IBM positions hybrid cloud and governance as the backbone of enterprise AI at scale

A widening chasm separates enterprise AI intentions from execution. According to Deloitte research, 54% of organizations intend to shift at least 40% of their AI projects into production within six months, yet merely 25% have achieved this milestone today. IBM is positioning itself to bridge this gap by drawing on its core competencies—mainframe infrastructure, hybrid computing capabilities and established governance frameworks—to differentiate itself in a crowded market.

Dave Vellante, analyst at theCUBE Research, sees IBM's strategy as distinctive. "In our opinion, IBM has found a differentiated path in enterprise AI by productizing workflow-level outcomes across a stack that, while sometimes confusing, customers generally trust," he said. "Client Zero proof, a workload-first hybrid design, durable platforms reimagined for agents and a pragmatic quantum roadmap create a credible basis for sustained advantage."

Building toward an enterprise AI operating model

IBM's generative AI business has grown substantially. The company reported AI-related software sales and consulting work totaling more than $12.5 billion in Q4 2025, compared to $9.5 billion in the prior quarter. Through strategic acquisitions, partnerships and product rollouts, IBM is assembling capabilities organized around four pillars: agent orchestration, trusted data, intelligent operations and governance.

A series of announcements leading up to IBM Think 2026 in May showcased this strategy. In February, IBM partnered with Deepgram Inc. to add voice functionality to watsonx Orchestrate, its platform for constructing, launching and overseeing AI agents. Two months later, IBM Bob—an AI-powered development assistant for planning, coding, testing, modernizing and deploying applications—became available globally.

IBM finalized its acquisition of Confluent, a data streaming platform, in May 2026 to strengthen watsonx.data. By incorporating streaming and real-time data capabilities, IBM aims to establish watsonx.data as a trusted data layer that furnishes AI agents with constantly refreshed context.

At Think 2026, IBM transformed Concert from a standalone product into an agentic IT operations platform designed to consolidate observability, optimization, security and automation across hybrid infrastructures. This repositioning establishes Concert as the intelligent operations component of IBM's wider enterprise AI strategy.

The IBM Sovereign Core platform, unveiled at Think 2026, addresses the governance pillar. It enables enterprises to construct and operate AI-ready sovereign environments by integrating governance, compliance and operational control into the infrastructure layer itself.

June brought additional announcements: IBM joined OpenAI's Daybreak Cyber Partner Program to detect AI-driven cybersecurity risks, and partnered with Google Cloud to assist IBM consultants in designing, constructing and governing enterprise-scale agents on Google Cloud infrastructure.

These moves reveal IBM's ambition to become the comprehensive platform for enterprise AI. The company is investing heavily in new capabilities while capitalizing on its reputation for trusted enterprise security and governance. John Furrier, also from theCUBE Research, frames the central question: "While others chase frontier models, IBM is betting on something harder: trusted AI in production," he told theCUBE. "The question coming out of Think is simple — are they becoming the system of record for enterprise AI or just another layer in the stack?"

IBM's legacy infrastructure finds new relevance in the AI era

During a media briefing before Think 2026, IBM Chief Executive Arvind Krishna highlighted a critical fact: over 70% of enterprise data remains stored in on-premises systems. This reality makes hybrid cloud essential to IBM's enterprise AI operating model, enabling organizations to leverage internal data for AI workloads while preserving their existing infrastructure investments.

Recent financial results validate IBM's hybrid cloud strategy. Red Hat Inc., whose OpenShift Kubernetes platform forms the foundation of IBM's hybrid cloud software offerings, achieved 13% year-over-year revenue growth. IBM Z, the company's mainframe line, posted 51% year-over-year revenue growth, demonstrating the enduring relevance of mainframes in IBM's infrastructure business.

IBM is embedding AI capabilities directly into IBM Z mainframes to handle intensive AI workloads. Ric Lewis, senior vice president of the Infrastructure Division at IBM, noted this approach has driven 20%-30% program-to-program growth for nearly a decade. Z mainframes represent a crucial option for enterprises seeking to deploy AI while retaining control of their data and systems, and they form a cornerstone of IBM's sovereignty strategy.

"Sovereignty is our home court. We do 70% of the world's financial transactions," Lewis told theCUBE. "The most important data that travels around the world is in our Z systems. Those are sovereign systems. They're on-prem, they're in environments, they're in banks, they're in financial institutions, they're in insurance. Sovereign is our home court, and we know this space extremely well."

Sovereignty becomes a prerequisite for enterprise AI

IBM's sovereignty vision centers on customer control: maintaining critical data and AI workloads in environments that customers own and manage, rather than relying entirely on external infrastructure. Javier Olaizola, global managing partner for hybrid cloud and data at IBM Consulting, observes that sovereignty discussions are occurring earlier in client conversations.

"Sovereignty and exposure was coming in on slide 40 in a PowerPoint pitch," he told theCUBE. "Now it's coming up front: 'How much is my exposure?' That is coming up with a new set of conversations that we are having with clients."

Sovereign Core represents IBM's response to these concerns, according to Sripriya Srinivasan, general manager for Core and ALM software products at IBM. The platform aims to help organizations maintain operational consistency as AI regulations and geopolitical circumstances evolve. It also addresses the challenge of managing widespread AI agent deployment.

"The proliferation of agents is real in enterprises. Everybody is starting to build agents," Srinivasan told theCUBE. "How do you, as a [chief information officer], make sure that there's a level of standardization, consistency, governance, orchestration? All of these are internal fears, not necessarily coming, just based on regulations."

Putting the enterprise AI operating model to work

Krishna articulated IBM's perspective on successful enterprise AI strategy during Think 2026: "The enterprises pulling ahead are not deploying more AI; they're redesigning how their business operates."

IBM applies this philosophy to itself, treating the company as Client Zero for its enterprise AI strategy. James Kavanaugh, senior vice president and chief financial officer of IBM, explained the scope of integration: "AI is now embedded across our business, from how we deliver services to our software portfolio to the capabilities we are adding to our infrastructure platforms and how we drive our own productivity."

The results are measurable. More than 80,000 IBM employees use IBM Bob, with users reporting a 45 percent increase in productivity. IBM Consulting has deployed more than 4,000 digital workers across 450 active projects, drawing from agents built with watsonx, Anthropic PBC and OpenAI Group PBC.

Managing this digital workforce requires a distinctive approach. Mohamad Ali, senior vice president and head of IBM Consulting, described how the company treats AI agents similarly to human employees. "Arvind called me, and we had a conversation about three years ago, and he said, 'I want you to come over, and I want you to be a consulting business,'" Ali recalled. "'What is digital labor? It's a whole bunch of bits of software. I need you to come in, and I need you to build this set of software and do it in a way that it could be managed. You could think of this as HR management … but now you have to HR manage human workers and digital workers.'"

IBM customers are adopting comparable approaches. Global bank BNP Paribas SA operates nearly 1,000 AI use cases across its organization, employing a group-level framework with governance responsibilities distributed among business units and functions.

"The strategy is to use AI, not to become AI — to use AI to better serve our customers and to give more value to them," Jean-Michel Garcia, group chief technology officer at BNP Paribas, told theCUBE. "But also internally, for employees, to give them more capabilities to focus on the right set of tasks and to make them more efficient and more focused on what they do."