Skills Policy for the Modern Workforce

📘 New OECD - OCDE Report: “How Workers Use, or Don’t Use, Their Skills in the Workplace” https://lnkd.in/eDtV5zYC The OECD’s latest analysis examines a critical but often overlooked question: Are workers actually using the skills they have? It is highly relevant for VET and workforce development — because skills shortages are not only about supply. They are also about how skills are deployed, recognised and valued at work. Here are the key takeaways👇 🔎 The Core Narrative: It’s Not Just a Skills Gap — It’s a Skills Use Gap • Many workers possess skills that are underused in their jobs • Overqualification and skills mismatch remain widespread • Low skill use reduces productivity, wages and job satisfaction • Improving skills use can deliver gains without training a single additional person 📊 Theme 1: Skills Mismatch Is Structural • Significant shares of workers are overqualified for their roles • Field-of-study mismatch remains persistent across countries • Cognitive and digital skills are often underutilised • Mismatch is linked to lower earnings and weaker career progression 👉 VET must not only train for employment — but train for meaningful skill deployment. 🏢 Theme 2: Workplace Practices Matter • High-performance work practices increase skill use • Autonomy, teamwork, problem-solving and continuous learning are key • Firms that invest in better work organisation achieve higher productivity This reinforces something we often underestimate in policy debates: 🎯 Skills policy and workplace innovation policy must go hand in hand. 💼 Theme 3: Management Quality Is a Skills Multiplier • Good management significantly improves skill utilisation • Poor management traps talent in routine, low-value tasks • Leadership and organisational culture determine whether skills flourish 👉 Successful ecosystems are those that connect VET providers with companies that actively innovate in work organisation, not only technology. ⚖️ Theme 4: Inequalities in Skills Use • Women, migrants and older workers are more likely to experience underutilisation • Low-skilled workers face fewer opportunities to use and develop skills • Inclusive workplaces are more likely to unlock human potential This confirms something fundamental: ✨ Inclusivity is not only a social objective — it is an economic efficiency strategy. 🚀 Why This Matters for VET & Skills Policy: • Investing in training alone is insufficient • We must align VET with workplace practices and employer strategies • Apprenticeships and work-based learning should expose learners to high-quality work environments • CoVE partnerships can promote innovation in both training and work organisation 👉 The future of VET is not just about producing skills: It is about ensuring those skills are fully used. 👉 If we ignore skills underutilisation, we undermine productivity, innovation and human dignity. EU Employment and Skills

Louder for the people at the back 🎤 Many organisations today seem to have shifted from being institutions that develop great talent to those that primarily seek ready-made talent. This trend overlooks the immense value of individuals who, despite lacking experience, possess a great attitude, commitment, and a team-oriented mindset. These qualities often outweigh the drawbacks of hiring experienced individuals with a fixed and toxic mindset. The best organisations attract talent with their best years ahead of them, focusing on potential rather than past achievements. Let’s be clear this is more about mindset and willingness to learn and unlearn as apposed to age. To realise the incredible potential return, organisations must commit to creating an environment where continuous development is possible. This requires a multi-faceted approach: 1. Robust Training Programmes: Employers should invest in comprehensive training programmes that equip employees with the necessary skills for their roles. This includes on-the-job training, mentorship programmes, online courses, and workshops. 2. Redefining Hiring Criteria: Organisations should revise their hiring criteria to focus more on candidates’ potential and willingness to learn rather than solely on prior experience or formal qualifications. Behavioural interviews, aptitude tests, and probationary periods can help assess a candidate's ability to learn and adapt. 3. Partnerships with Educational Institutions: Companies can collaborate with educational institutions to design curricula that align with industry needs. Apprenticeship programmes, internships, and cooperative education can bridge the gap between academic learning and practical job skills. 4. Lifelong Learning Culture: Encouraging a culture of lifelong learning within organisations is crucial. Employers should provide ongoing education opportunities and support for professional development. This includes continuous skills assessment and access to resources for upskilling and reskilling. 5. Inclusive Recruitment Practices: Employers should implement inclusive recruitment practices that remove biases and barriers. Blind recruitment, diversity quotas, and targeted outreach programmes can help ensure that diverse candidates are given a fair chance. By implementing these measures, organisations can develop a workforce that is adaptable, innovative, and resilient, ensuring sustainable success and growth.

Have you seen the newly released U.S. Department of Labor AI framework for workforce development? In my latest article, I took a moment to break the new policy down into bite-sized points and included source links to save you some time. It's easy to overlook federal AI guidance, especially when the pace of AI innovation surpasses the pace of general AI understanding. But if you care about workforce modernization, artificial intelligence policy, or long-term business growth, this one deserves your attention. Last week, the U.S. Department of Labor issued Training and Employment Guidance Notice 07-25 outlining how AI should be integrated into federally funded workforce systems. This is not a theoretical conversation anymore. The World Economic Forum reports that 44 percent of core job skills are expected to change within five years. McKinsey & Company’s 2025 State of AI survey shows that 65 percent of organizations are already using generative AI in at least one function. When employer operations shift, workforce systems must follow. Here is what this federal AI framework signals for leaders: 🔹 Workforce modernization is moving from digitization to intelligence. Labor market analysis, job matching, and service delivery are expected to integrate AI with oversight. 🔹 Governance is not optional. Transparency, documentation, and compliance are embedded in the guidance. 🔹 Public and private sectors are converging. Agencies will look for partners who understand both AI capability and regulatory expectations. If you operate in education, workforce development, HR tech, national economic strategy, or business growth and modernization, this affects you. The most strategic leaders I know do not wait for headlines to force adjustment. They study policy signals early and position accordingly. How is your organization preparing for AI integration inside public workforce systems? If this perspective is useful, let's connect ~Dr. Kiesha King and subscribe to my newsletter for more on education strategy, AI workforce modernization, leadership and sustainable business growth. Disclaimer: All views are my own and do not represent the views of my employer or any affiliated organization.

America’s talent shortage is one of our most urgent national security challenges. A new report from JPMorganChase’s PolicyCenter points to a sobering reality: the U.S. simply does not have enough skilled workers to build, compete, or protect its economic and strategic interests. Critical sectors are feeling the strain. 75% employers report difficulty finding qualified talent, 40% of adults lack basic digital skills, and manufacturing alone may need 3.8 million workers by 2033 with nearly half of those jobs projected to go unfilled. Technology roles are expected to grow at twice the rate of the rest of the labor market, and energy apprenticeships must expand significantly to meet future demand. JPMorganChase’s Security and Resiliency Initiative is investing $1.5 trillion dollars to strengthen strategic industries. But the report is clear: capital cannot deliver results without a strong talent pipeline. Workforce must be treated as core infrastructure. The report highlights several polices to strengthen the talent pipelne: ✅ Scale high quality apprenticeships to expand pathways into advanced manufacturing, energy, AI, and cybersecurity. ✅ Increase employer based training through reforms to WIOA that allow more investment in upskilling and on the job training. ✅ Strengthen industry and sector partnerships that align employers, education providers, and community organizations around shared workforce needs. ✅ Expand public private partnerships so education and training programs stay closely connected to in demand careers. ✅ Accelerate digital skill development by updating federal definitions of basic skills and expanding access to digital literacy programs. ✅ Implement Workforce Pell effectively by aligning federal regulations with state workforce systems, supporting classroom instruction connected to apprenticeships, and ensuring states use data to approve only high quality short term training programs aligned to critical industries. Last week's release of the National Security Strategy and the Administration’s AI Action Plan both make clear that America’s strategic advantage will hinge on our ability to innovate, deploy, and secure critical technologies like AI and quantum computing. But none of these ambitions can be realized without a workforce equipped with the skills to build, operate, and secure these technologies. Closing the talent gap isn’t just an economic imperative; it is foundational to sustaining our technological edge, economic resilience, and national security https://lnkd.in/gsa45XxV

Delighted to see my report on rethinking workforce capacity development for our era of artificial intelligence and platform work published by The Brookings Institution. It discusses four key themes: - Why embedding skilling in the right scaffolding is essential for successful #genAI occupational transitions; - How to overcome barriers of geography in capacity planning, and what we can learn from our policy failures during prior automation waves; - Why mitigating income volatility is critical as the growth of freelance, platform and other forms of independent work accelerates, and - How to fund the social safety net of the 21st century and why it should be decoupled from the "employment" work arrangement. I also summarize some #futureofwork policy actions that I believe would be most helpful. I'd welcome your feedback and comments! https://lnkd.in/eqbx6W6Q

There is a structural shift happening in American workforce development right now and most people are not paying attention how the small changes are adding up to something big. This month, the U.S. Department of Labor announced a $243M initiative to integrate AI literacy into Registered Apprenticeship programs across every major industry sector. Days later, DOL and the National Science Foundation formalized a partnership to build 56 state and territory AI readiness hubs — up to $224M — designed to connect workforce training systems, community colleges, and regional employers under one strategy. See what they did there? Next, as of July 1st 2026 Workforce Pell Grants become real: for the first time, need-based federal Pell funding will cover short-term, employer-aligned training programs — as little as eight weeks — at accredited institutions. Taken together, these moves represent a meaningful reorientation of how the U.S. funds and delivers skills-based education. This is not headline news; it is plumbing. But the plumbing is what determines whether the water gets to the people who need it. I believe higher education and workforce development are not separate systems — they are overlapping ones. When federal policy starts treating them as one, it creates real opportunities for institutions and organizations willing to move toward the policy rather than wait for it to arrive on their desk. We have been in the background making moves knowing that this is coming. Watch this space. #WorkforceDevelopment #HigherEducation #SkillsGap

From Degrees to Competences:  Human-Centred Skills Policies for an AI-Transformed Labour Market The OECD - OCDE Skills Outlook 2025 shows that countries are entering a decade where shocks, megatrends and rapid digital innovation are reshaping skills needs faster than education and labour-market systems can adapt, risking deeper divides between those who can keep up and those who cannot. It documents how socio-economic background, gender, migrant status and where people grow up still strongly shape who acquires core 21st-century skills. While digital transformation accelerates changes an increasing demand for higher-order cognitive, social and digital skills are exposing adults with lower qualifications to greater risk of displacement and low-quality jobs. 1. Build Agile, Data-Driven Skills Governance 🧭 Develop real-time, inclusive skills intelligence systems that continuously adjust funding, regulation and programmes to labour-market demand. 2. Invest Early in Inclusive, High-Quality Education 🎒 Guarantee access to high-quality education to secure strong literacy, numeracy, digital and social-emotional foundations and break the link between background and skills. 3. Make Lifelong Learning a Right for Those Who Need It Most 🔄 Reorient adult learning systems so that flexible, modular and digitally enabled training, backed by financial support and recognition of outcomes, is most generous for low-qualified workers. 4. Align Digital Transformation with Inclusion Targets 💻🤝 Couple investments in AI, broadband and automation and incentives for technologies that complement workers, improve job quality and open tech pathways for under-represented groups. 5. Promote Skills-First Labour Markets and Strong Career Guidance 🧩 Progression toward demonstrable skills through skills taxonomies, recognition of prior learning and micro-credentials. AI-Driven (and divided) Societies: Artificial intelligence is reshaping the workforce and society by changing which tasks are automated, which are augmented and which become newly valuable. Rising demand for complex problem-solving, management & communication. Decline in routine clerical and some cognitive tasks. Rather than requiring everyone to become AI engineers, most workers will need to work effectively with AI tools, and reinforced social and emotional skills—like collaboration, ethics and adaptability—that machines cannot easily replicate. At the same time, AI risks widening inequalities if low-qualified workers, smaller firms or marginalised regions lack access to upskilling opportunities. AI can also help organisations, including SMEs, to compensate for skill gaps and labour shortages and boost productivity, but it also increases the premium on continuous learning. 🤖📚 Source: OECD. (2025). OECD Skills Outlook 2025: Building the skills of the 21st century for all. OECD Publishing. https://lnkd.in/empf7P7B

Expanding the U.S. workforce in emerging technology is a pressing challenge. How can we build new talent pipelines for critical industries like biotechnology and AI? CSET’s recent report, "Biotech Manufacturing Apprenticeships: A Case Study in Workforce Innovation," by Luke Koslosky, Steph Batalis, and Veronica Jade Kinoshita, explores a promising solution. By examining the North Carolina Life Sciences Apprenticeship Consortium (NCLSAC), the report offers a practical guide for organizations looking to develop their own programs. A few policy takeaways from the report that caught my eye included: 1️⃣ Provide sustainable funding for the infrastructure that apprenticeship programs rely on, such as regional workforce hubs, technical education programs, and pre-apprenticeship training. 2️⃣ Support regular, regional labor market studies and ensure timely access to data on skills gaps and hiring needs to help target training efforts effectively. 3️⃣ Increase federal and state funding for the startup and long-term costs of apprenticeship programs, including support services for apprentices like stipends and child care — flexible funding is helpful! 4️⃣ Support recruitment initiatives that build awareness and reduce barriers to entry, especially for engaging new and historically underserved communities in the industry. 5️⃣ Create or strengthen regional groups that bring together employers, education providers, and government partners to align their efforts and goals. For organizations in any emerging tech field considering this model, our new report provides guiding questions to start the process: ❓What are your current workforce gaps in terms of roles and numbers, and what specific skills are most in demand? ❓What type of apprenticeship model—employer-sponsored, an intermediary partnership, or a consortium—best suits your organization's needs and resources? Learn more and see how this model could apply to your industry: ➡️ Read the full report: https://lnkd.in/ekcTD7GY ➡️ For industry & workforce developers, see our guiding questions: https://lnkd.in/e3rAhtQV ➡️ For policymakers, check out the "Policy Takeaways": https://lnkd.in/eiNx2qfD

How can today's workforce adapt to the rapid pace of automation and technological change? The workplace is transforming faster than ever before, driven by advances like data analytics, artificial intelligence, and automation. While some jobs may be at risk, workers willing to continuously gain new skills can thrive in emerging roles. Critical Considerations • Automation will transform tasks but not fully eliminate human roles. Work will require new skills. • Retraining could add $6.5 trillion to global GDP by closing skills gaps. But it requires long-term investments. • A majority of workers are willing to learn amid industry disruptions, but a minority of organizations connect reskilling and upskilling to strategy. • Technical skills like data analytics will be in high demand across industries. Data literacy and data-informed decision-making is becoming essential. • Organizations need to implement responsible AI ethics frameworks and foster cultures of lifelong learning. To navigate this era of change, stakeholders should focus on: Workers • Seek training in digital skills like data literacy and analytics. • Stay adaptable and open to retraining. • Advocate for company programs to support continuous learning. Organizations • Align training initiatives with business strategy. • Reskill at-risk workers proactively. • Implement ethical AI frameworks and data governance. Educators • Integrate hands-on data skills into both technical and non-technical programs. • Foster lifelong learning capabilities in students. Policymakers • Fund digital training and infrastructure. • Provide incentives for employer-supported upskilling. • Enact AI accountability and data privacy laws. #FutureOfWork #DataLiteracy #DigitalTransformation #SkillsOfTheFuture #LifelongLearning https://lnkd.in/evp3vAxv

The most important skills today and in the next years will be human capabilities: critical and analytic thinking, resilience, leadership and influence, overlaid with technological literacy and AI skills to amplify these human capacities. World Economic Forum's new Future of Jobs Report provides a deep and broad analysis of the drivers of labour market transformation, the outlook for jobs and skills, and workforce strategies across industries and nations. It's a really worthwhile deep dive if you're interested in the topic (link in comments). Here are some of the highlights from the Skills section, which to my mind is at the heart of it. 🧠 Analytical Thinking Leads Core Skills. Skills like analytical thinking (70%), resilience (66%), and creative thinking (64%) top the list of core abilities for 2025. By 2030, the emphasis shifts even more towards AI and big data proficiency (85%), technological literacy (76%), and curiosity-driven lifelong learning (79%). This shift underscores the critical role of technology and adaptability in future workplaces. 📉 Skill Stability Declines but at a Slower Rate. Employers predict that 39% of workers' core skills will change by 2030, slightly lower than 44% in 2023. This reflects a stabilization in the pace of skill disruption due to increased emphasis on upskilling and reskilling programs. Half of the workforce now engages in training as part of long-term learning strategies compared to 41% in 2023, showcasing the growing adaptation to technological changes . 🌍 Economic Disparities in Skill Disruption. Middle-income economies anticipate higher skill disruption compared to high-income ones. This disparity highlights the uneven challenges of transitioning labor forces across global regions, particularly in economies still grappling with structural changes. 🚀 Tech-Savvy Skills in High Demand. The adoption of frontier technologies, including generative AI and machine learning, is increasing the demand for skills like big data analysis, cybersecurity, and technological literacy. These trends indicate that businesses are aligning workforce strategies to integrate these advancements effectively. 📚 Upskilling Is the Norm, Not the Exception. By 2030, 73% of organizations aim to prioritize workforce upskilling as a response to ongoing disruptions. This reflects a shift in corporate investment priorities towards human capital enhancement to maintain competitiveness.