
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Examine how AM-driven systems redefine skills measurement and labour market signalling.
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Identify institutional gaps and emerging governance challenges in digital labour markets.
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Discuss implications for adapting VET, lifelong learning, and skills anticipation mechanisms.
The agenda, presentations, webinar recording and a short summary will be available on this page soon.
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