The race for AI dominance is about more than which model will reign supreme. The real action is happening underneath the surface, where hyperscalers such as Google LLC are focused on the infrastructure and the data pipelines that models run on \u2014 especially as agentic AI infrastructure becomes the true battleground for enterprise scale.\u00a0<\/p>\n
In an analysis of Google Cloud Next 2026<\/a>, John Furrier,<\/a> executive analyst of theCUBE Research, explained that Google is positioning itself as the dominant player in the agentic control layer<\/a> \u2013 the operating system for the agentic enterprise and a core component of agentic AI infrastructure.<\/p>\n \u201cThe control plane is that horizontal layer that moves data around and it connects to all the systems,\u201d Furrier told co-host Alison Kosik<\/a> in a day one keynote analysis<\/a>, during an exclusive broadcast on theCUBE, SiliconANGLE Media\u2019s livestreaming studio. \u201cIt\u2019s like the main nerve center. It\u2019s like the backbone, the spine of all the systems \u2014 and whoever owns the control plane kind of wins.\u201d<\/p>\n Enterprises are speeding ahead with major IT investments and AI deployments \u2013 to mixed results. Furrier mentioned the increasing presence of AI-native applications and agent-driven software coding, with some businesses reporting that they now have more machines than humans doing code work. Other organizations are still trying to determine which use cases will yield the biggest impact from AI, which in turn affects decision-making responsibilities across the enterprise, a challenge that underscores the importance of agentic AI infrastructure.<\/p>\n \u201cYou have a new kind of currency going on with tokens, and that\u2019s changing the organizational structures,\u201d Furrier said. \u201cThat\u2019s changing how people are organizing their teams. That\u2019s changing how people work. It\u2019s a complete reset in the corporate world.\u201d<\/p>\n During interviews at Google Cloud Next<\/a> with industry experts at Google, OpenText Corp., Advanced Micro Devices Inc. and Sabre Corp., Furrier and Kosik discussed how AI is forcing enterprises to rethink data and compute infrastructure and where the biggest efficiencies are currently being found. They also covered examples of how organizations can achieve real value from AI with industry experts from McKinsey & Company Inc., Deloitte Consulting LLP and Covered California, among others. (* Disclosure below.)<\/p>\n Here\u2019s the complete video interview with John Furrier and Alison Kosik, part of SiliconANGLE\u2019s and theCUBE\u2019s coverage of Google Cloud Next<\/a>:<\/p>\n Here are three key insights you may have missed from Google Cloud Next 2026:<\/p>\n Insight #1: Contextual data is the bedrock in the foundation for agentic AI infrastructure.<\/p>\n AI models are only as good as the data they are based on. Google Cloud is focused on enabling an intelligent agentic data cloud that is capable of delivering not just the correct data, but the best data at the right time, a critical requirement for scalable agentic AI infrastructure, according to Sailesh Krishnamurthy<\/a>, vice president of engineering for databases at Google Cloud.\u00a0<\/p>\n \u201cThe models are amazing. The models surprise us every day. They can do a lot of work, but they don\u2019t have all the context,\u201d Krishnamurthy told theCUBE<\/a>. \u201cThe context is in the data. The heart of the data is actually stored in these systems. You need to provide that context in order to answer the questions.\u201d<\/p>\n Compared to legacy databases that simply stored data and delivered the exact results when queried, agent data clouds need the intelligence to parse the data and deliver the best quality results.\u00a0To enable that, databases need capabilities such as graph traversal, vector embeddings, full-text search and relational operations all in one system without requiring data to move between environments \u2014 all foundational to modern agentic AI infrastructure. <\/p>\n Here\u2019s the complete video interview with Sailesh Krishnamurthy:<\/p>\n Waqas Ahmed<\/a>, VP of AI engineering at OpenText, echoed those thoughts. OpenText and Google Cloud are working together to build a full agentic stack built on context engineering, data sovereignty and open interoperability standards.<\/p>\n \u201cEnterprise information is not just files on a drive,\u201d Ahmed told theCUBE<\/a>. \u201cIt is organized, governed, tagged with context, tagged with metadata and integrated with the business applications and customer processes. To wire that into the AI providers and LLMs, you have to be able to build that context so you are not flooding the LLMs with extra information, but you\u2019re giving them the right information at the right time.\u201d<\/p>\n OpenText and Google Cloud are creating industry-specific solutions that provide a secure environment for users to easily access decades of enterprise documentation, according to Yemi Falokun<\/a>, global AI and machine learning partner engineering lead at Google.<\/p>\n \u201cWhat they\u2019re now doing is taking the foundation they\u2019ve built from 2023 into the AI agentic era,\u201d he said. \u201cWe\u2019re now deeply integrating the Gemini Enterprise Agent Platform so that we can allow our joint customers to deploy secure autonomous solutions at scale, leveraging those decades of information that they store on behalf of their users.\u201d<\/p>\n Here\u2019s the complete video interview with Waqas Ahmed and Yemi Falokun:<\/p>\n Insight #2: Partnerships will be key to delivering an efficient AI-ready infrastructure.<\/p>\n Enterprises need substantial compute resources for AI inference, without sacrificing security and control. This has implications for both the enterprise cloud and on-premises environments, and Google has partnered with vendors such as Nvidia Corp. and Dell Technologies Inc. to help enable AI-ready infrastructure, explained Muninder Sambi<\/a>, VP and general manager for networking and security at Google.<\/p>\n \u201cThe challenge is [enterprises] had a choice: Either you can be sovereign and be compliant or give it up and go to the cloud,\u201d Sambi told theCUBE<\/a>. \u201cWith Google Distributed Cloud, we are actually bringing the power and the intelligence of Gemini and all that Google has to offer for an on-premises environment.\u201d<\/p>\n Kubernetes has a key role to play in this new environment as one of the primary orchestrators of AI agents across hybrid environments, according to Drew Bradstock<\/a>, senior product director for Kubernetes and Google Compute Engine at Google.<\/p>\n \u201cKubernetes has become that operating system for AI \u2014 from training to inference to [reinforcement learning],\u201d he said. \u201cThis has really been the heart of everything. We\u2019re finding ourselves on the gun a lot more to adapt Kubernetes quite quickly, even faster than the [open-source community] can keep up.\u201d\u00a0<\/p>\n Here\u2019s the complete video interview with Muninder Sambi and Drew Bradstock:<\/p>\n Businesses are also grappling with the rapid escalation of costs. In the search for financial efficiency, a trusted and time-tested compute standard \u2013 x86 \u2013 has become the answer<\/a> because it is already embedded deeply into both cloud and on-premises infrastructure.\u00a0<\/p>\n \u201cMost of the enterprise and larger customers that I see out there \u2026 are running on-premise in their own real estate, but also running in cloud,\u201d explained Mike Thompson<\/a>\u00a0(pictured right), director of cloud product and go-to-market at AMD. \u201cWhen you\u2019re running containers, that\u2019s one of the things that makes it easier. You have a container; it contains everything you need. You can drop it in. It\u2019s really hard to run a hybrid environment with containers on Arm, because generally those servers aren\u2019t available on-prem. I see containers being leveraged specifically on x86 because of the ease of migration between the two.\u201d<\/p>\n The efficiency of x86 enabled immediate benefits<\/a> when his business migrated more than 50,000 virtual CPUs to AMD-based instances on Google Cloud, according to Tim McArdle<\/a>\u00a0(left), senior FinOps engineer at Sabre, a travel technology company.\u00a0<\/p>\n \u201cWhen we moved to the AMD platform, we experienced a price benefit. It\u2019s faster, we have a smaller footprint and we made zero code changes,\u201d he said. \u201cFor us, that\u2019s a huge win-win-win. We are able to take that savings and invest it in the new world of agentic AI. That has helped us immensely.\u201d<\/p>\n Here\u2019s the complete video interview with Mike Thompson and Tim McArdle:<\/p>\n Google is investing big into bringing together the various players in the agentic AI delivery chain. The company\u2019s $750 million commitment to build a partner ecosystem<\/a> will help accelerate outcomes for over 120,000 members, according to Philip Larson<\/a>, managing director of the Google Cloud Partner Network at Google.<\/p>\n \u201cAgents from our partners are going to talk to agents from the Google Cloud Partner Network across onboarding, training, etc.,\u201d Larson said. \u201cIt\u2019s going to infuse the content from my system into their internal systems. It\u2019s going to make targeted recommendations around what learning their reps should do in real time from within their systems. All of a sudden, the people are going to be sitting on top with an intelligence layer that\u2019s helping them figure out how to add value fast.\u201d<\/p>\n Here\u2019s the complete video interview with Philip Larson:<\/p>\n Insight #3: AI has its biggest impact when it tackles the toughest use cases.<\/p>\n C-suite executives who say they\u2019re still struggling to find business value from large investments in AI<\/a> may need to raise their horizons, according to Asutosh Padhi<\/a>, senior partner and global leader of firm strategy at McKinsey & Company Inc. Successful AI projects require the ambition and focus of the entire C-suite to pursue big foundation-shaking projects.<\/p>\n \u201cStart with one of your tougher business problems,\u201d Padhi told theCUBE. \u201cDemonstrate the fact that it works and then you can scale it up from there. When you start with something that will be a needle mover for the enterprise value, then everyone pays attention. The necessary focus from a change management and capability building standpoint goes into it. When you\u2019re working with something on a simple use case, it\u2019s something that\u2019s happening on the side that no one is really paying attention to. Even if it succeeds, no one really cares.\u201d<\/p>\n Here\u2019s theCUBE\u2019s complete video interview with Asutosh Padhi:<\/p>\n To that end, Covered California, the U.S.\u2019s largest state-based health insurance marketplace serving more than 16 million enrolled residents, has provided an example of what\u2019s possible with ambitious AI initiatives. In partnership with Deloitte Consulting and Google, Covered California leveraged Google Document AI to streamline its eligibility and enrollment verification processes.\u00a0<\/p>\n The project resulted in an estimated 24,000 hours of annual savings in service center operations. Documents that once took 72 hours to verify could be completed in seconds, according to Shilpa Akunuri<\/a>, chief technology officer at Covered California.<\/p>\n \u201cOur staff was spending a tedious number of hours \u2014 no one wakes up on a Monday thinking that I\u2019m going to manually process tons of documents today,\u201d she said. \u201cIt\u2019s not just manual labor hour savings, but they can now focus on high-value customer support<\/a> and providing that operational excellence to the next level.\u201d<\/p>\n In this case, AI not only led to faster operations, but a more empathetic customer journey, explained Vishal Prabhu<\/a>, managing director at Deloitte.<\/p>\n \u201cWhile we hear that AI might replace the human touch, what I would submit to you is: Isn\u2019t AI the key to bring it back?\u201d he said. \u201cTechnology is doing the heavy lifting and people can focus on people.\u201d<\/p>\n Here\u2019s theCUBE\u2019s complete video interview with Shilpa Akunuri and Vishal Prabhu:<\/p>\n Catch up on our complete video coverage of Google Cloud Next 2026:<\/p>\n (* Disclosure: TheCUBE is a paid media partner for Google Cloud Next. Sponsors of theCUBE\u2019s event coverage do not have editorial control over content on theCUBE or SiliconANGLE.)<\/p>\n Photo: SiliconANGLE<\/p>\n Support our mission to keep content open and free by engaging with theCUBE community. Join theCUBE\u2019s Alumni Trust Network, where technology leaders connect, share intelligence and create opportunities.<\/p>\n 15M+ viewers of theCUBE videos, powering conversations across AI, cloud, cybersecurity and more About SiliconANGLE Media<\/p>\n SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-time audience engagement. As the parent company of SiliconANGLE<\/a>, theCUBE Network<\/a>, theCUBE Research<\/a>, CUBE365<\/a>, theCUBE AI<\/a> and theCUBE SuperStudios \u2014 with flagship locations in Silicon Valley and the New York Stock Exchange \u2014 SiliconANGLE Media operates at the intersection of media, technology and AI.<\/p>\n Founded by tech visionaries John Furrier and Dave Vellante, SiliconANGLE Media has built a dynamic ecosystem of industry-leading digital media brands that reach 15+ million elite tech professionals. Our new proprietary theCUBE AI Video Cloud is breaking ground in audience interaction, leveraging theCUBEai.com neural network to help technology companies make data-driven decisions and stay at the forefront of industry conversations.<\/p>\n","protected":false},"excerpt":{"rendered":"The race for AI dominance is about more than which model will reign supreme. The real action is…\n","protected":false},"author":2,"featured_media":27189,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[9],"tags":[24,132,1429,2822,396,18078],"class_list":{"0":"post-27188","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-google","8":"tag-ai","9":"tag-google","10":"tag-google-ai","11":"tag-guest-author","12":"tag-siliconangle","13":"tag-three-insights-you-might-have-missed-from-thecubes-coverage-of-google-cloud-next"},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/27188","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=27188"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/27188\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/27189"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=27188"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=27188"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=27188"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\n11.4k+ theCUBE alumni \u2014 Connect with more than 11,400 tech and business leaders shaping the future through a unique trusted-based network.<\/p>\n