From July 15 to July 16, enterprise and technology leaders gathered at the Signia by Hilton in San Jose for the Momentum AI 2025 Summit, hosted by Reuters Events. The two-day event attracted more than 500 senior decision‑makers—including CIOs, CTOs, CDOs, CISOs, and other executives—from leading global organizations. They convened to confront the complex challenge of scaling AI initiatives beyond pilots, focusing on strategy, governance, return on investment (ROI), and cross-functional collaboration.
Momentum AI distinguished itself by shifting away from speculative or research-heavy discussions. The agenda was firmly rooted in applied AI—specifically the operational, ethical, and financial considerations associated with enterprise-level deployment. Primary themes included AI implementation strategies, robust data governance frameworks, realistic ROI models, seamless system interoperability, and collaborative leadership models.
Crucially, the summit featured two high-stakes co-located forums: the invitation-only CIO Forum on July 15 and the AI Risk Forum on July 16. The former provided a discreet environment for about 30 top-tier CIOs—including CTOs and board-level counterparts from JLL, NRG Energy, and Stanford HAI—to exchange candid, peer-backed insights into AI adoption tactics and benchmarks. The subsequent AI Risk Forum convened CISOs, legal counsel, and risk officers to explore synthesizing security, legal, and operational standards in mitigation of AI risks.
The summit opened with an executive interview featuring Stanford HAI Director Russell Wald and Reuters Technology Correspondent Jeffrey Dastin, who contextualized AI’s accelerating role in 2025, highlighting its implications across regulation, investment, and geopolitical strategy. A pivotal panel entitled “Aligning Board Vision with AI’s Transformative Potential” brought together Yao Morin (CTO, JLL), Franziska Bell (Chief Data, AI & Analytics Officer, Ford), and Cencora’s Pawan Verma. Moderated by U.S. Chamber of Commerce VP for Tech, Data & AI, Dr. Denise Turley, the session revealed executives’ strategies for integrating AI literacy at the board level—emphasizing education, transparency, and framing AI as a key driver of innovation while safeguarding against risks.
A follow-up discussion on “Integrating and Scaling AI to Drive Enterprise‑Wide Transformation” featured Dak Liyanerachchi (Chief Data & Technology Officer, NRG Energy), Swarup Pogalur (Managing Director, CTO Digital & AI Engineering, Wells Fargo), and Armand Ruiz (VP, IBM AI Platform), moderated by KPMG’s Rahsaan Shears. They detailed the strategies their organizations are using to upskill teams, enforce data governance, and enhance cross-departmental collaboration—all in service of scaling AI beyond isolated projects.
A standout fireside chat, “The Great AI Crossroads: Open Highways vs. Walled Gardens,” challenged CIOs and architects to weigh infrastructure choices with David Flynn, CEO of Hammerspace, and Eric Kavanagh, CEO of The Bloor Group. They argued that open, Linux-native data fabrics—decoupled from proprietary stack lock-in—offer enterprises greater flexibility and operational scalability as AI becomes embedded across business domains.
Much of the second day targeted ROI and cost efficiency. A panel titled “Demonstrating Measurable ROI from AI Initiatives” featured executives from AGCO, Corteva Agriscience, and Cardinal Health, chaired by Edward Jones’ Hasan Malik. Presenters underscored that AI must be measurable—to be viable. They shared best practices for tracking KPIs such as cost reduction, revenue enhancements, and productivity improvements.
Concurrent workshops illustrated specific enterprise use cases, from Google-led demos of AI agents improving workforce productivity, to TDK’s smart factory strategies powering next-gen Industry 4.0.
Organizers integrated ethics and risk conversations via the AI Risk Forum and main-stage conversations. Speakers from Deloitte, ITU, and IBM emphasized bias detection frameworks, fairness audits, and secure development pipelines. Across sessions, scholars and risk officers reiterated that without these systems, AI risks suppress ROI and erode public trust.
While enterprise automation has often prioritized predictive models and narrow AI, Momentum AI spotlighted agentic AI—autonomous digital agents capable of executing tasks and learning over time. Corporate examples included Google’s AI applications and IBM’s platform, demonstrating how agents streamline workflows and free human capital for high-value tasks.
Speakers recognized that countless AI pilots stall short of scale. To overcome this “valley of death,” the summit offered a structured approach: launch high-impact pilots, upskill staff, set rigid metrics, unify data architecture, and employ open rather than locked systems. Change management—via transparent communication and iterative feedback—was identified as essential for organizational adoption.
Momentum AI concluded with a forward-looking consensus: over the next five years, agentic AI models and open data ecosystems will dominate enterprise AI architectures. Simultaneously, regulators, boards, and tech leaders must collaborate to democratize access and maintain ethical guardrails. Public trust emerges as the cornerstone for any large-scale AI transformation.
Momentum AI San Jose 2025 signaled a decisive shift: enterprise AI is no longer theoretical—it’s tactical. The infusion of governance, measurable ROI, and infrastructure planning speaks volumes. The summit succeeded in transforming internal momentum into external momentum—giving enterprises a clear roadmap to evolve AI from promising pilot to operational powerhouse.
