IBM Infrastructure Profit Soars 53% on AI and z17 Mainframe Demand

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IBM’s Infrastructure segment profit grew 53% year-over-year in Q4 driven by stronger AI, hybrid cloud and z17 mainframe adoption. The company also unveiled its Enterprise Advantage consulting service for scaling agentic AI platforms and launched an IBM watsonx Orchestrate partnership with e& for governance and compliance.

1. IBM Partners with e& to Deploy Enterprise-Grade Agentic AI

At the World Economic Forum in Davos, IBM and global technology group e& unveiled an agentic AI solution built on IBM watsonx Orchestrate, embedding over 500 domain-specific tools into e&’s core governance, risk and compliance systems. A joint proof of concept, delivered in just eight weeks by IBM’s Client Engineering team and Gulf Business Machines, demonstrated end-to-end reasoning, traceable responses and 24/7 self-service access. Integration with IBM OpenPages and watsonx.governance ensures that every decision follows pre-configured policy controls, positioning this as one of the earliest enterprise-grade agentic AI implementations in the Middle East and Europe.

2. IBM Launches Enterprise Advantage Service to Scale Agentic AI

IBM Enterprise Advantage, announced January 19, 2026, combines IBM’s internal AI-powered delivery platform, IBM Consulting Advantage, with reusable AI assets and a secured governance framework. Having already supported more than 150 client engagements and driven a 50% uplift in consultant productivity, the service lets organizations build custom AI platforms on existing cloud and infrastructure investments—whether AWS, Azure, Google Cloud or IBM watsonx—without overhauling their architecture. Early adopters such as Pearson and a leading manufacturer have used the service to identify high-value use cases, launch targeted prototypes and deploy governed AI assistants at scale.

3. IBM Study Indicates AI Investment Shift toward Innovation by 2030

New research from the IBM Institute for Business Value, based on a survey of 2,007 C-suite executives, finds that 79% expect AI to contribute significantly to revenue by 2030—up from 40% today—yet only 24% have clarity on those revenue sources. Respondents predict a 150% increase in AI investment between now and 2030, with 62% of spend dedicated to innovation versus 47% today on efficiency. AI-driven productivity is projected to rise by 42%, and 67% of executives anticipate AI will remove current resource and skills constraints. Despite 82% expecting multi-model capabilities and 72% foreseeing small language models surpassing large ones, only 28% have a clear model roadmap for the decade ahead.

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