Why Many AI Investments Are Falling Short of Expectations
346Many companies are pouring huge amounts of money into artificial intelligence, but most aren’t seeing the results they hoped for. A recent report from Red Hat shows that nearly 9 out of 10 organizations haven’t achieved real value from their AI projects. Despite the hype and investment, AI still faces many hurdles before it can deliver on its promises.
Challenges in Integrating AI into Business Systems
One of the biggest issues companies face is how difficult it is to incorporate AI into their existing systems. The process can be complex and costly, with many organizations citing high expenses for both implementation and ongoing maintenance. These costs make it hard for businesses to see quick or obvious benefits from their AI efforts.
Data privacy and security are also major concerns. Many organizations struggle to find ways to safely and effectively connect AI tools with their current data systems. Nearly a quarter of the companies surveyed reported difficulties in this area, which slows down AI adoption and limits its potential impact.
The Hidden Threat of Shadow AI
A surprising finding from the report is the rise of “shadow AI” — when employees use unauthorized AI tools without approval from IT departments. This practice can create security risks and lead to inefficiencies, as these tools often operate outside formal controls. Shadow AI highlights the gap between what companies want to achieve and what employees are actually doing.
This trend also raises questions about how organizations can better manage AI use and ensure security while encouraging innovation. Without proper oversight, shadow AI could undermine efforts to build secure and reliable AI systems.
The Role of Open Source and Future Outlook
To overcome some of these hurdles, many UK organizations are turning to open source software. A large majority of surveyed companies believe that open source is crucial for their AI strategies. Open source allows for collaboration, sharing best practices, and more flexibility, which can help accelerate AI development and adoption.
Joanna Hodgson from Red Hat explains that there is a clear gap between companies’ ambitions and their actual results. She emphasizes that openness and collaboration are key to making AI more accessible and reusable, much like how hybrid cloud solutions have become successful. This approach could be vital in transforming the AI landscape in the coming years.
What Areas Are Companies Prioritizing?
The survey also looked at what specific AI technologies companies are focusing on. Agentic AI — which involves systems capable of operating with a high level of autonomy — is the top priority for most organizations. This type of AI can make decisions and act independently, which has great potential but also presents challenges.
Other priorities include helping employees adopt AI tools more broadly and finding ways to turn AI into a practical part of everyday operations. However, a major obstacle remains: there is a skills gap. Many companies struggle to find talent with the right expertise, especially in advanced AI areas like agentic AI and educating staff on how to use these new tools effectively.
Despite these challenges, there is a positive outlook. Most respondents believe the UK is well-positioned to become a leader in AI innovation. They see promise in overcoming current hurdles through collaboration and open-source solutions, which could help unlock the true potential of AI in the future.
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