Organizations across Europe are carrying out artificial intelligence adoption initiatives without previously defining the results they expect to achieve. According to new research from Rebura, a Westcon-Comstor company and specialist AWS (Amazon Web Services) solutions provider and consultant, only a quarter (25%) of organizations have fully defined the business outcomes of their AI initiatives.
The study, prepared from a survey of 300 business leaders from the United Kingdom, France, Germany, Italy and Spain, shows that the adoption of artificial intelligence is advancing in many organizations without a sufficiently defined strategy.
At the same time, more than a third of respondents (37%) say their AI-related activities are primarily driven by guidance from senior management. This data suggests that many companies launch AI adoption projects before establishing clear objectives and concrete criteria to measure their success.
Measurable business results
The results reflect a growing gap between organizations’ AI ambitions and their ability to transform investment into measurable business results. According to the report, called The AI Reality Check: Why Most AI Initiatives Never Make It, only 27% of AI initiatives successfully reach production environments.
On the other hand, more than half of respondents (58%) describe their approach to AI implementation and adoption as ad hoc experimentation, while less than a third (29%) follow a structured AI lifecycle. Additionally, nearly one in five organizations (19%) say they do not have clearly defined outcomes for their AI initiatives.
The survey data suggests that obstacles to AI success typically transcend the technology itself. Many organizations continue to face challenges related to governance, planning, data preparation and operational processes. All of this raises questions about whether companies are putting too much emphasis on AI tools and not enough on the foundations needed to achieve quantifiable results.
In this context, the adoption of artificial intelligence requires not only selecting the appropriate technologies, but also establishing processes that allow determining where it adds value and how that impact should be measured.
The report also identifies a significant preparedness gap between smaller organizations and large enterprises. Only 14% of SMBs consider their data to be AI-ready, compared to 36% of large enterprises. Additionally, SMBs are disproportionately affected by other barriers to AI success: 58% report security and compliance as an issue, while 46% face challenges related to poor data quality.
Regardless of company size, security and compliance are among the most cited challenges, both during AI deployment and as organizations attempt to scale their initiatives post-launch. This indicates that governance remains a long-term operational consideration and not simply an obstacle associated with implementation.
A business transformation initiative
“The conversation about AI often focuses on the technology itself, but our research suggests the biggest challenge lies elsewhere,” said Aaron Rees, CEO of Rebura. “Organizations are facing increasing pressure to demonstrate advances in AI, yet many do so before they have clearly defined the outcomes they aim to achieve. The true value lies in combining the technology with proper governance, robust databases and operational discipline. Those companies that approach AI as a business transformation initiative, rather than as an isolated technology project, will be much better positioned to move beyond the experimentation phase and achieve lasting results.”
Only 27% of AI initiatives successfully reach production environments, report says
The research therefore shows that the adoption of AI should not be limited to the implementation of pilot projects or the incorporation of new tools. For this adoption to translate into results, organizations need to previously define their objectives, prepare data and establish governance and measurement mechanisms.
The report also notes that sustainable AI adoption requires addressing issues such as security, regulatory compliance, and data quality from the early stages of projects. These issues become even more relevant as companies move from experimentation to large-scale deployment.
The research was conducted by Coleman Parkes on behalf of Rebura in May 2026. A total of 300 organizations were surveyed – from small businesses to medium and large corporations – that were carrying out AI initiatives and were based in France, Germany, Italy, Spain and the United Kingdom. Participants are from 11 different sectors, including technology, professional services, financial services, manufacturing and healthcare. The organizations have, on average, 2,494 employees and annual revenues of £3.27 billion. Respondents’ positions include IT operations managers, digital transformation managers, and IT infrastructure managers.
