Excellent questions! Let’s take them one by one.
”Was it so that at the core of Witted’s business model is building the customer’s teams, and specifically so that your people are involved in these teams in key roles?”
Exactly. To simplify slightly, the change management side of Nexec typically provides program management, project management, change management, etc., while the software development business provides architects, developers, scrum masters, and so on.
Has the role of AI been exceptionally significant in the work of these customer teams, and can Witted’s improved success be explained by this new ”team member”?
“Exceptionally significant” might be a bit of an overstatement, but its importance grows month by month. In some accounts, we are at a stage where no one can get by without AI expertise anymore; in others, it’s an earlier phase. In more advanced accounts, we are seeing the re-rolling of teams for the AI era, and demand is strengthening for experts capable of systemic thinking, understanding business problems, and “factory-like” software production instead of strengths purely in writing “code syntax.”
If you are interested, you can read more about this in this white paper. And if you’re interested but short on time, ask Claude/Gemini/ChatGPT to summarize the key messages. 
In addition to those easy yes/no answers (I hope you’ll elaborate), I’d like to hear how you, as the CEO of an IT services company, see the AI disruption affecting the operations and revenue of IT service companies now and in the future?
I already tried to say more than just yes and no above. But let’s continue.
First, briefly, the impact on us: revenue and profitability-enhancing in the medium and long term.
Then, in more detail. I’ll answer specifically from our perspective because we are a unique type of IT services company. We focus primarily on serving digitally advanced customers, where the customer’s buying behavior differs from the mainstream (more customer-led work where specialized expertise is provided; fewer project deliveries where the customer’s own activity is lower). Furthermore, our operating model is particularly suited for experienced professionals (read: we can pay senior professionals better if they are willing to share the risk of being billable in customer projects with us), and thus the market challenge regarding the future of junior developers does not affect us. Additionally, our customer base is heavily weighted toward large enterprise accounts, meaning all AI-related initiatives have a very strong change management perspective. We are not building from scratch; we are changing how hundreds or thousands of employees work in a technological environment where some building blocks might be decades old.
Our strategy is based on the assumption that gradually, every company will become a software or technology company. With AI, development becomes vastly more efficient, and the financial calculations for technology investments are recalculated. This leads to a major investment wave in automating and redesigning companies’ core functions.
A very large proportion of employees at big enterprise customers—estimates vary by industry from 20% to 50% of the workforce—perform work that is partially or entirely automatable. We have tried to estimate how many development resources are needed to automate such work, and our best educated guess is that for every 10 operational tasks being automated, 1-2 developer-type experts are needed. Those previous 10 operational tasks were not our business, but the new 1-2 developer roles are.
However, these 1-2 new developer roles are not identical in content to how software was previously developed (referring also to the white paper above). The level of abstraction rises, managing entire systems becomes more important, and enterprise-level requirements for things like security and quality bring forth entirely new key roles in the “software development factory.” At the same time, business domain experts are expanding their skills toward software development. All this means that a good IT services company must radically develop its offering and expertise. But the market is willing to pay more than before for this modern expertise.
In our business model, experts have very strong incentives to continuously develop their skills. They understand that mastery of these new methods and tools strengthens their personal demand and can positively impact earnings through the higher value provided to customers. We have an exceptionally low need to “push” people to learn new things; instead, there is a pull from the experts, as long as we can guide them in the right directions based on customer demand and broader market insight. If this weren’t the case, my hair would be turning gray much faster—the risk of “obsolete inventory” would be the single greatest danger to business profitability.
