Most companies have spent the last two years experimenting with AI. They built chatbots, automated a report here, sped up a process there. Some of it worked. Very little of it scaled.
A March 2026 survey of enterprise technology leaders found that 78% of companies have AI pilot projects running, but fewer than 15% have successfully moved those projects to full production. A separate study from MIT found that 95% of AI pilot programs have produced no measurable financial return. The money is being spent. The results are not materializing.
The reason is not the AI models themselves. The failures come from what surrounds them: the inability to manage who has access to what data, the difficulty of applying consistent security rules across dozens of separate AI projects, and the challenge of proving to auditors and regulators that the system is behaving correctly. These are exactly the problems that get ignored when you are building a small pilot but become urgent when you try to run something at real scale.
This is the exact problem Microsoft and Red Hat walked into Red Hat Summit 2026 to address. Their pitch was simple: stop building separate systems for each AI project, and run everything on a single managed platform that has governance, identity control, and compliance built in from the start.
The platform they are selling is Azure Red Hat OpenShift, a jointly operated cloud service that has existed in some form since 2018 but has been significantly repositioned at this summit. What is new is not the technology but the framing. Microsoft and Red Hat are now selling it as the operating layer for enterprise AI, not just a way to run software in the cloud.
The strongest proof point is Banco Bradesco, one of the largest banks in Latin America, with around 74 million customers. Bradesco has built its entire AI operation on this platform, unifying governance across more than 200 separate AI initiatives. Their AI assistant, BIA, handles billions of transactions daily. The bank's internal audit team also used Azure AI tools to improve audit planning efficiency by 65%. This is not a pilot. It is a production system that touches the core of a heavily regulated bank.
A second example, Dutch fintech firm Topicus, deployed its Akkuro lending platform in Microsoft's Switzerland data center specifically because Swiss regulations require customer financial data to stay inside the country. That single fact matters enormously for any company operating across multiple countries with different data laws, and it is increasingly the norm rather than the exception.
At the same time, a separate and very large number of enterprises are actively looking to move away from VMware, the software that most large companies have used to run their internal systems for the past two decades. When Broadcom acquired VMware and restructured its pricing, many customers saw their costs increase by 100% to over 1,000%. Gartner estimates that 35% of VMware workloads will migrate to alternative platforms by 2028. OpenShift Virtualization, which lets companies run their old-style systems and new AI workloads side by side without rebuilding everything from scratch, is now one of the most serious alternatives.
These two trends are colliding. The VMware migration pressure and the AI production pressure are driving companies toward the same conclusion: they need one platform that handles both, with a single support contract and a single governance framework.
Microsoft and Red Hat are betting that enterprises will choose a pre-integrated, jointly supported platform over building their own stack from separate pieces. For industries like banking, insurance, healthcare, and manufacturing, where regulators want clear audit trails and data residency guarantees, that bet looks increasingly sound. The organizations that figure out the governance layer first will be the ones that can actually run AI at scale. Everyone else will keep restarting pilots.