Despite historic investments in workforce development, America’s talent marketplace remains deeply fragmented – employers can’t find the skilled workers they need, while millions of workers remain underemployed or left out of opportunity altogether.

During a NationSwell roundtable on February 10, leaders from business, philanthropy, education, and policy came together to explore how we can better align the disparate pieces of the workforce ecosystem. Below are a few of the models that surfaced that are bridging the gap between training supply and employer demand, and driving real results for workers, businesses, and communities alike.

Key Takeaways:

Design workforce strategies for non-linear career journeys. Real-world careers rarely follow a straight path from education to employment. Adults cycle through transitions – career changes, skill updates, pauses, and reinvention. Yet, many workforce systems remain built on linear assumptions (train → place → exit) and risk excluding the learners they aim to serve.

The opportunity:

  • Design pathways that anticipate re-entry and reinvention
  • Normalize career cycling
  • Build systems that assume movement, not permanence

Extend support beyond initial job placement to enable sustained economic mobility. Entry into a role is only one milestone. Workers often stall after landing their first opportunity. The true test of alignment isn’t placement – it’s progression. Continued upskilling, advancement pathways, and alumni engagement are important to achieving long-term economic mobility. We need to be asking if workers are building durable mobility over time.

Sustained mobility requires:

  • Continued upskilling
  • Advancement pathways
  • Alumni engagement
  • Financial capability support
  • Clear progression toward a thriving wage (not just a living wage)

Close the communication gap between skills and courses. There is a fundamental disconnect between how employers articulate needs (skills, competencies, capabilities) and how education systems structure offerings (courses, credits, seat time). Translating between these frameworks, and moving toward skills-based validation, remains a critical alignment challenge. Research from WGU highlighted that employers struggle to evaluate skill sets beyond resumes. Employers prioritize critical thinking, adaptability, problem-solving, and emotional intelligence – but struggle to see those signals clearly. Translating between these frameworks – and moving toward credible, skills-based validation remains a central alignment challenge. 

Anchor curriculum development in employer-identified skill gaps. Effective training models are co-designed with employers, focusing on what companies are hiring for now and where talent shortages persist. Demand-driven alignment strengthens both learner outcomes and employer confidence in training pipelines. Hands-on training models reinforce the importance of foundational technical competency alongside durable human skills.

Build post-graduation ‘captive ecosystems’ that promote talent portability. In K-12 education, we have a captive ecosystem: learners are enrolled, connected to infrastructure, supported by shared tools, and guided through a structured progression. That system – while imperfect – creates continuity, accountability, and exposure to skill-building environments. After graduation, that ecosystem dissolves. For many workers – especially those who are low-income, career-changing, or not attached to a large employer – there is no comparable structure guiding ongoing development, skill validation, or mobility. Navigation becomes fragmented and self-directed in a system that is complex and rapidly evolving. 

The opportunity is to intentionally design post-secondary and workforce ecosystems that replicate the strengths of captive ecosystems: continuity of support, access to shared infrastructure and tools, structured exposure to experiential learning, ongoing skill validation, real-time labor market insight, and clear progression pathways.

Embed experiential learning as a core signal of readiness. Experience is increasingly the differentiator. Learners must be able to demonstrate capabilities in addition to acquiring knowledge. Simulations, project-based learning, real-world datasets, internships, and apprenticeships were framed as essential mechanisms for building confidence, validating skills, and meeting employer expectations for experience. Experiential learning lowers risk for employers, provides tangible evidence of capability, builds durable skills in real contexts, and supports transferable skill translation (especially for veterans or career changers).

Adapt to how AI is reshaping hiring patterns and skill expectations. AI is not eliminating talent demand – but it is reshaping it. Employer data indicates a shift toward mid-level talent, reduced entry-level hiring in certain sectors, and increased emphasis on AI fluency alongside durable human skills. This evolution heightens the importance of adaptable credentialing and experience-building pathways. Lagging data – often 12 months behind labor market realities, also limits responsiveness. Real-time data systems and better cross-platform integration are critical to staying aligned with demand.