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The AI models and general-purpose digital technologies are already dramatically altering and “revolutionizing” socio-economic spheres, governance and the employment sectors in various states around the world. While mitigating the inquired AI’s social and economic risks, the rapidly shifting skill requirements are urgently needed in national education policies.
Background
During recent years, the AI adoption in the corporate sectors has accelerated rapidly, driven in part by the emergence of generative and agentic AI tools and models. Businesses increasingly use AI technologies to automate routine tasks, optimise resource allocation and improve the quality of goods and services. These developments can raise productivity and create more engaging and higher-value work for employees.
However, adoption remains uneven across firms, sectors and countries: i.e. larger firms as well as new-type innovative enterprises tend to lead in the AI uptake, while SMEs, generally, are facing certain barriers related to cost, infrastructure and skills shortages. Thus, without targeted nation-wide governance, policy and regulatory interventions these disparities are providing risks in existing productivity gaps and limiting the AI diffusion’s benefits in economy.
As the OECD research has correctly shown recently (July 2026), that “by enhancing productivity, stimulating economic growth and creating new job opportunities, AI could significantly enhance human work and the labour market”. The research has both examined the AIs projections in transforming labour markets and the governance’s policy actions (in 39 member states) through the process of harnessing the digital transformative potential.
Source and citations from: https://www.oecd.org/en/publications/skills-in-the-ai-age_972bd15e-en/full-report.html
Skills needed in digital societies
The OECD report has formulated the following “persona; requirements”:
= Foundational skills, such as basic digital literacy, numeracy and digital-scientific knowledge, etc. to enable citizens actively participating in the digital socio-economic transition.
= Information and communication technologies (ICT) skills, coped with the basics in advanced technical competencies, in order to help workers meet evolving job requirements and thrive in the digital age. Advanced AI skills (e.g. machine learning, data science) are in high demand, but workers with such skills remain rare (around 1% of the workforce).
= Complementary skills such as critical thinking, creativity, and collaboration enable high-performance work practices and a strong ability to continue learning. They become increasingly important as they enable effective interaction with AI systems and adaptation to changing tasks.
Two main research findings
First, that the AI adoption is accelerating differently across corporate sectors:
= Generally, the AI “corporate uptake” in OECD countries is rising rapidly, increasing from around 7 to 20 percent between 2021-2025, driven in part by the diffusion of generative AI tools.
= Larger firms and start-ups are more likely to adopt AI due to greater financial resources and innovation capacity, respectively.
= SMEs face persistent barriers to AI uptake, including costs, lack of infrastructure, computing facilities, data and shortages of skilled workers.
= However, among the top barriers are the skills shortages that represent basic constraints in the AI adaptation processes at the corporate level.
Secondly, the AI is transforming jobs, but not necessarily destroying them, thus:
= The AI models are affecting the labour markets through three main channels: a) automation of existing tasks, b) creation of new tasks and occupations, and c) improving productivity. These effects often coexist; but -in perspective, the net impact on employment will depend on these “channels” relative balance.
= Evidences suggest that the AI often complements rather than substitutes human labour, contributing to productivity gains and job creation.
= However, job displacement remains a risk, particularly for workers in routine and repetitive roles.
Education governance in shaping AI skills
To make the most of benefits from AI technologies while mitigating the risks, governments must put into action agile policies that facilitate “collective implementation” of the following factors and aspects:
= Strengthening education and training systems by improving quality, equity and labour market relevance of education and integrating AI literacy, digital skills and critical thinking across curricula;
= Expanding the lifelong learning opportunities by promoting continuous upskilling and reskilling across the life course by developing flexible, modular and online training pathways and strengthening recognition of prior learning systems;
= Developing the ICT and AI talent’s pipeline by expanding formal education programs in AI and digital fields, providing short, targeted reskilling programs for adults and aligning training provision with evolving labour market needs;
= Promoting the AI literacy for all by equipping workers with basic skills to use, understand and critically assess AI, and broadening access to AI learning beyond all employment sectors;
= Encouraging employer-led training by supporting firms through financial incentives, subsidies and co-financing schemes, fostering partnerships between employers and education providers and aligning workplace training with technological change; and
= Strengthening policy co‑ordination and partnerships by fostering collaboration between governments, digital industry and education systems, and using labour market data and skills forecasting to guide policy.
Among some AI challenges are the job displacement issues, which require a properly managed governance-regulatory approach. Although the effects of AI on employment differ across sectors, states, regions and cities, as well as across skill levels, the adaptation process could require universally recognised shifts in the process of developing new skills that aligning with evolving labour market demands. Quite naturally, the national governance and decision-makers in education policies play vital role in ensuring that the labor market is “equipped” with the necessary skills to complement the seriously altering and AI-driven economies.
The EU’s approach in skills
The European Union approaches skills development primarily through the Union of Skills program, which represents a strategic framework launched in March 2025 to tackle labor shortages and boost economic competitiveness.
Core pillars of this approach are the following elements:
= Foundational education: it focuses on strengthening basic literacy, numeracy, digital literacy, science and citizenship skills from early childhood through adult learning via the Action Plan on Basic Skills.
= Upskilling and reskilling: it promotes lifelong learning and continuous training to help the workforce adapt to the green and digital economic transitions.
= Talent mobility: it facilitates the free flow of learners and workers across borders using programs like Erasmus+ (backed by nearly €28 billion) and the European Social Fund Plus (ESF+ with over €142 billion for 2021–2027).
= Global talent attraction: this element aims to attract non-EU states’ talent through initiatives like an EU talent pool and targeted visa strategies for skilled workers, top students and researchers.
More in: https://commission.europa.eu/topics/competitiveness/union-skills_en
The European “Union of Skills” represents both a continuation and evolution of previous EU strategies, while also introducing new, increasingly concentrated governance structures. These may further entrench the link between education and macroeconomic goals and push national policies toward convergence under a common European trajectory. Against this backdrop, the key question remains whether this policy framework can be re-signified in ways that go beyond competitiveness to genuinely promote democratic well-being, social cohesion, and personal self-actualization.
Source: Lintzeris, P., & Valassi, D. (2025). The EU Communication ’Union of Skills’: A further step toward embedding skills policies within a competitiveness-oriented economic rationality. Adult Education Critical Issues, 5(1), 7–22. https://doi.org/10.12681/haea.41618
Conclusion
An imperative element in ensuring that the digital technology’s progress shall be a proper understanding of the ways that strengthen the AIs is affecting economic systems and the social and corporate foundations.
Amid the rapidly evolving digital and AI systems, the digital skills development is both an economic and a societal imperative essential to promoting social engagement, civic participation and mutual trust in an age of uncertainty. Individuals need a combination of foundational skills, ICT proficiency and different complementary skills (such as critical thinking and creativity) to prosper in the AI age. In this respect, lifelong learning and the willingness to be adaptable become the main elements that tie innovation and social resilience. To make these capabilities widespread, education systems and employers must prioritise both upskilling and reskilling as a shared responsibility on a continuous basis.
At the same time, the reforming education policies also play decisive roles in steering digital transformation towards growth and well-being. Governments and public institutions should be agile, in anticipating: e.g. changes by creating frameworks that promote the relevance of skills to labour market needs, supporting upskilling and reskilling programs, and offering relevant training opportunities for all. By aligning skills strategies with forward-looking education and digital policies, societies can shape a future where technology amplifies human capabilities. The challenge ahead is to keep pace with AI while guiding its development towards prosperity, resilience and human-centred innovation.
General reference and citation: OECD. 2026. “Skills in the AI age”. OECD Artificial Intelligence Papers, No. 60, OECD Publishing, Paris, https://doi.org/10.1787/972bd15e-en.