The AI jobs debate is missing the skilled trades

For all the debate about AI and the future of work, we are still viewing the workplace through a narrow lens. Much of the public conversation has focused on those most visibly affected: software engineers, tech employees, knowledge workers and office personnel.

That debate matters. But it misses a larger and more immediate reality.

AI is also reshaping occupations rarely placed at the centre of the technology debate: skilled trades, public sector jobs and service roles. These are the people who maintain equipment, work in healthcare, keep infrastructure running and deliver the essential work societies depend on every day.

At the same time, demand for skilled workers is growing and will continue to grow as the world’s population ages and shrinks. It is time we focused more sharply on their future in the AI era.

Our new research report, For Every Future: Preparing Early-Career Skilled Trade, Technical and Service Talent for an AI-Infused World, finds that the remaking of skilled jobs and rising demand for these workers are on a collision course. From that emerges a new challenge: a rapidly developing triple capability gap.

The first gap concerns new capability. People entering skilled trade, technical and service roles increasingly need to understand how to work with AI: when to use it, when to question it and how to apply it safely and responsibly.

An early-career construction worker, for example, will increasingly work alongside AI-powered safety systems. They must know when to act on an alert, when to verify it and when to trust their own judgment if the technology misses a hazard.

In pharmacy, AI can support dispensing and stock management, but it cannot replace clinical judgment. Technicians still need the expertise to identify risks, challenge outputs and intervene when patient safety demands it.

The second gap is a consequence of the first. As AI reshapes roles, workers must strengthen the distinctively human capabilities it cannot replicate, including collaboration, communication and adaptability. These will become a primary source of value in an AI-augmented workplace.

The final gap concerns experience-based knowledge. Skilled occupations have always depended on practice, observation and learning from experienced colleagues. Workers learn how to spot the problem that is not in the manual or recognise the sound of broken machinery.

As experienced workers retire or leave in record numbers, that practical knowledge is becoming harder to access just as it becomes more important.

This is not simply an AI skills challenge. It is an expertise challenge: young workers risk lacking old and new knowledge at the same time. How do we skill people in an era that is AI-rich but experience-poor?

Closing the triple capability gap requires three things: role-specific AI literacy; stronger human capabilities, such as communication and collaboration; and more opportunities for experienced workers to pass on institutional knowledge through effective mentoring and structured knowledge bases.

Judgment. Ethical responsibility. Practical know-how. The capabilities that pass from one generation to another.

Our research found that AI is not replacing skilled workers. It is exposing how unprepared we are to train them for the workplace of the future.

Left unaddressed, the gap risks leaving a generation behind. We could have undertrained workers in safety-critical jobs and suffer real economic damage if employers cannot find, develop and retain the people they need.

But the opportunity is significant. AI can help people learn faster, access knowledge more easily and solve problems in new ways. It can improve productivity and open new pathways into meaningful careers. That will happen only if we are intentional about how expertise is built, training evolves and human judgment remains central.

Employers, educators, policymakers, industry bodies and technology providers must work together to redesign pathways into skilled work. We need training that reflects modern workplaces, stronger links between learning and practice and better ways to capture experienced workers’ knowledge before it is lost.

The future of AI will not be determined by technology alone, but by whether people are prepared to use it well. This report is a call to widen the conversation, recognise the essential workers too often excluded from it and ensure that, as work changes, people are not left behind.