With AI, trivial work can be automated and complicated work can be sped up. There are many fantastic possibilities for your company to be ahead of the competition – and even achieve this at lower costs. If you do a clever AI transformation, there are so many golden eggs you can pick up on your way. By all means, go do so. However, one particular problem looms on the horizon: if AI is doing most of the work, and humans are mostly here to define what AI should do and review the output, how do you ensure that future generations of employees have the required competences to validate what AI is doing? Are we heading towards digital illiteracy by automating what previously built employee capabilities?
If we look at how, for example, software development was done prior to the AI revolution, software architects were defining the structure of systems, senior developers were programming the complicated parts of the software, and junior developers were developing the simpler parts while being mentored by seniors. Through this, junior developers could build up their experience and competences, and through hard work, sweat and maybe even tears, they could reach a senior level over years of practice. With AI taking over what junior developers are doing – and maybe even some of what senior developers do – your company will, over time, lose the opportunity to grow experienced seniors. Experience and competences come through hard work, which includes a long chain of failures and successes. The question is: how do you substitute this in an AI-driven world?
Prior to the AI revolution, software was, to a great extent, developed by using Agile practices like Kanban or Scrum. Some think that with AI, Agile is no longer needed, while others – like the author of this article – think it is even more important than ever before; it is just the practices that must change while the focus on value creation and human interaction remains. Agile operated with cross-functional teams, where the collective competences of the members should cover what was needed to get the job done, end to end. It was recommended that a team consist of some five to nine persons, and there were usually also a variety of seniority levels in the teams. Working towards shared goals gave opportunities for knowledge sharing and growing skillsets.
With AI as part of the equation, teams will most likely consist of a few humans and many AI agents. The humans, acting as initiators, reviewers and integrators of work, while the AI agents are doing the "dirty" work. You can get a lot of work done in such a setup. But is it the right stuff, and is it of the right quality? Only competent and experienced developers can verify this – at least for many years to come. Once it is no longer needed, well, then digital illiteracy will truly take hold.
As an Agentic Leader, you need to think about sustainability, and you need to consider having the right competences in the future. Like saving up for retirement, you need to invest in future competences already today; otherwise, your company will lose its competitive advantage in the future. Consider how you will help your teams organise their work so that mentorship and knowledge sharing will continue, while your company benefits from the great advantages that AI will bring. In Agile, we use the latest responsible moment as a core factor for when to make decisions or act. To secure sufficient future competences, the latest responsible moment for this is most likely now.
