Enterprise AI survey: ambition, the value gap, and the importance of open source

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2025-10-09 ~1 min read www.redhat.com #kubernetes

⚡ TL;DR

Enterprise AI survey: ambition, the value gap, and the importance of open source About the author Hans Roth More like this Blog post Blog post Original podcast Original podcast Browse by channel Automation Artificial intelligence Open hybrid cloud Security Edge computing Infrastructure Applications Virtualization Share EMEA organizations are primed for widespread AI adoption, and see enterprise open source as an important success factor; however, their ability to scale is challenged by skills gaps, high costs and shadow AI. That’s the headline finding of our latest survey of over 900 IT leaders and AI engineers in nine countries 1.

📝 Summary

Enterprise AI survey: ambition, the value gap, and the importance of open source About the author Hans Roth More like this Blog post Blog post Original podcast Original podcast Browse by channel Automation Artificial intelligence Open hybrid cloud Security Edge computing Infrastructure Applications Virtualization Share EMEA organizations are primed for widespread AI adoption, and see enterprise open source as an important success factor; however, their ability to scale is challenged by skills gaps, high costs and shadow AI. That’s the headline finding of our latest survey of over 900 IT leaders and AI engineers in nine countries 1. According to the survey AI is a core strategic priority for 72% 2 of organizations in Europe, the Middle East, and Africa, and they have plans to increase their AI investments by an average of 32% by 2026 3. The focus on AI is clear, yet the data also reveals a stark gap between ambition and reality: only 7% of organisations report “driving customer value” at scale from their AI investments today 4. This is a crucial challenge for leaders who need to translate significant investment into tangible business outcomes. So what is preventing organisations moving from small-scale pilots to enterprise-wide value? Tackling the barriers to scale AI Our survey data outlines the extent of the talent shortage faced, with 70% of respondents agreeing there is an urgent AI skills gap 3. The most significant gaps cited by those respondents are in the practical application of AI, such as connecting AI to enterprise data (49%), and making efficient use of AI capabilities (48%). Nearly as many (47%) report difficulty educating the business to use AI effectively, which complicates organisation-wide adoption. As the role of AI in the workplace is established, another layer of complexity emerges. ‘Shadow AI’, the use of unsanctioned AI tools by employees, is becoming a significant challenge to effective governance and scalable adoption. The vast majority of responding EMEA organisations (91% 5 ) admit their organisation is experiencing a shadow AI problem. This should serve as a wake-up call: AI is being adopted with or without IT teams’ authorisation.