Enterprise AI Value Gap: Why Only 5% of Companies Are “Future-Built” | AppDevAngle

In this theCUBE Research interview, Paul Nashawaty (Practice Lead & Principal Analyst, Application Development) sits down with Kevin Camel (Head of Product Management for AI, Mirantis) to unpack why only 5% of global enterprises are “future-built”—and what separates the organizations turning AI into measurable business outcomes from everyone stuck in pilot mode.
They dig into the enterprise AI skills gap, why AI infrastructure is fundamentally different from traditional IT, and how organizations should think about platform strategy, GPU economics, data protection, and operational readiness as AI becomes a board-level priority.
Key highlights (fast takeaways):
Why “AI value” is hard to prove, and why the moment feels like the early internet era
The shift to purpose-built AI infrastructure (GPUs, high-performance networking, specialized storage)
Why the real constraint is talent and platform expertise, not just hardware budgets
Agentic AI’s growing share of enterprise value (and what it implies for IT strategy)
Security and governance risks: AI-generated data protection gaps + emerging agent protocols (e.g., MCP)
How AIOps/event intelligence supports human-in-the-loop operations at scale
Where to assess maturity: Mirantis’ AI readiness assessment and maturity model


00:00 - Intro
00:07 - Strategic AI Adoption and Its Role in Business Competitiveness: Featuring Insights from Kevin Kamel and Mirantis
02:19 - Bridging the Gap: Demonstrating AI's Value within Traditional IT Frameworks
05:41 - Specialized Hardware and AI Technology
09:41 - Strategic Investments for Future Competitiveness
11:55 - Navigating the Future: Bridging Skills Gaps and Mitigating AI Security Risks
14:33 - Operational Efficiency and Human in the Loop
18:15 - Advancing AI Understanding and Future Insights