In this keynote preview from Google Cloud Next 2026, theCUBE's John Furrier and co-host Alison Kosik set the stage for three days of wall-to-wall coverage by dissecting Google's strategy to capture the AI control plane — the horizontal connectivity layer that routes data across systems and enables agents to operate at enterprise scale. Furrier frames Gemini not as a standalone model but as an orchestrator, evolving toward something closer to an AI operating system. He cites a Databricks milestone as a marker of how far the transformation has advanced: machines are now writing more code than humans.

The conversation also explores the competitive dynamics shaping the AI landscape, where model-level leapfrogging between Anthropic and OpenAI matters less than who owns the systems those models integrate with. Furrier argues that enterprise adoption — catalyzed first by AI-assisted coding and now being supercharged by agentic workflows — is the defining battleground at this event. The organizational stakes are equally significant: CFOs are shifting into operator roles, chief people officers are being drawn into AI workforce decisions, and tokens are emerging as a new enterprise currency. From Google's TPU investments to the agent ecosystem forming around Gemini, Furrier and Kosik outline what Google must prove this week and why winning the enterprise remains the decisive test of any AI platform's staying power.

In this interview from Google Cloud Next 2026, Giovanni Carraro, senior vice president of alliances at Kyndryl, joins Hector Genaro Moran, chief information officer of PiSA Farmacéutica, to talk with theCUBE's John Furrier and co-host Alison Kosik about the partnership driving enterprise cloud modernization and the shift from AI experimentation to agentic production. Carraro describes how AI has decisively cleared the experimentation phase — the question is no longer if, but how to deploy it at scale. He outlines how Kyndryl's expertise in mission-critical systems enables clients like PiSA to migrate legacy SAP environments to Google Cloud, unlocking decades of manufacturing data trapped in systems of record. Moran notes that for a regulated pharmaceutical manufacturer still running on-premises infrastructure, the move to cloud is not a technical checkbox but a strategic foundation — the prerequisite for everything that follows.

The conversation also explores the governance challenges that shadow AI introduces and why frameworks built for traditional IT cannot be repurposed wholesale for autonomous agents. Carraro argues that as enterprises evolve from managing people and processes to orchestrating people, processes and agents together, governance must advance at the same pace. He also highlights Kyndryl's expanded partnership with Google, including new Distributed Cloud services designed to match the right workloads to the right environments. Both guests converge on leadership transformation as a defining theme: Moran envisions a new generation of board members who treat AI literacy as a core competency rather than an IT concern, while Carraro frames the modern executive as a champion of change rather than a guardian of stability. From migrating a Latin American pharmaceutical leader off legacy infrastructure to envisioning hybrid organizations where humans and agents operate side by side, the discussion maps a clear path from cloud foundation to AI-native enterprise.

In this interview from Google Cloud Next 2026, Mike Thompson, director of cloud product at AMD, joins Tim McArdle, senior principal of FinOps at Sabre, to talk with theCUBE's John Furrier and co-host Alison Kosik about how compute efficiency and strategic cloud migration are freeing up budget to fund the next wave of AI innovation. Thompson points to the industry-wide shift from model training to inference as the defining compute trend of 2026, noting that surging demand is exposing a long-overlooked problem: many enterprises run servers at only 10% utilization. McArdle illustrates the opportunity firsthand — Sabre migrated a massive CPU-intensive workload to AMD instances on Google Cloud with zero code changes, achieving a smaller footprint, faster performance and immediate cost savings, all while scaling to over 50,000 vCPUs.

The conversation also explores how those infrastructure savings are being reinvested directly into agentic AI development at Sabre, which has moved 99% of its compute capacity to Google Cloud. Thompson details how migrating general-purpose workloads to AMD typically drives 30 to 50% OpEx savings — headroom that enterprises can redirect toward new AI applications without waiting for budget cycles to reset. Both guests make the case for x86-based containerization as the foundation of a resilient hybrid cloud, highlighting its portability advantage over multi-architecture environments. McArdle underscores the cultural dimension of modernization, noting that the real barrier is not learning new technology fast enough — it's letting go of established ways of working. From decades of on-premise legacy infrastructure at Sabre to the emerging discipline of AI FinOps, the conversation maps a practical path for enterprises looking to optimize existing budgets while competing in an increasingly AI-native world.

In this interview from Google Cloud Next 2026, Gaurav Syal, vice president and global head of AI, cloud and infrastructure services, EMEA, at Tata Consultancy Services, joins Amit Kapur, chief AI and services transformation officer at Tata Consultancy Services, to talk with theCUBE's John Furrier and co-host Alison Kosik about how enterprises are crossing the divide from AI experimentation to production-ready agentic deployment. As Google's Diamond partner and its top-ranked talent development competency holder, TCS earned five awards at Google Cloud Next 2026, spanning agent development, security and talent. Syal explains how TCS operates as "customer zero" for Gemini Enterprise — deploying the platform internally across 30,000 employees before recommending it to clients. Kapur frames the broader market shift: enterprises are moving away from isolated use cases toward fundamentally reimagining entire workflows on AI, not sprinkling it onto existing processes.

The conversation also explores TCS's approach to cultural transformation, including "AI Fridays" — recurring sessions where employees collectively log 12,000 hours in a single day tackling real-world problems, with 240,000 hours of AI learning accumulated to date. Syal details two standout deployments: an APAC retailer where agentic AI autonomously manages product replenishment by negotiating with suppliers, handling compliance and fulfilling orders end-to-end; and a UK bank that realized $50 million in business value across more than 50 use cases including fraud detection and mortgage lending. Kapur outlines a repeatable engagement model — immersing C-suite leaders in 60-minute hands-on sessions, then delivering a production-ready proof of value in 12 to 16 weeks. From seven Gemini experience centers spanning the globe to the emerging convergence of digital and physical AI in capital-intensive manufacturing environments, the discussion provides a practical roadmap for enterprises ready to move from curiosity to conviction.

In this interview from Google Cloud Next 2026, Philip Larson, managing director of the Google Cloud Partner Network at Google, joins theCUBE's John Furrier and co-host Alison Kosik to discuss how Google is rebuilding its partner ecosystem for the agentic AI era. Larson explains that the redesigned Google Cloud Partner Network (GCPN) functions as an umbrella spanning ISVs, services partners, data providers and marketplace partners — all aligned to guide enterprises through what he describes as an unavoidable transformation to the agentic enterprise. He details a $750 million investment covering AI training, sandbox credits and deployment vouchers, and underscores that the GCPN itself is built on Google's own unified AI stack, with agents embedded across every stage from partner onboarding through to delivery and support.

The conversation also explores how Larson's team eliminated the friction that typically undermines partner programs — stripping out unnecessary external audits in favor of metrics that actually drive outcomes: certifications, co-sell activity and closed statements of work. A standout example is the agentic SOW analyzer, which now influences 90% of funded engagements just six months after launch. Larson notes that partners are demanding new features at a pace that has compressed release cycles from annual to monthly, reflecting the energy around what he calls a once-in-a-generation opportunity. With 500 agentic customer use cases announced at the event, he outlines a near-future vision where partner agents communicate directly with GCPN agents to surface real-time go-to-market recommendations — building a competitive moat he believes no other hyperscaler can replicate at scale.