Artificial intelligence (AI) continues to captivate businesses worldwide, promising transformative benefits across industries. However, a recent comprehensive report by Red Hat reveals a substantial gap between AI investments and the tangible customer value delivered. According to the study, 89 percent of businesses have yet to realize significant customer value from their AI initiatives, despite anticipations of a 32 percent increase in AI spending by 2026.
Introduction: The Growing Investment in AI and Its Challenges
Artificial intelligence investment is soaring globally as organizations seek competitive advantages through automation, enhanced analytics, and innovative product development. In the UK, AI is emerging as a top priority alongside cybersecurity, highlighting a strategic focus on technology-driven resilience.
The Red Hat survey of UK enterprises underscores this trend by identifying AI and security as the joint top IT priorities over the next 18 months, with 62 percent of respondents emphasizing their critical importance. Following closely are hybrid and multi-cloud strategies and virtualization, which reflect how businesses are architecting their IT infrastructures to support AI effectively.
Key Barriers Limiting AI Adoption and Value Realization
Despite the enthusiasm, the path to successful AI integration faces multiple obstacles. The survey highlights the primary challenges that limit AI’s impact:
- High implementation and maintenance costs: Cited by 34 percent of respondents, these financial burdens hinder wider AI adoption.
- Data privacy and security concerns: 30 percent of organizations identify these issues as significant barriers, especially as AI workloads expand.
- Integration difficulties: Nearly 28 percent struggle to incorporate AI solutions effectively within existing systems and workflows.
Adding complexity is the widespread phenomenon of “shadow AI”, where 83 percent of businesses reported unauthorized use of AI tools by employees. While such grassroots adoption illustrates AI’s appeal and potential, it also raises concerns about security, governance, and productivity alignment.
The Growing Role of Open Source in AI Strategy
To navigate these challenges, UK organizations increasingly embrace open source software, recognizing its benefits for AI development. The Red Hat survey found that 84 percent of respondents regard enterprise open source as essential for their AI strategy. This sentiment extends to other critical IT domains, including virtualization, hybrid and multi-cloud deployment, and security.
Joanna Hodgson, UK Country Manager at Red Hat, observes that this divide between AI ambition and business reality can be bridged by leveraging open-source technologies. She notes, “Openness fosters collaboration, facilitates sharing of best practices, and provides the necessary flexibility for evolving AI solutions. Like hybrid cloud deployments, open source forms the foundation for scalable and reusable AI systems.”
Real-World Applications and Trends
The survey also reveals prioritized AI use cases—most notably, agentic AI, which refers to autonomous AI systems capable of independent decision-making. Around 68 percent of businesses view agentic AI as a top investment area, underscoring a shift toward more sophisticated AI capabilities.
Moreover, organizations emphasize enabling broad employee adoption of AI tools and operationalizing AI technologies within daily business functions to maximize ROI.
The Persisting AI Skills Gap
A consistent hurdle is the shortage of skilled AI professionals. For the second consecutive year, AI skills are the most urgent concern among IT leaders, particularly in areas requiring expertise in agentic AI, efficient AI utilization, and educating enterprise teams on AI adoption.
This talent gap impedes the scaling of AI projects from pilots to production-grade applications. Complementary investments in training and hiring remain critical to unlock AI’s full potential.
UK’s Outlook on the Global AI Landscape
Despite these challenges, there is robust optimism regarding the UK’s AI leadership prospects. An overwhelming 83 percent of survey respondents believe that the UK is either already a global AI powerhouse or is poised to become one within the next three years.
However, persistent barriers include:
- Insufficient talent pipeline
- Limited public funding
- Inadequate private sector engagement
These factors constrain the nation’s ability to fully harness AI’s economic and societal benefits.
Complexities of Cloud and AI Workload Integration
Cloud adoption, a cornerstone for modern AI deployment, faces additional complexity due to AI workloads. Organizations encounter:
- Operational silos limiting cross-functional collaboration
- Data sovereignty and compliance concerns
- Unclear return on investment and cost management challenges
In response, enterprises prioritize operational control, IT autonomy, security of the software supply chain, and maintaining flexibility in vendor selection.
Hans Roth, Senior Vice President and General Manager for EMEA at Red Hat, explains, “Businesses seek resilient and adaptable IT environments amid constant disruption. Sovereignty and transparency are at the forefront of cloud and AI strategy, with open source playing a pivotal role in enabling rapid innovation without compromising control.”
Conclusion: A Pragmatic Path Forward for AI Value Realization
The Red Hat report presents a snapshot of the current AI landscape—characterized by high expectations but tempered by implementation challenges. The high prevalence of shadow AI and integration obstacles highlights the need for stronger governance and strategic alignment.
The increasing reliance on open-source solutions signals a pragmatic and collaborative approach, offering businesses the agility and transparency needed to translate AI investment into real-world customer value. Addressing the persistent skills gap, clarifying cloud integration strategies, and promoting inclusive AI adoption across organizations will be critical to unlocking AI’s transformative promise.
Key Takeaways:
- 89% of businesses currently do not derive significant customer value from AI, despite rising investment.
- AI and cybersecurity are co-top IT priorities, illustrating a dual focus on innovation and protection.
- High costs, data security, and integration issues remain primary barriers.
- Shadow AI’s rise points to a disconnect between IT strategy and employee practices, creating risks and inefficiencies.
- Open-source technology emerges as a cornerstone for scalable and flexible AI adoption.
- The AI talent shortage threatens to stall projects, emphasizing the need for education and training.
- UK businesses are optimistic about national AI leadership but face funding and talent hurdles.
- Cloud strategies require enhanced focus on sovereignty, control, and supply chain security.
As AI continues to evolve, the alignment of technology, people, and processes will be pivotal in transforming investment into measurable value.