Artificial intelligence has reached a new milestone in Luxembourg’s business sector. After several years marked by experimentation and enthusiasm for new technologies, organisations are now moving towards a focus on deployment and value creation. This is the key finding of the 2026 edition of the AI Survey conducted by Fedil, Luxembourg AI Factory and Luxinnovation among 136 professionals from various sectors, the results of which were published on Tuesday 2 June.
The picture is clear. AI is no longer seen as an emerging technology reserved for pioneers. It is gradually becoming central to operations and digital transformation strategies. Productivity and efficiency gains remain the primary driver for adoption, cited by 88% of respondents. Next come process optimisation and cost savings, two drivers that reflect what is now a resolutely pragmatic approach to artificial intelligence.
Generative AI is playing a key role in this acceleration. Thanks to its ease of use and the rapid benefits it delivers, it is becoming established in administrative functions, reporting, translation, document management and customer service. Nearly six in ten companies report that they have already deployed generative AI solutions across the organisation or in operational use cases. Conversely, only 7% of the organisations surveyed do not plan to use it in the next 12 months.
The frameworks and rules are progressing slowly
The study also reveals that AI is becoming increasingly widespread beyond IT departments. Marketing, communications, human resources, finance and customer relations are now adopting these tools to automate certain tasks and improve their efficiency. At the same time, 70% of respondents indicate that AI-related initiatives are now integrated into broader digital transformation programmes, a sign that the technology is becoming a structural element of corporate strategy.
But this rise in prominence has been accompanied by a shift in the nature of the challenges faced. The main challenge is no longer one of persuasion or experimentation. Companies are facing a persistent skills shortage in the fields of data, AI engineering and change management. They must also absorb higher costs as projects move beyond the pilot phase and into full-scale industrial deployment. Infrastructure, cybersecurity, governance, data management and the recruitment of specialist staff are driving up the bill.
The issue of data appears to be another major obstacle. Whilst many organisations have largely digitised their operations, they are still struggling to put in place the governance and operational mechanisms needed to make full use of their data. This weakness directly limits their ability to develop robust and scalable AI solutions.
Governance is, ultimately, the major challenge for the coming years. Fewer than one in two companies currently has a formal AI policy in place. Whilst the use of AI is growing rapidly, regulatory frameworks and internal rules are evolving at a slower pace. This mismatch could become problematic as these technologies play an increasingly significant role in decision-making and operational processes.
