Dutch organisations primarily use AI to make existing tasks more efficient. Fundamental changes to business processes remain limited. According to Lucas Jellema, CTO of Conclusion, the problem lies not so much with the technology itself, but with the way organisations structure their processes. Moreover, many lack a clear understanding of the actual returns on their IT investments.
The Tech Reality Check 2026, a survey conducted by Conclusion among 1,058 IT decision-makers in the Netherlands, Germany, Portugal and Spain, shows that 74 per cent primarily use AI to improve efficiency. Dutch organisations appear particularly reluctant to embrace broader transformation. Only 11 per cent of Dutch executives and board members explicitly take responsibility for technological transformation, according to respondents. In Germany and Portugal, the figures are 31 and 30 per cent respectively.
Jellema adds a note of caution to these comparisons. The findings are based on IT decision-makers' assessments of their own organisations, which do not necessarily provide an objective measure. "If you think you've already made considerable progress, you may be perfectly satisfied. Meanwhile, an organisation with much greater ambitions might see itself as falling behind."
Look at the entire process
One of Jellema's main conclusions from the research is that organisations do not adequately measure the actual returns on their IT initiatives. Investments are made on the basis of business cases, but organisations often fail to establish afterwards whether the expected results have been achieved.
The same applies to AI. Many organisations report significant productivity gains, but these usually relate to individual tasks. "When people talk about the productivity gains they achieve with AI, they're almost always referring to a task that can be completed much faster. They're not looking at the entire process, from start to finish."
He gives an example from within Conclusion. A colleague used AI to automate almost the entire process of deploying software components into a production environment. The effort required for these activities fell by approximately 80 per cent. However, this did not mean that the overall process became five times faster. Additional work was needed to prepare the AI systems and enable them to perform the tasks.
According to Jellema, organisations therefore need to look beyond individual applications. Many business processes consist of steps that were introduced for good reasons but have since become unnecessary. "You really need to put everything you currently do back on the table and redesign the process from scratch."
AI as a catalyst
Interestingly, such transformation does not always require AI. The attention surrounding the technology has made it easier to revisit automation opportunities that have existed for years.
Jellema points to organisations where employees still manually re-enter data or transfer information between systems. IT staff are also sometimes called in during the night to deploy software, even though these activities could be automated.
"AI has now become something of a catalyst," he observes. Issues that previously received insufficient management attention can be brought back onto the agenda. "We say we're going to automate using AI, when in reality what we're doing sometimes has almost nothing to do with AI. But we still achieve the benefits we predicted."
From advice to implementation
Conclusion supports organisations in both redesigning business processes and implementing the underlying technology. According to Jellema, the company's strength lies in combining different areas of expertise, ranging from strategic consultancy to software development, infrastructure and operational management.
One example is Conclusion's work in close collaboration with energy company Eneco to manage electricity generation from wind and solar farms. To maintain grid stability, energy producers must sometimes reduce their output within seconds of receiving instructions from grid operator TenneT.
Conclusion helped design and implement the entire technical and organisational process, from receiving the control signal to adjusting electricity generation and reporting back to TenneT. This involves data connectivity, IoT, cloud management and mission-critical availability.
Jellema emphasises that this is not primarily an AI application. The value comes from combining technologies and establishing a reliable process. An additional application involves temporarily shutting down wind turbines when radar systems detect large flocks of birds. In this case, AI is used for image recognition.
Start with self-assessment
What should executives do if they recognise their own organisation in the research findings? Jellema advises against immediately launching another technology project. Instead, organisations should first take a critical look at their existing operations.
Which processes were originally designed around constraints that no longer exist? Which technology decisions should be reconsidered? And which investments have actually delivered the expected results?
It can also be useful to involve someone from outside the organisation who can examine established working practices without being influenced by their history.
According to Jellema, the Tech Reality Check is primarily intended to encourage this kind of reflection. The most important step towards technological transformation is not acquiring new AI tools, but being willing to reassess previous decisions and fundamentally redesign processes where necessary.
