At the World Economic Forum in Davos on January 19, 2026, IBM announced a strategic collaboration with global technology group e& to embed agentic AI into e&’s core governance, risk and compliance systems. Powered by IBM watsonx Orchestrate—which offers over 500 customizable, domain-specific agents—the solution integrates natively with IBM OpenPages and the broader watsonx portfolio to deliver clear, traceable, action-oriented responses aligned with enterprise controls. A joint proof of concept, delivered in just eight weeks by IBM’s Client Engineering team alongside Gulf Business Machines and e&, demonstrated the system’s ability to operate at real-world scale, enabling employees and auditors to access and interpret legal and regulatory data more quickly. This marks one of the region’s first enterprise-grade agentic AI deployments, reinforcing IBM’s leadership in governed AI for mission-critical applications.

On January 19, 2026, IBM introduced Enterprise Advantage, an asset-based consulting service designed to help clients build, govern and operate internal AI platforms at scale. Leveraging technology from IBM Consulting Advantage—already proven in more than 150 client engagements to boost consultant productivity by up to 50%—the service provides a secured platform, shared standards and a marketplace of reusable AI assets. Organizations such as Pearson have used Enterprise Advantage to combine human expertise with agentic assistants, while manufacturing clients have deployed multi-technology AI assistants in governed environments. The offering supports existing cloud, model and infrastructure investments, enabling companies to accelerate AI-driven innovation without disrupting their current ecosystems.

A new report from the IBM Institute for Business Value, based on a survey of 2,007 C-suite executives across 33 geographies and 20 industries, finds that 79% expect AI to significantly contribute to revenue by 2030—up from 40% today—yet only 24% have clarity on revenue sources. Respondents foresee a shift in AI investment from 47% on efficiency today to 62% on innovation by 2030, driving a projected 42% increase in productivity and fueling reinvestment for growth. Executives anticipate a 150% surge in AI spending over the next five years, with 67% expecting AI to eliminate resource and skills constraints. The study highlights gaps in AI model strategy—only 28% have a clear view of required models—and predicts that multi-model AI capabilities and small language models will dominate by 2030.