Greening TVET in Ghana: Where AI Fits Now

Ghana’s green jobs future won’t wait for our curriculum committees.

The labour market is already shifting toward solar installation, energy-efficient construction, waste sorting and recycling, sustainable agriculture, and cleaner manufacturing. The uncomfortable part is that many training programmes still treat sustainability as “an extra topic” rather than a core skill that affects how work gets done.

A useful reminder comes from a UNESCO-UNEVOC initiative: the BILT workshop on Greening TVET (held in Malta, 23–24 October 2019). Nine institutions across eight European countries compared practical approaches to “green” their technical and vocational education and training. The details weren’t about slogans. They were about curriculum, teacher readiness, industry alignment, and the link between digital tools and sustainability.

This post brings those lessons home to Ghana—especially for readers following our series “Sɛnea AI Reboa Adwumakuo Ketewa (SMEs) Wɔ Ghana”. Because here’s my stance: Greening TVET and helping SMEs adopt AI should be planned together, not as separate projects. TVET supplies the skills. SMEs supply the workplace reality. AI can connect the two with better data, faster training updates, and more practical learning.

What the BILT workshop got right about greening TVET

Greening TVET works when it becomes a whole-institution habit, not a one-off module. That’s the core idea behind the “whole-institution approach” discussed in the BILT context: you don’t just add a lesson on climate change—you change what the institution teaches, how it teaches, how the campus operates, and how it partners with employers.

The workshop highlighted two pressure points that apply directly to Ghana:

1. Rising demand for green skills from employers (the labour market is pulling training institutions).
2. The real impact of integrating green skills into curriculum and standards (if it’s not assessed, it won’t stick).

The participants also spent time on a practical question that Ghana can’t ignore: transferability. In other words, “Can this approach work in another country with different institutions and industries?” That’s exactly the question we should ask when we adapt global TVET ideas to local realities in Accra, Kumasi, Tamale, Takoradi, and beyond.

Stakeholders decide whether greening TVET survives

The workshop’s clearest message was stakeholder breadth. Greening doesn’t hold if it’s only a principal’s passion project.

They emphasised co-developing with:

• Students (because they pressure-test what’s practical)
• Teachers and trainers (because they deliver the change)
• Parents and management (because they influence resourcing and continuity)
• Private sector and municipalities (because they validate relevance and help scale)

For Ghana, I’d add one more stakeholder group: SME associations and informal sector master-craft networks. If greening TVET doesn’t reach the workshops, garages, and small production sites where most people actually learn and work, it stays academic.

Why Ghana should treat “green skills” as job skills

Green skills aren’t only for environmental specialists. They’re becoming basic competence in trades.

A mason who understands thermal comfort and passive cooling designs is more employable. An electrician who can size solar systems and troubleshoot inverters wins contracts. A hairdresser who can choose safer chemicals and manage waste responsibly reduces risk and cost.

The curriculum shift: transversal + sector-specific skills

One smart point from the BILT workshop: institutions used two complementary approaches.

1. Transversal skills (cross-cutting): climate awareness, resource efficiency, safe material use, responsible waste handling, basic energy literacy.
2. Sector-specific skills (deep technical): solar PV installation standards, energy auditing basics, green building materials, efficient motor systems in industry, sustainable water use in agriculture.

For Ghanaian TVET, the mistake is picking only one.

• If you teach only transversal content, graduates sound informed but can’t execute.
• If you teach only sector-specific content, graduates can execute one task but miss the bigger system (and safety, compliance, and customer expectations suffer).

A balanced model works better: transversal skills in year 1, then sector-specific tracks aligned with local demand.

Student-centred teaching is non-negotiable (but it’s hard)

The workshop called out something many systems dodge: green competencies often require new pedagogical approaches—more projects, more real-world problem-solving, more experimentation.

That’s great. But it only happens when teachers are supported.

In Ghana, teacher support should be designed like a product:

• Short, frequent upskilling sessions (not one big annual seminar)
• Ready-to-teach lesson packs (projects, rubrics, materials lists)
• Industry attachments for instructors (even 2–4 weeks makes a difference)
• A feedback loop from employers and SMEs every term

This is where AI can stop being hype and become infrastructure.

Where AI strengthens greening TVET (without adding workload)

AI helps most when it reduces the cost of updating training and measuring outcomes. If it adds complexity, schools and SMEs will ignore it.

Here are practical ways AI fits the “greening + TVET” agenda in Ghana—especially for SMEs that host apprentices, offer attachments, or hire TVET graduates.

1) Curriculum that updates faster than policy cycles

Most companies get this wrong: they wait for official curriculum revision before changing what they teach. The labour market doesn’t wait.

A realistic approach is to use AI tools to:

• Summarise changes in manufacturer manuals (solar, HVAC, efficient motors)
• Turn real workplace incidents into classroom case studies
• Generate first drafts of competency checklists for new equipment

Human experts must approve the content, but AI can cut the prep time from weeks to hours. That matters when the same instructors are teaching, supervising workshops, and handling assessment.

2) Smarter assessments that prove skill, not memorisation

Greening TVET fails when “sustainability” becomes an essay question.

AI can support performance-based assessment by helping teachers generate:

• Practical tasks (e.g., “Diagnose why a solar system underperforms”)
• Marking rubrics with clear criteria
• Variations of the same task to reduce copying

For SMEs, this means graduates arrive with verifiable competence—not just certificates.

3) Training content that SMEs can actually use

This series focuses on how AI supports SMEs in Ghana, and this is a big overlap: SMEs need short training assets for real operations.

AI can help SMEs create:

• One-page SOPs for waste handling, chemical storage, energy-saving shutdown routines
• Simple customer education scripts (why an efficient option costs more but saves money)
• Maintenance checklists for tools and machines to reduce energy waste

When SMEs improve operations, apprentices learn better habits automatically. That’s greening TVET through the workplace—not only through the classroom.

4) Linking digitalisation and greening (the overlooked win)

The BILT workshop recognised the link between digitalisation and greening in two directions:

• Tech growth is driving renewable energy sectors.
• Digital learning tools (apps, MOOCs, open resources) make sustainability education more accessible.

For Ghana, I’d make it more specific: digital tools help greening when they reduce material waste, travel, and downtime.

Examples that fit TVET + SMEs:

• Virtual troubleshooting simulations before touching equipment
• QR-code based maintenance logs in workshops
• Short mobile lessons for apprentices who can’t attend evening classes

A Ghana-ready “whole-institution” greening plan (with AI)

A workable plan has to be simple enough to run with limited budgets. Here’s a framework you can adapt whether you’re a TVET leader, an NGO, or an SME collaborating with a training centre.

Step 1: Start with one trade area and one measurable outcome

Pick a trade where green demand is obvious (electrical, construction, automotive, welding, agro-processing). Then choose a measurable outcome such as:

• Reduce workshop electricity use by 10% in a term
• Introduce a safe waste segregation routine and track compliance weekly
• Ensure 80% of students can pass a practical energy-efficiency diagnostic task

AI’s role: help design the measurement sheets, summaries, and reporting so it doesn’t become “extra paperwork.”

Step 2: Co-design with SMEs and local authorities

The BILT workshop was direct about the role of private sector and municipalities.

In Ghana, translate that into:

• 3–5 SMEs on a trade advisory group (not 30 names on paper)
• One local authority contact for sanitation/waste or works department alignment
• One termly review meeting with evidence: student work, employer feedback, basic metrics

AI’s role: capture minutes, turn feedback into an action list, and track what changed.

Step 3: Upgrade teachers first, then scale

If teachers aren’t confident, student-centred learning doesn’t happen.

A practical upgrade path:

1. Micro-train teachers on one green competency and one project method
2. Run the project with students
3. Review results and improve the materials
4. Repeat each term

AI’s role: create draft lesson plans, rubrics, and project variations—then teachers localise them.

Step 4: Make the campus part of the curriculum

“Greening the campus” isn’t decoration. It’s a living lab.

Low-cost options:

• Track water leaks and fix them as student projects
• Measure energy use per workshop area and set targets
• Build simple waste stations and assign student maintenance teams

AI’s role: basic dashboards and simple trend summaries for student reflection.

Common questions Ghanaian SMEs ask (and straight answers)

“We’re small. Do we really need green skills?”

Yes—because efficiency is money. Reduced energy waste, better material use, and safer processes lower operating costs and attract better clients.

“Won’t AI be too expensive for our training needs?”

Not if you use it like a tool, not a department. Start with narrow tasks: drafting SOPs, generating checklists, creating quizzes, summarising feedback.

“How do we avoid teaching wrong information with AI?”

Use AI for drafts, then validate with a human expert and local standards. If you can’t verify it, don’t teach it.

A simple rule I use: if the output would be dangerous when applied in a workshop (electricity, chemicals, lifting), it needs a second set of human eyes.

What to do next (TVET leaders, SMEs, and partners)

The BILT workshop showed that greening TVET becomes real when stakeholders work together, when curricula reflect labour market demand, and when teachers have the support to teach differently. Ghana can borrow those principles—but we should add a 2025 upgrade: use AI to reduce the friction of implementation.

If you run a TVET institution, pick one programme and pilot a whole-institution greening project with clear metrics. If you run an SME, start with one operational improvement (energy, waste, chemicals) and turn it into a training routine for apprentices. If you support skills development as an NGO or agency, fund the boring parts—teacher support systems, assessment tools, and simple measurement.

The series “Sɛnea AI Reboa Adwumakuo Ketewa (SMEs) Wɔ Ghana” keeps coming back to one point: AI is most useful when it makes everyday work clearer, faster, and more consistent. Greening TVET needs exactly that.

What would happen if every TVET graduate in Ghana could prove—practically, not theoretically—that they can do their trade safely, efficiently, and with less waste?