After the White Paper, Don’t Forget the Glue that Makes Skills Deliverable

Ed Fidoe welcomes the Post-16 White Paper’s focus on growth, levy flex and clearer technical routes, but warns it misses the glue: interdisciplinary skills and AI-first literacy. He urges problem-led curricula, FE to HE bridges, portable AI/data/cyber bolt-ons, and outcome measures that reward cross-team delivery.

The Post-16 Education and Skills White Paper is a major reset: growth at the centre, new levy flex for shorter training, a stronger role for Technical Excellence Colleges, and clearer Level 4–5 routes. All welcome. But one ingredient still feels missing from the blueprint: making interdisciplinary skills the norm, especially where further and higher education meet. And as AI reshapes entry routes, the paper says too little about AI-first workforce strategies.

The labour market is shifting fast. Over 40% of UK business leaders expect to reduce entry-level hiring because of AI (BSI, Flourishing in the AI Workforce, 2025), while over 70% report significant shortages in AI, data and cyber roles (Electronics Specifier, 2025). In cyber alone, almost 50% of firms say applicants lack key technical skills (UK Government, Cyber Security Skills in the UK Labour Market 2024). If we don’t change how learners build applied capability, we risk fewer early-career opportunities and persistent gaps in exactly the skills employers need.

Specialism matters. We need expert engineers, clinicians, data scientists and skilled trades. But the problems that hold the country back don’t fit inside one job title. A rail scheme isn’t only engineering; it’s budgets, supply chains, planning rules, local consent and the environment. Cutting hospital waiting lists involves data, behaviour, staffing and procurement. Retrofitting homes for net zero spans materials, finance, trades and community engagement. If we want delivery on time and on budget, we need people who can connect the pieces.

That’s what interdisciplinarity teaching does. It helps teams see the whole system, reduces misunderstandings between departments, and speeds responsible tech adoption because people understand how tools will actually be used. It also gives workers durable, transferable skills – so when technologies change, they can adapt.

There are practical models already working. At LIS we run a Cross-Functional Leadership course for people who deliver with colleagues from different teams and professions. Participants practise mapping systems, communicating with different audiences and making decisions that serve the whole organisation, not a single silo. We also help teams build a shared language so product managers, data analysts, clinical leads or site supervisors mean the same thing when they discuss a problem. Projects often stall not through disagreement, but because people talk past each other; a common vocabulary cuts rework.

Now that the White Paper is out, here’s how to turn intent into delivery – without adding complexity:

1. Make real-world problems the curriculum spine: Alongside subject depth, fund problem-led modules where learners combine methods to deliver a result – electrify a bus network; cut surgical waits without burning out staff; design a flood-resilience plan. Assess both the solution and the reasoning.
2. Link Further and Higher Education at levels 4–5 so learners move, not start again: Create shared modules co-taught by colleges and universities, set employer briefs for mixed teams, and make credit transfer seamless- into degrees or back into advanced technical training.
3. Use levy flex to build portable bolt-ons with AI, data and cyber in the core: Short courses should let a civil engineering apprentice add geospatial skills, a healthcare assistant add improvement methods, or a construction supervisor add environmental assessment – without restarting. Crucially, embed AI, data and cyber literacy so juniors can contribute alongside the tools that are changing their roles (BSI, 2025).
4. Reward outcomes that matter to delivery: Alongside participation and completion, track cross-team projects delivered, adoption of new methods on the job, and progression into roles that coordinate across functions. Counting hours taught is not enough.

None of this waters down expertise. It makes expertise effective. Interdisciplinary capability reduces the translation tax between teams, accelerates safe tech adoption, and equips learners with breadth-plus-depth skills that travel across sectors. In our programmes we see people move from “my task” to “the system”: framing problems clearly, choosing the right tools and delivering something that works.

The White Paper gets many building blocks right, sector depth, employer alignment, clearer routes. To make it deliver, we also need the glue: interdisciplinary learning and assessment, portable bolt-ons with AI/data/cyber at their heart, shared language, and measures that reward cross-boundary problem-solving. If we build that into the FE–HE link-up and we won’t just train more specialists, we’ll assemble the teams that get big national projects over the line and future-proof graduates for an AI-shaped economy.

By Ed Fidoe, CEO and co-founder, London Interdisciplinary School (LIS)