Artificial intelligence is changing knowledge work and the requirements for it. Orchestration and management of work are essential skills for specialists. Those who are curious about change and combine the opportunities offered by new tools with their own expertise are most successful. Organizations' role is to enable a new kind of work – to be responsible for managing competence and change.
Read the summary (AI-generated, human-reviewed)
- AI will not take away the work of experts but will change the way we work. The work moves from individual deliverables towards understanding and managing the big picture.
- Change requires new kinds of competence, communication, and leadership. AI expertise is becoming layered, and in an increasingly technical world, the value of human skills is increasing. Success in change requires communication and leadership.
- The role of organizations is crucial. Competitiveness is created by how well companies enable learning, support change, and help experts combine the opportunities of artificial intelligence with their own expertise.
The debate on the revolutionary impact of AI on working life is accelerating at the same pace as technological development. In addition to the poor economic situation, several companies have already cited AI's impact in justifying personnel reductions.
The transformative power of AI has been closely monitored in the software industry, where its effects are significant. On the eve of major changes, new structures are often shrouded in obscurity for a long time, yet some clear developments in AI's impact on work can already be observed. Over time, they find their way into many areas of the world of work.
"The first change is that work is changing from tasks that require task skills towards continuous systemic understanding to skills that require continuous systemic understanding. And this applies to all knowledge work, not just the IT sector," says Digia's CTO Juhana Juppo.
The point is that as AI takes on more and more diverse business-related tasks, the responsibility for performance quality remains with humans. In other words, it is necessary to understand how AI's activities affect the broader business and even the societal framework.
Three levels of AI expertise – demand for expertise that combines the operating environment and technology in particular
Another major consequence of technological development is the fact that AI expertise has become layered.
At a basic level, it is enough to work with AI, i.e., to master the "normal literacy" of artificial intelligence. On the second level, in addition to AI, you need to understand the current operating environment, whether it is a specific industry or even a role within the company.
"For example, you can be an expert in healthcare, finance, or HR who is able to effectively utilize AI built specifically for these roles. There will be a lot of demand for such a combination of skills," Juppo says.
And at the third level, you need a deep understanding of AI itself, i.e., the ability to build and maintain the AI systems needed in business.
Communication and leadership are decisive
However, the current transformation of working life is also about much more than the competence related to AI itself, as described above. In an increasingly technological world, teams are increasingly composed of people and machines, which increases the value of human skills, especially communication.
"An important factor in the success of a team is how its members are able to collaborate with each other and how they are able to pass on their knowledge to each other when working with artificial intelligence. It is also pointless to imagine that adapting to technological changes in working life would be possible without high-quality communication and leadership," Juppo says.
Indeed, work is changing from the performance of time-limited tasks to the continuous orchestration of work. For example, we can talk about AI stewardship, but orchestration is about much broader management of work tasks. It includes the management of all work performed by humans and machines, both together and separately.
"Orchestration skills are essential at all levels of the company. An individual employee must be able to manage their own work with AI. Team managers must be able to orchestrate the work of AI agents and humans. Business leaders need to be able to orchestrate the work of teams and different functions, and so on upwards," Juppo describes.
Work orchestration is a new, necessary skill without which companies' competitiveness will inevitably erode.
It goes without saying that early adopters of AI will have an accelerating competitive advantage over other companies as they learn the potential of new tools and how to use them most effectively in conjunction with humans.
Therefore, companies should be especially curious about which new skills they need.
"Change is difficult and even frightening, but you shouldn't look for reasons to continue doing things that used to be right but are no longer right," Juppo says.
Experience helps when coding with AI
Among industries, the software industry is the furthest along in AI adoption. Contrary to the old saying, in this case, the cobbler’s children really have shoes: AI is being used very actively.
With the spread of AI, especially in vibe coding, the illusion has arisen that everyone knows how to code. Maria Hintikka, Digia's Director of Application Development, says that this is a slight misunderstanding, to say the least.
"Of course, the code can be commissioned by AI, but without your own coding expertise, it is impossible to assess whether the AI code will do exactly what it is supposed to do in the future. My working life observation is that seniors work efficiently with agents to create high-quality code, but only because they have a long experience of coding themselves."
So coding is not a sunset industry, even though you hear it claimed to be; quite the opposite.
"Problem-solving is the bread and butter of coders, and now they can do it much more efficiently than before. The new tools have brought a neat itch to the work," Hintikka says.
AI enables significantly faster development cycles, with new versions presented almost immediately. This, in turn, reshapes the dialogue with the customer into something completely new. As the operating environment changes, so do the demands of work.
"Coders also need to start understanding business more than before. At the same time, of course, the importance of communication is growing in the software industry in the same way as in other fields."
Read more about the new era of software development in the blog of Mikko Sairanen, Director of Digital Experience at Digia, >>
AI is an opportunity, not a threat
It has long been feared that technological advances will take jobs from people. But the opposite has often happened, as disappearing jobs have been replaced by tons of new ones. However, it is feared that the leap in artificial intelligence will be so fundamental that new jobs will not be created to replace those that will disappear. Both Juppo and Hintikka think that there is no reason to be afraid.
"AI is not a threat to unemployment for Finland, but an opportunity that we should be able to take advantage of. Times are changing, and jobs are changing, but the productivity leap enabled by AI should not be missed," says Juhana Juppo.
The situation in the IT sector is similar to the average in society, even though AI is already a necessary part of everyday life in the sector.
"The unemployment figures in the sector are not due to AI; the challenges come from elsewhere. If you keep up with the development, there is plenty of work to do," says Maria Hintikka.
She points out that young people, in particular those currently studying, will eventually enter the workforce as AI natives, which means there is certainly demand for their skills.
"In fact, we will soon start to need AI-native expertise, and at the same time, we will retrain the generations already in working life to use artificial intelligence effectively," Hintikka says.
5 perspectives on how AI is changing work:
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The new organization of work into teams of people and machines requires human skills, especially effective communication.
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The combination of AI expertise and industry knowledge is an increasingly necessary skill in the workplace.
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The fear of change prevents people from experimenting and discovering the benefits of AI.
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Software know-how is still essential because, without it, it is not possible to use AI safely and efficiently.
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Companies should focus on competence and change management, i.e. how people can do their jobs better, rather than one-sided efficiency and productivity thinking.
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