This report shows that, despite well-established support systems in place, many Minimum Income Scheme (MIS) beneficiaries in Belgium and Greece continue to face substantial barriers to finding stable employment and progressing in their careers. Investing in AI-enhanced job and career recommendation tools that consider the needs of MIS beneficiaries could help connect them to better jobs and careers.
Both Belgium and Greece have made important digitalisation investments in recent years, including by embracing AI. However, existing tools are often designed for broader populations and provide basic job matching functionalities, limiting their ability to address the specific characteristics, needs, and barriers faced by those with weaker labour market prospects. At the same time, international experience demonstrates the growing potential of digital and AI-powered tools to support more effective and personalised labour market services. Such tools can improve matching between jobseekers and vacancies, support career guidance, strengthen service co‑ordination, and help identify opportunities for training and other active labour market policies (ALMPs).
This report proposes concepts for the development of comprehensive AI-enhanced solutions to support the job matching and career progression of MIS beneficiaries in Belgium and Greece. The proposed solutions are intended to guide and complement existing employment and social support services. They can be used by job counsellors, social workers, and beneficiaries themselves to support job search, identify support needs, guide career development and recommend ALMPs. By facilitating more effective job matching and more informed career decisions, these tools have the potential not only to shorten unemployment spells but also to promote more sustainable and higher quality employment and, therefore, strengthen social inclusion.
The proposed concepts for new digital solutions presented in this report draw on the analysis of rich linked administrative data. In Belgium, the analysis relied on tailored aggregate data provided through the Crossroads Bank for Social Security. In Greece, multiple administrative datasets were linked at the individual level, providing a unique evidence base on the employment trajectories of MIS beneficiaries. While some elements of the proposed concepts are relevant and applicable across both countries, strategic options regarding the design and implementation of such solutions are tailored to each country’s institutional framework, including Belgium’s decentralised governance structure and distribution of responsibilities across levels of government.
The lessons from this report extend beyond these two countries. As governments across OECD countries increasingly explore and embrace the potential of digitalisation and AI in employment services, this report offers practical insights on designing and implementing comprehensive job and career recommendation platforms, while managing associated risks. The report also guides how to embed these tools within service delivery and operational processes to better support those further from the labour market in accessing good and sustainable jobs.
Four key takeaways emerge that are particularly relevant for the development of digital and AI-enhanced job and career recommendation tools in Belgium and Greece:
Strengthen data linkage, interoperability and quality to support integrated digital and AI-enabled employment services. Both Belgium and Greece have a strong data foundation and hold rich information on MIS beneficiaries and vacancies. However, these data are often fragmented across institutions, collected for administrative rather than analytical purposes, or not coded consistently enough, thereby limiting their ability to support the full range of functionalities envisaged for advanced AI-enabled job-matching and career recommendation tools.
Design labour market tools to support career progression, not only job placements. While many MIS beneficiaries succeed in entering employment, they mostly access unstable, low-paid, part-time, and lower-entry service occupations, with limited prospects for advancement. Digital tools can help address this challenge by identifying opportunities not only to enter employment, but also to progress towards better-quality and more sustainable jobs.
Enable job matching and career recommendation tools to fully consider individual circumstances and local labour market realities. MIS beneficiaries differ considerably in their skills, employment histories, and barriers to work while labour demand also varies across sectors and regions. To provide meaningful support, digital tools should integrate information on individual profiles, vacancies, training opportunities, employment barriers, and regional labour market needs. This would allow both counsellors and beneficiaries themselves to identify realistic job options and explore pathways for upskilling, reskilling and career progression. This is even more prominent in the case of Belgium, where identifying opportunities beyond regional borders can be particularly challenging.
Introduce AI-powered tools as part of a broader support system and governance. The effectiveness of these digital tools will be higher if accompanied by strong governance, co‑ordination across institutions, staff training, user-centred design, and safeguards for risk management. Addressing data governance and responsibility, ensuring compliance with the EU AI Act, and managing disparities in data quality and digital maturity among institutions involved in delivering employment and social services are critical success factors. AI tools should support rather than replace human judgement and be deployed gradually, starting with core functionalities and expanding over time, based on user feedback and implementation experience. Continuous monitoring and evaluation are also key to finetune tool design, improve performance, and ensure that AI-powered solutions deliver meaningful benefits for users. At the same time, complementary policy actions are needed to maximise the impact of such tools, including stronger institutional co‑ordination, continuous access to training, ALMPs, and social services, and the availability of quality employment opportunities, as technology alone cannot overcome all the labour market barriers faced by many MIS beneficiaries.