AI Industry Radar 2026
Benchmarking AI in Belgium through the eyes of AI decision makers
The AI Industry Radar is an initiative by PwC, powered by Tijd | Echo Connect and Mediafin Intelligence. The research was conducted by Profacts among with readers of Belgian daily newspapers De Tijd/L’Echo to understand the state of AI play with AI decision makers in Belgian companies. Specifically, to gauge its current level of strategic importance. Topics addressed include AI maturity and use cases, what drives or impedes trust in AI, and governance, data, and security*.
*As the survey only addressed people involved in decisions concerning AI, the results cannot be automatically extrapolated to the entire Belgian business landscape, however they do provide telling insights among AI decision makers.
Belgian companies need guidance
Implementing AI technologies is much more than simply an IT exercise, introducing a new digital solution or app. AI has the potential to completely transform processes and operations when included as part of a company’s overall strategy. But it seems that many companies don’t know where to start, outside of exploring the technology and using some more accessible AI tools to help improve user productivity.
Operational gains dominate
According to respondents, the top three reasons for using or considering using AI are mostly operational—improved efficiency, cost savings, and cost optimisation. These findings hold true for both larger and smaller concerns.
Governance is a game-changer
The research found that companies with well-developed AI governance are more confident about their level of AI maturity, their competitive position, and their technological readiness. The strong correlation with past AI partnerships suggests that AI partners may play a crucial role in helping organisations develop robust governance structures.
Technology and risks are barriers
The main reasons behind distrust in AI are reportedly security and privacy concerns—for all companies no matter their size. These are also the biggest barriers to AI deployment, along with budget constraints and lack of knowledge or expertise.
Building trust in AI
One of the key findings of the survey was that trust in AI is moderately positive—significantly more so with companies that have fully implemented AI governance and have worked with AI partners in the past. Trust in AI is a double-edged sword. On the one hand, it creates a burden, but on the other, it can create competitive edge. That’s where the EU AI Act can help. The Act offers the right balance between controlling risks and facilitating innovation aimed at AI applications that serve society and business in a safe, fair manner. Read more.
AI in financial services
The biggest challenge we see with clients in the financial services sector is AI adoption. Most have some form of AI, but there are very different levels of maturity. Organisations tend to adopt one of three strategies. Citizen-led where people are given licences and encouraged to use AI. A more structured approach via training and champions with use cases and monitoring. Or a more strategic approach whereby companies look where there’s still a lot of manual labour which can be replaced by AI. Those that are more advanced also look at their processes and how they can redefine them to make them more efficient. As to which strategy a firm adopts, it usually depends on its size.
AI in industrial manufacturing and automotive
We see investment in AI as being quite low in this sector for the time being. It’s a bit of a chicken and egg situation—the industry’s not doing well, so companies cut back on investments, but you need to invest to gain the potential that AI has to offer. One area where AI has great potential to deliver significant benefits is procurement. While procurement’s become much more strategic over the past 15 years or so, AI’s really raised the bar on what it could become. AI can take care of a lot of the manual work freeing up time for procurement experts to become more strategic and focus on the value add. Think about the total cost of buying something and the savings that could be made with AI making complex calculations about lifetime of a product vs. cost, including installment and maintenance, and the power of near real-time evaluations of index evolutions impacting supplies. To date, there aren’t sufficient examples of AI usage to move the needle.
AI in health industries
AI’s being tested by most big players in the health sector in terms of proofs of concept (PoCs) to help improve efficiency. Smaller biotech companies are leaner and more agile by design, which has pushed them even more toward AI. However, the databases of biotechs, which typically focus on rare diseases, are far more limited, making the implementation of AI more cumbersome. Investment overall for the industry is potentially much greater than for other sectors. Implementing the technology is just one part of the equation. Once embedded, companies must be able to validate to the relevant regulators that it’s safe, it works, and that it can be reproduced confidently. And every time evolutions are introduced, this validation process must be repeated. Given the speed of technological developments, the investment required is immense.
AI Industry Radar 2026
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