European Vision for Optimising Learning, Validation and Employment: AI-Driven Skills Intelligence and Micro-credentials for European Manufacturing.

EVOLVE is a 36-month MSCA Staff Exchanges action that builds a cross-border, GDPR-compliant skills intelligence system for European manufacturing, using the textile and clothing sector as its pilot environment. Nine organisations from higher education, public authorities, industry and civil society exchange staff across sectors and borders to map current skills gaps, forecast future qualification shortages through machine learning, and convert those forecasts into modular micro-credentials. Recognition of Prior Learning (RPL) and Validation of Non-Formal and Informal Learning (VNFIL) are embedded directly in the forecasting logic, so that competences acquired outside formal education become visible in workforce planning rather than absent from it.

The challenge
Digitalisation, the green transition and demographic change are reshaping European labour markets, and demand for advanced technical, digital and green competences in manufacturing is accelerating faster than education and training systems can respond. SMEs and higher education institutions are expected to align workforce capabilities with shifting requirements, yet the evidence available to them remains fragmented. Skills data infrastructures are largely national, rarely interoperable, and mostly descriptive and retrospective rather than predictive. Existing instruments record formal qualifications while overlooking non-formal and informal learning. The textile and clothing industry illustrates the consequences: large enterprises continue to relocate production and investment to Asia and Africa, while the competences of the remaining European workforce, a significant part of it female, migrant or without formal certification, are neither systematically documented nor formally recognised.

What the project does
EVOLVE delivers its research and innovation programme through secondments rather than alongside them: data scientists are hosted by public authorities and SMEs, education specialists are embedded in industrial settings, and policy specialists are seconded to universities, with structured reintegration ensuring that new methods are absorbed by the sending organisations. The work advances in four connected stages. First, a harmonised methodology and GDPR-compliant data governance framework enable comparative analysis of skills supply and demand, with primary data collected in Poland, Austria, Malta and Scotland and secondary datasets integrated from six countries. Second, an AI forecasting engine is co-developed to predict medium- and long-term skill and qualification needs, built to EU requirements for trustworthy AI and equipped with explainable outputs and stakeholder dashboards. Third, forecasting outputs are translated into micro-credentials co-designed with textile SMEs, VET providers and qualifications authorities, mapped to occupational profiles at MQF Levels 4 to 6 and piloted in real workplace conditions with RPL and VNFIL validation. Fourth, the evidence generated is consolidated into EU-level policy recommendations and a sustainability model for long-term adoption of the tool and the credentialing system.

What the project will deliver
EVOLVE will produce a Harmonised Skills Data Model and Protocols and a Comparative Report on Current Skills Gaps; an AI Skills Forecasting Engine with an integrated online platform, interactive dashboards for policymakers, HEIs and SMEs, and a dedicated VNFIL/RPL Compatibility Module; a Micro-credential Design Framework for the textile sector and a VNFIL-Based Skills Validation Toolkit for textile workers; Guidelines for Sector-Specific Micro-credential Scaling; and EU-level policy briefs on skills forecasting, validation of learning and micro-credentials, together with a Sustainability and Exploitation Plan. Targets include integrated datasets from at least six countries, a validated forecasting model tested across three countries, at least two co-developed micro-credential modules, and pilot delivery involving at least 30 learners and employees in two countries.

The partnership
EVOLVE brings together nine organisations from six countries, coordinated by the Malta Further and Higher Education Authority (MFHEA): the University of Malta (Malta), C.I.P. Citizens in Power (Cyprus), BOKU University (Austria), Haaga-Helia University of Applied Sciences (Finland), the University of Agriculture in Krakow (Poland), the Scottish Credit and Qualifications Framework Partnership (Scotland, United Kingdom). The consortium combines national qualifications authorities, AI and labour market research capacity, applied policy and curriculum expertise, civil society outreach, and two textile enterprises of contrasting scale providing authentic pilot environments.

CIP’s role
Citizens in Power leads the project’s dissemination and communication strategy, coordinating events, webinars, newsletters, publications and the final conference, and contributes to the ethical and data governance framework underpinning all data activities. In the research work, CIP leads the compilation of EU-comparable datasets on skills, occupations and qualifications and the resulting Key Sector Insights Report, and safeguards data integrity across national classification systems. CIP reviews the assumptions and outputs of the AI model for societal relevance, ensuring that non-formal learning pathways are represented and that predictions are communicated in accessible formats. In the micro-credential pilots, CIP contributes competency-based learning expertise, supports learner engagement and guidance in RPL and VNFIL validation, and collects feedback from learners and supervisors. Across the policy work, CIP ensures alignment with national qualifications frameworks and sectoral priorities, and mobilises its lifelong-learning networks and accredited training centre to widen the reach of results.

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Funded by the European Union under Grant Agreement No. 101299970 [TO VERIFY]. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the granting authority (REA – European Research Executive Agency) [TO VERIFY]. Neither the European Union nor the granting authority can be held responsible for them.