We may be reaching the limit of skills as the main way we think about human development at work.

Industrialisation changed both the tools people used and the way work was organised.

Industrial production divided work into narrower, repeatable tasks that could be standardised and coordinated. The assembly line became one of the clearest examples of this.

This brought enormous gains in productivity, although it also changed the relationship people had with their work. Earlier forms of work could be extremely hard and insecure, but many trades and crafts involved a broader range of abilities and a clearer connection between the person, the work and its purpose.

Life itself was not organised entirely around productive work. Religious and seasonal festivals, local traditions, music, art and other forms of communal life also provided structure and meaning. None of this should be romanticised, but it is worth remembering that human development has not always been understood primarily in terms of economic capability.

As knowledge work expanded, we increasingly described what people could do in terms of discrete skills. Those skills could then be taught, assessed, recorded and matched to particular tasks or roles.

In that sense, the modern emphasis on skills can be seen as an extension of the same underlying logic. Work was broken into smaller parts, and as knowledge expanded, human capability was increasingly described in smaller parts too.

This has been useful. It gives organisations a practical way to think about recruitment, development and the allocation of work.

AI may now make some of the limits of that approach more apparent.

Many of the tasks that can be clearly separated and described are also the ones that AI can increasingly perform or support. If that continues, the value of human contribution may depend less on individual skills in isolation and more on how they are combined.

Expertise is not just a collection of skills. It also involves judgement, experience, context and the ability to connect different forms of knowledge.

That includes forms of understanding that do not fit easily into a skills framework. The humanities and arts can shape judgement, perspective and our sense of what matters, even when they do not map neatly onto a particular task.

It often depends on understanding how a particular piece of work fits into a wider situation, and on knowing why it matters as well as how to do it.

That does not make essential skills unimportant. But if AI becomes increasingly capable of handling many of the individual parts, then human development and work may need to place more emphasis again on integration, judgement, meaning and understanding the whole.