A new Red Hat report highlights a reality check for the AI boom: despite record investment, 89% of businesses say they’ve yet to see measurable customer value from their AI initiatives.
Yet optimism hasn’t faded. Companies expect to increase AI spending by 32% by 2026, hoping that the right mix of open-source tools, hybrid cloud infrastructure, and talent development will finally turn experimentation into impact.
AI and Security Dominate IT Agendas
The survey found that AI and cybersecurity are now the joint top technology priorities for UK organizations over the next 18 months, with 62% of respondents naming them as critical focus areas. Right behind them: hybrid and multi-cloud strategies, along with virtualization—showing that businesses see AI not as an isolated tool, but as part of a larger modernization push.
Barriers to Adoption: Cost, Privacy, and Integration
Despite the enthusiasm, most organizations face real obstacles. The high cost of AI implementation and maintenance topped the list of concerns (34%), followed by data privacy and security risks (30%) and challenges integrating AI with legacy systems (28%).
This aligns with a broader pattern seen across industries: AI pilots are easy to start but hard to scale.
The Rise of “Shadow AI”
Perhaps the most eye-opening finding is the scale of “shadow AI”—where employees use unauthorized AI tools outside company policy. A staggering 83% of organizations reported this happening internally.
While shadow AI often comes from employees trying to work more efficiently, it introduces major security and compliance risks. The trend underscores a disconnect between top-down AI strategies and how teams are actually using the technology day-to-day.
Why Open Source Is Gaining Momentum
To regain control and accelerate trustworthy adoption, many organizations are turning to enterprise open source.
Red Hat found that 84% of respondents consider open source vital to their AI strategy—both for flexibility and cost efficiency. The same sentiment extends to virtualization and hybrid cloud adoption, suggesting that openness and interoperability are now seen as strategic advantages.
Joanna Hodgson, UK Country Manager at Red Hat, summarized it well:
“There’s a clear gap between ambition and reality. Companies are investing heavily in AI, but few are seeing real value. The key will be enterprise integration and collaboration—areas where open-source principles can make AI more usable and scalable.”
Agentic AI Tops the Priority List
When asked about specific focus areas, “agentic AI”—systems capable of operating with a high level of autonomy—ranked as the top priority for 68% of respondents. Following that came enabling broad employee adoption and operationalizing AI into production environments.
The Talent and Education Bottleneck
The AI skills gap continues to be one of the biggest roadblocks. For the second year in a row, AI ranked as the area with the most urgent talent shortage. The gaps are widest in agentic AI, AI utilization efficiency, and training non-technical employees to work alongside AI systems.
Without a stronger talent pipeline and internal education, even the best technology investments risk stagnation.
Confidence in the UK’s AI Potential — With Caveats
Despite the hurdles, optimism runs high: 83% of UK respondents believe the country either already is or soon will be a global AI leader. But that confidence is tempered by familiar issues—limited public funding, a shallow talent pool, and insufficient private-sector collaboration.
Cloud Complexity Adds Another Layer
The integration of AI into hybrid and multi-cloud environments is also proving difficult. Many businesses report internal silos, data sovereignty concerns, and unclear ROI from cloud transitions.
Hans Roth, SVP and GM for EMEA at Red Hat, noted that organizations are increasingly prioritizing control, resiliency, and sovereignty in their IT strategies:
“Open source provides the transparency and flexibility needed to innovate rapidly without compromise. It’s becoming central to how enterprises adapt to disruption.”
The Bottom Line
The report paints a picture of a market still in the “early industrial revolution” phase of AI—flush with investment and experimentation, but struggling with the hard work of integration, governance, and education.
If open-source adoption continues to accelerate, it may help close the gap between lofty AI ambitions and practical business value. For now, though, most organizations remain stuck in the experimentation phase—eagerly waiting for the payoff that’s yet to arrive.
