AI and automation are already reshaping how work gets done. For organisations, the question is no longer whether work will change, but how quickly they can adapt.

Recent research highlights the scale of the transformation. According to the World Economic Forum, around 22% of jobs are expected to change structurally within the next five years. Some roles will disappear, many will evolve, and new ones will emerge.

At the same time, AI is increasingly becoming part of everyday work rather than a specialised technology used by a few experts. In Finland, estimates suggest that around 63% of jobs will be supported by AI in performing tasks, meaning that most employees will interact with AI tools as part of their daily work.

This shift raises a critical question for organisations: What skills will actually matter in the years ahead?

Work is changing, not disappearing

It is tempting to frame AI primarily as a threat to jobs. In reality, the change is more nuanced.

Studies suggest that while some jobs will be displaced by automation, many will simply change. A significant share of workers will need to update their skills within their current roles, while others may move into adjacent roles that require new capabilities.

In practice, this means that the focus for most organisations should not be job replacement but skill evolution.

Routine and repetitive tasks are increasingly automated. At the same time, work that requires judgment, collaboration, communication and problem-solving becomes more important. AI does not replace these capabilities, it often makes them more valuable.

Why skills development often falls short

Despite widespread awareness of the coming changes, many organisations struggle to translate this into practical action.

A common pattern is to launch training programmes that are disconnected from real work. Employees attend courses or online training, but the new skills are rarely integrated into daily tasks.

Another challenge is that AI adoption often starts from the technology side. Tools are introduced first, and the discussion about roles, processes and capabilities comes later, if at all.

This can lead to uneven adoption across the organisation. Some teams experiment actively with new tools, while others remain uncertain about how AI relates to their work.

Without a clear view of future skills and capabilities, organisations risk investing in training that does not address their most important needs.

A practical starting point: understanding the skills gap

One of the most useful starting points is a structured assessment of future skills needs.

This typically begins by examining how planned technology investments and digital initiatives will change key processes. Once these changes are understood, organisations can identify the capabilities that will be required in the future.

From there, three practical questions emerge:

1. How will technology change the way work is done?
Which tasks are likely to be automated, supported by AI, or redesigned?

2. What capabilities will be required going forward?
Which skills should everyone in the organisation develop, and which require deeper expertise?

3. Where are the largest gaps today?
Which capabilities already exist within the organisation, and where is development most urgently needed?

Sources: WEF, The Future of jobs report