en.Wedoany.com Reported - IBM is positioning itself as a foundational player in the enterprise artificial intelligence (AI) space. Leveraging its mainframe hardware, hybrid computing assets, and a strong governance legacy, the computing giant has entered the core of AI infrastructure discussions. Dave Vellante of theCUBE Research noted in his analysis that these advantages place IBM at the center of enterprise AI conversations.

"We believe IBM has found a differentiated path to enterprise AI by productizing workflow-level outcomes across the entire technology stack," Vellante said in a recent analysis. "This stack, though sometimes confusing, is broadly trusted by customers. Client Zero validation, a workload-first hybrid design, a durable platform reimagined for agents, and a pragmatic quantum roadmap lay a credible foundation for sustained advantage."

At IBM Think 2026, theCUBE (SiliconANGLE Media's live studio) conducted exclusive interviews. Furrier and Vellante spoke with industry experts from IBM and BNP Paribas, discussing how organizations can effectively integrate AI agents into workflows, the characteristics required for effective hybrid AI governance, and successful AI deployment cases in large global enterprises.

As enterprises seek trusted infrastructure to support AI use cases, IBM's mainframe platform, IBM Z, has seen strong growth. Ric Lewis, Senior Vice President of IBM's Infrastructure division, discussed this trend in theCUBE coverage. "It couldn't be more interesting right now. This industry is the most exciting period of my career. Every board is discussing: 'What are you doing with AI? What's the plan? What's the underlying infrastructure?' In just the last 18 months, with the development of agent technology and the speed at which it's changing everything, the conversation has fundamentally shifted," Lewis said. He noted that as AI projects move from experimentation to production, enterprises need trusted systems—an area where IBM has a clear advantage. "Sovereignty is our home turf. We handle 70% of the world's financial transactions. The world's most important data flows through our Z systems. These are sovereign systems, deployed on-premises, across various environments, in banks, financial institutions, and insurance companies. We know this space very well."

As enterprise leaders consider governing an increasingly digital workforce, they can draw lessons from managing human employees. IBM CEO Arvind Krishna instructed Mohamad Ali, Senior Vice President and Head of IBM Consulting, to treat the digital workforce as manageable software components, akin to human resource management, overseeing both human and digital employees. "About three years ago, Arvind called me and said: 'I need you to come in, build this set of software, and do it in a manageable way. Think of it like HR management... but now you need to manage both human employees and digital employees,'" Ali said in a theCUBE interview. This model has been implemented within IBM Consulting, which relies on a general management layer to deploy and manage over 4,000 digital employees across 450 active projects, including agents from IBM watsonx, Anthropic, and OpenAI. The management layer can track agent utilization and shut down agents that don't create value. "If you build an agent that nobody uses, eventually we'll retire it. It will 'starve,' won't get tokens, and will be retired," Ali said. AI agents can be tested, rated, and certified for core skills. Ali noted that IBM Consulting saw a 20% year-over-year profit increase from 2024 to 2025. "We manage $25 billion in spending and have actually saved $4.5 billion of that. This happened because we broke the company down into 490 workflows, selected 70, redesigned them, and implemented them."

The speed and scale of AI innovation have created a noisy partner ecosystem, including hyperscalers, cloud providers, software vendors, and more. Jason Kelley, Global Core Business Applications Lead and Managing Partner at IBM Consulting, emphasized that IBM Consulting has a unique advantage in helping enterprises achieve a healthy balance. "The challenge we face is ensuring partners can collaborate effectively for a specific client, industry, or sovereign network. That's where we come in—as the conductor of this collaboration." The IBM Sovereign Core platform, announced at Think 2026, is designed to embed governance and compliance controls directly into the infrastructure runtime. Javier Olaizola, Global Managing Partner for Hybrid Cloud and Data at IBM Consulting, explained that this helps address risk exposure, control, and business model alignment. "Sovereignty and risk exposure are usually slide 40 in a PowerPoint presentation. Now it's being brought to the forefront—'How much risk am I exposed to?' This creates a new conversation." Olaizola added that enterprises benefiting most from AI think strategically about the business outcomes AI helps drive. "AI is now putting significant pressure on clients to reflect on actual value and rethink their business models from first principles. The winners in the market are those truly realigning their entire operating model around AI."

Organizations no longer view AI governance solely as a data sovereignty issue. Sripriya Srinivasan, General Manager of IBM Core and ALM Software Products, noted that there is also an operational sovereignty issue, including who runs the platform, where the control plane is, and who holds the keys. "It comes down to two things: control and independence. It's not that enterprises are trying to replicate becoming a technology vendor or chip hardware supplier. That's not the focus. They want operational resilience, ensuring the business is always operable." Srinivasan said the IBM Sovereign Core platform is designed to help address these issues, providing enterprises with a way to govern the proliferation of agents across departments. "The proliferation of agents within enterprises is real. Everyone is starting to build agents. As a CIO or CTO, how do you ensure a certain level of standardization, consistency, governance, and orchestration? These concerns stem from internal needs—not just regulatory requirements."

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