Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Apple's fourth quarter results were mixed, but services revenue topped the $100 billion in annual revenue. The results were better-than-expected.

The company reported fourth quarter earnings of $1.85 a share on revenue of $102.5 billion, up 8% from a year ago.

Wall Street was expecting fourth quarter earnings of $1.77 a share on revenue of $102.25 billion.

The September quarter only includes a few days of sales of the iPhone 17 lineup.

CEO Tim Cook said the company's portfolio, which includes iPhone 17 devices, iPhone Air and refreshed MacBook Pro and iPad Pro. 

On a conference call with analysts, Cook said: "We're also seeing developers take advantage of our on device foundation models. So excited for a more personalized Siri. We're making good progress on it, and as we've shared, we expect to release it next year."

By the numbers:

• Apple reported fiscal 2025 revenue of $416.16 billion with net income of $112 billion.
• Services revenue was $28.75 billion for the fourth quarter and $109.16 billion for the year.
• iPhone revenue was $49.02 billion in the fourth quarter and $209.59 billion for the year.
• Mac sales were $8.73 billion in the fourth quarter.
• iPad sales in the fourth quarter were flat from a year ago at $6.95 billion.
• Wearables, home and accessories revenue was $9.01 billion, down slightly from a year ago.
• China revenue in the fourth quarter was $14.49 billion, down from $15 billion a year ago.

Constellation Research analyst Holger Mueller said:

"Apple had a good quarter. The good news is that the main platform, the iPhone got another boost, showing that innovation gets Apple users to upgrade. Now Apple just has to deliver more of it. The Apple Intelligence release is the big milestone to watch. With rising iPhone sales the platform and services up as well it's and surprising Apple is creating record sales. Services are now more revenue for Apple than all non iPhone categories together. Good to see. Now all eyes are on the always critical holiday quarter. Wearables, iPad and likely Mac won't help much. Apple is and remains the iPhone and growingly iPhone services company."

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Amazon Web Services' revenue growth in the third quarter accelerated 20% as the unit delivered operating income of $11.4 billion on revenue of $33 billion.

The AWS results landed in a better-than-expected quarter for Amazon overall. Amazon reported third quarter net income of $21.1 billion, or $1.95 a share, on revenue of $180.2 billion.

Wall Street was expecting Amazon to report earnings of $1.56 a share on revenue of $177.76 billion.

• AWS re:Invent 2025 to feature Trainium3, scaling secure AI agents

AWS' revenue growth of 20% was above expectations. Microsoft said Azure revenue was up 40% and Google Cloud delivered sales growth of 34%. Both of those rivals are operating off a smaller base than AWS, which is on a $132 billion annual revenue run rate.

• AWS fires up Project Rainier, Trainium2 cluster for Anthropic
• AWS delivers outage post mortem: When automation bites back
• AWS launches Amazon Quick Suite, aims to automate business workflows
• Amazon cuts 14,000 corporate jobs
• Amazon Bedrock AgentCore generally available

Andy Jassy, Amazon CEO, said:

"AWS is growing at a pace we haven’t seen since 2022, re-accelerating to 20.2% YoY. We continue to see strong demand in AI and core infrastructure, and we’ve been focused on accelerating capacity – adding more than 3.8 gigawatts in the past 12 months."

AWS fired up its Project Rainier data center cluster designed for Anthropic's AI workloads. AWS also said its Trainium2 custom AI chip is "fully subscribed and a multi-billion-dollar business."

In addition, AWS said it saw strong adoption of Transform, an AI agent that makes it easier to migrate to AWS. Transform has saved 700,000 hours in migration work.

As for the outlook, Amazon said fourth quarter revenue will be between $206 billion and $213 billion, or up 10% to 13%. Operating income will be between $21 billion to $26 billion.

On a conference call with analysts, Jassy said:

• Backlog in the third quarter was $200 billion and "doesn't include several unannounced new deals in October."
• "A lot of the future value companies will get from AI will be in the form of agents. AWS is heavily investing in this area. Companies will both create their own agents and use agents from other companies. For those building their own, it's been harder to build than shipping. For companies who successfully built agents, they hesitated putting them into production because they lack secure, scalable runtime services or memory or observability built specifically for agents. It's why we launched AgentCore instead of infrastructure building blocks that allow builders to deploy scalable agents."
• "AWS continues to earn most of the big enterprise and government transformations to the cloud. AWS is where the ponderance company's data and workloads reside, and part of why most companies want to run AI on AWS. We need to have the requisite capacity. We've been focused on accelerating capacity the last several months, adding more than 3.8 gigawatts of power in the past 12 months. To put that into perspective, we're now double the power capacity that AWS was in 2022 and we're on track to double again by 2027."
• "You're going to see us continue to be very aggressive investing in capacity, because we see demand as fast as we're adding capacity right now. As fast as we're bringing capacity in right now, we are monetizing it."
• "Starting with Trainium3, we're building Bedrock to be the biggest inference engine in the world. In the long run, we believe Bedrock will be as big a business for AWS as EC2."
• "We have a small number of very large customers on Trainium2, but because it is 30% to 40% better price performance, there are customers contemplating broader scale for AI focused workloads and inference. Trainium3 should preview at the end of this year and beginning of 2026 we have a lot of customers very interested. Trainium3 will be 40% better than Trainium2." 
• "We buy a lot of Nvidia, but history shows there's never just one player that satisfies everyone's needs. But we have our own strong chip team. For our customers to use AI expansively, they're going to need better price performance."

Here's a look at the third quarter numbers:

• North American commerce sales were $106.3 billion, up 11%, with operating income of $4.8 billion.
• International commerce sales were $40.9 billion, up 14% from a year ago, with operating income of $1.2 billion.
• Free cash flow for the third quarter was $14.8 billion for the trailing 12 months, down from $47.7 billion a year ago. Amazon said it has spent $50.9 billion on property and equipment--mostly GPUs, CPUs and data centers.

• Advertising revenue in the third quarter was $17.7 billion, up 24% from a year ago.
• Subscription services revenue was $12.57 billion, up 11% from a year ago.
• Amazon ended the quarter with 1,578,000 employees.
• Amazon took a $2.5 billion charge to settle a lawsuit with the Federal Trade Commission.
• The company took a $1.8 billion charge related to severance costs and layoffs. Operating income would have been $21.7 billion without those charges.

Constellation Research analyst Holger Mueller said:

"Amazon is picking up speed again, across all segments, with  AWS leading the charge. But it didn't move on the profit side, due to regulatory fines and restructuring. Evidently, Andy Jassy is confident that Amazon can grow with less employees, a sign that the internal AI offerings are maturing. Jassy would not shift the hand to machine ratio if AWS AI wasn't ready. That is a very good confidence indicator for CxOs buying from AWS that they can start investing into the maturing AI offerings of AWS."

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Wayfair plays in a rough neighborhood where it has to deal with tariffs, an anemic housing market and consumer purchasing patterns that were skewed by the Covid-19 pandemic. However, a technology replatforming during that volatility has made it more agile and able to position itself for AI.

The home goods retailer shined this week with third quarter results that handily topped estimates. Wayfair delivered a third quarter net loss of $99 million on revenue of $3.1 billion, up 8% from a year ago. Non-GAAP earnings in the quarter were 70 cents a share, 26 cents a share ahead of Wall Street estimates.

Wayfair had 21.2 million active customers in the third quarter, down 2.3% from a year ago, but was able to increase net revenue per active customers. A big reason Wayfair was able to increase revenue per active customer was that it used technology to help people design and buy easier. Repeat orders were up 6.8% from a year ago.

Niraj Shah, CEO of Wayfair, said the company has benefited from "the groundwork we've laid over multiple years directly driving share capture and profitability despite a category that remains stubbornly sluggish."

Shah added:

"We completed the bulk of our replatforming earlier this year and the timing couldn't have been better as we are in the early innings of a new phase in how customers shop online. While AI has certainly become the buzzword of late, we've been on the forefront of machine learning for a long time, leveraging algorithms to drive everything from pricing decisions to marketing investments. Today, there is new ground being broken with the proliferation and sophistication of generative AI, and Wayfair is a leader in the application of AI in retail."

Simply put, Wayfair doesn’t necessarily need a housing market recovery to thrive.

• Wayfair starts to reap rewards from optimization, tech replatforming efforts
• CCE 2025: AI agents: Dreams, reality and what's next
• How Wayfair's tech transformation aims to drive revenue while saving money
• BT150 interview: Wayfair CTO Fiona Tan on transformation, business alignment and paying down tech debt

On the earnings call, Wayfair CTO Fiona Tan, a BT150 member, laid out the company's AI plans. Here's a look at the strategy.

AI as growth engine

Tan said generative AI and agentic AI is central to Wayfair’s next growth phase. The company is leveraging its long history with machine learning (pricing, cataloging, marketing) and is now scaling generative AI capabilities across the customer journey, operations, and supplier ecosystem.

“Our investments in AI are pragmatic and results-oriented centered on three key strategic outcomes: reinventing the customer journey, supercharging our operations and teams, and powering our platform and ecosystem,” she said.

Reinventing the customer journey

Wayfair is transforming the shopping experience into an AI-powered growth flywheel—inspire, engage, learn, personalize—to move beyond traditional personalization.

Key initiatives include:

• Muse: A proprietary AI-powered inspiration engine that generates photorealistic, shoppable room scenes to attract low-intent shoppers.
• Discover Tab: Integrates insights from Muse to create a looping shopping experience that drives longer visits and higher conversion.
• Interest-Based Carousels: Personalize product recommendations based on lifestyle, with future context signals like weather and location.
• LLM-Powered Search & Visual Search: Moves beyond keywords—customers can upload a photo and find similar products instantly.
• AI Assistant & Designer-Quality Recommendations: Combines Wayfair’s designer expertise with LLMs to produce curated, personalized design matches—customers shown these are 33% more likely to add to cart or purchase.
• “Complete the Look” (in testing): Generates full AI-styled rooms using real shoppable items from the catalog.

Operations

AI is being embedded across operations to boost efficiency and accuracy. Here’s a look at the moving parts:

• Catalog Enrichment: Generative AI improves product data quality and consistency, driving higher add-to-cart rates.
• Duplicate Detection: AI identifies redundant listings, cutting manual review costs by 75%.
• AI Customer Service Agents: 24/7 fully autonomous bots handle common inquiries, while human agents use AI copilots with intent-based routing and reasoning models for complex issues.
• Trust & Safety: Multimodal AI detects fraudulent imagery in real time.
• AI for All Employees: Every employee has access to a generative AI license; company-wide Gen AI Innovation Challenge encourages practical AI adoption across departments.

“We’re making AI experimentation part of our everyday culture. Our teams are learning with the same urgency and curiosity we expect of the technology itself,” said Tan.

Platform and ecosystem

Tan said the supplier side of the Wayfair marketplace will leverage a series of AI agents as well as generative AI tools. Here’s a look:

• AI Agents for Suppliers: Automate ticket classification and resolution, reducing manual work.
• Generative AI for SEO & Ads: LLMs optimize product titles and ad copy—boosting Google visibility, free traffic, and ad performance.
• Generative Engine Optimization: Ensures Wayfair products are surfaced in AI-driven search and chat platforms.

“We believe customer attention will flow to the most trustworthy API, not the loudest ad,” said Tan.

Agentic commerce

Tan said Wayfair is building a dual-pronged agentic AI strategy that revolves around the following.

• Integrate with AI Platforms (e.g., Google, OpenAI, Perplexity) — ensuring its vast catalog is verifiable, discoverable, and fully transactable within AI environments.
• Strengthen Wayfair’s Own Moats — emphasizing proprietary data, curated catalog, verified supply chains, and delivery reliability.

“Our plan is to make our catalog fully transactable on leading AI platforms, allowing customers to shop with confidence wherever their journey begins,” she said.

If successful, Tan said that AI-driven commerce will serve as a moat for Wayfair. “In a world of AI-driven commerce, retailers with a large, well-detailed catalog, verified supply chains, and deep technology capabilities are advantaged,” she said.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

ServiceNow said its third-quarter results were better than expected, raised its outlook and said it will split its stock 5-for-1.

The company reported third quarter earnings of $502 million, or $2.40 a share, on revenue of $3.41 billion, up 22% from a year ago. Non-GAAP earnings were $4.82 a share.

Wall Street was expecting third quarter earnings of $4.27 a share on revenue of $3.35 billion.

ServiceNow said current remaining performance obligations were $11.35 billion in the third quarter, up 21% from a year ago. Remaining performance obligations were $24.3 billion, up 24% from a year ago.

• ServiceNow launches AIx as AI becomes the platform UI
• ServiceNow launches Zurich release, inserts process, task mining into AI agent workflows

Bill McDermott, CEO of ServiceNow, said the company was in an elite club and that "enterprise AI was a great neighborhood to be in." McDermott touted ServiceNow CRM, the company's control tower for agentic AI and fast time to value.

CFO Gina Mastantuono aid "Now Assist, U.S. Federal, Workflow Data Fabric, and RaptorDB were all ahead of plan."

As for the outlook, ServiceNow projected fourth quarter subscription revenue of $3.42 billion to $3.43 billion, up nearly 20% from a year ago. For fiscal 2025, ServiceNow projected subscription revenue of $12.83 billion to $12.84 billion.

A few choice quotes from McDermott, who was particularly enthusiastic on the ServiceNow third quarter earnings call.

• "Here's the headline: ServiceNow is one of the most durable, consistent overperforming growth companies in the enterprise software industry. When you think about brands shaping the future, you have GPU leaders like Nvidia, hyperscalers, foundation models and one company integrating all together, the AI workflow company ServiceNow. It used to be the MAG 7. Now there's a new category. I'm calling this Super Eight. That's the Mag 7 plus ServiceNow."
• "Our AI Control Tower deal volume more than quadrupled quarter over quarter in Q3. Just since the end of May, AI agent assist consumption has increased over 55x. That's the foundation of a beautiful hockey stick that's coming to you."
• "ServiceNow's workflow engine is creating the roadmap that AI agents follow to get work done."
• "Enterprises invested a lot into legacy CRM deployments. For all that investment, they got a sprawling mess of instances and silos. They want a better way with AI. This applies to many legacy vendors, some more than others. Our AI experience turns CRM into an AI-first system of action that drives growth and customer loyalty."

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

• Capital expenses including assets under finance leases were $34.9 billion, up 74% from a year ago. Half of that sum went to GPUs and CPUs for Azure.
• Productivity and Business Process revenue was $33 billion, up 17% in the first quarter.
• Microsoft Commercial Cloud revenue was up 17% and consumer cloud sales were up 26%.
• Dynamics 365 revenue was up 18%.
• Windows OEM and devices revenue was up 6%.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Google Cloud revenue surged 34% in the third quarter and is hitting an annual run rate of nearly $61 billion.

In the third quarter, Google Cloud delivered revenue of $15.2 billion with operating income of $3.6 billion. Google Cloud saw strength in core AI infrastructure and generative AI products.

The Google Cloud gains landed as Alphabet reported better-than-expected financial results overall. Alphabet reported third quarter net income of $35 billion, or $2.87 a share, on revenue of $102.35 billion, up 16% from a year ago.

Wall Street was looking for third quarter revenue of $99.89 billion with earnings of $2.26 a share.

Alphabet said that Google Search, YouTube ads, Google subscriptions and Google Cloud all delivered double-digit growth in the third quarter.

CEO Sundar Pichai said the company saw strength across every unit to deliver its first $100 billion quarter. "Our full stack approach to AI is delivering strong momentum and we’re shipping at speed," said Pichai.

Capital expenses in the third quarter were $23.95 billion, up 83% from a year ago.

• Google Public Sector: AI agents and the future of government
• Anthropic to use Google Cloud TPUs as it diversifies capacity
• Google claims quantum advantage with Willow breakthrough
• Google Cloud launches Gemini Enterprise, eyes agentic AI orchestration

By the numbers:

• Gemini processes 7 billion tokens per minute via direct API use.
• The Gemini App has more than 650 million monthly active users.
• Google Cloud ended the quarter with a backlog of $155 billion.
• YouTube Premium and Google One drove more than 300 million subscriptions.
• Alphabet's other bets, which includes Waymo, had third quarter revenue of $344 million with a loss of $1.43 billion in the third quarter.
• Free cash flow in the third quarter was $24.46 billion, up 39% from a year ago.

On a conference call, Pichai said:

• "Our extensive and reliable infrastructure, which powers all of Google's products, is the foundation of our stack and a key differentiator. We are scaling the most advanced chips in our data centers, including GPUs from our partner, Nvidia, as well as our own purpose built GPUs, and we are the only company providing a wide range of both."
• "We are investing in TPU capacity to meet the tremendous demand we are seeing from customers and partners."
• "Over the last quarter, we rolled out AI Mode globally across 40 languages. It now has over 75 million daily active users, and we shipped over 100 improvements to the product in q3 an incredibly fast pace. Most importantly, AI mode is already driving incremental total query growth for search."
• "The number of new Google Cloud customers increased by nearly 34% year over year. We are signing larger deals. We have signed more deals, Over $1 billion through Q3 this year than we did in the previous two years combined. More than 70% of existing Google Cloud customers use our AI products."
• "Over the past 12 months, nearly 150 Google Cloud customers each processed approximately 1 trillion tokens with our models for a wide range of applications."

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Amazon Web Services said Project Rainier, an AI compute cluster powered by 500,000 Trainium2 chips, is now in use for Anthropic.

The AI infrastructure project is critical for AWS since it is being used by Anthropic to train its Claude models as well as other workloads. AWS said that Project Ranier will ultimately scale to 1 million Trainium2 processors.

Project Ranier was announced a year ago. Anthropic has pursued a multi-cloud approach and recently said it would procure TPUs from Google Cloud. Anthropic's models will now run on Nvidia, AWS and Google Cloud.

Key facts include:

• AWS said Project Rainier will have more than 1 million Trainium2 chips by the end of the year.
• The AI compute power is being used to build and deploy future versions of Claude.
• Project Rainier is AWS largest infrastructure project to date.
• Project Rainier is designed as a massive “EC2 UltraCluster of Trainium2 UltraServers.”
• The architecture consists of stringing together UltraServers, which have four physical Trainium2 servers each with 16 Trainium2 chips. They communicate via high-speed connections called NeuronLinks.
• The combination of these Ultraservers add up to an UltraCluster.
• AWS said the vertical integration will enable it to continually optimize Project Rainier for cost and energy efficiency.
• Given that AWS is highly likely to announce Trainium3, the next question will revolve around the replacement cadence and depreciation for Trainium2.

Constellation Research analyst Holger Muller said:

"It's good to see AWS being on track to build its first super computer. Traditionally AWS would scale through many machines not large machines, which require different engineering and different fault tolerances. We will see more details when the new machine will be in production. Obviously, AWS is confident for it to work and wants a portion of the news during GTC week. And finally it's a great proof point for AWS wanting to keep workloads inhouse and living the build vs buy mantra."

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Google Public Sector CEO Karen Dahut said there's urgency in government to leverage AI, transform and do it in a national secure way. The company positioned itself as a key public sector AI infrastructure provider that can enable AI agents to carry out missions.

“We believe agencies of the future will be powered by AI and agents that are ubiquitous and multimodal. This means the public sector will become more productive and more efficient,” said Dahut.

The Google unit, which launched in 2022, has increasingly gained in public sector accounts and has hooked up with key integrators such as Lockheed Martin. As outlined a year ago, Google Public Sector is also set up on Google Cloud's security foundation and various controls as well as its Mandiant unit and security operations. Google Public Sector is an independent entity that leverage Google Cloud technology, but takes it the last mile (with isolated instances in some cases). Google rolled out Gemini for Government before Gemini for Enterprise.

"The pace truly is unlike anything we've ever seen. We're talking days, not months or years, and there is a heightened sense of global urgency. We've got to move fast, and there's a new national security imperative," said Dahut. "The high ground is no longer just air and space, it's the digital domain. This is our new reality, and the stakes are super high at the same time you are being asked to do more with less in mission critical environments that are constantly evolving."

Google Public Sector 2025 kicked off amid a US government shutdown that Dahut addressed at the top.

"I know that for so many of you in this room, and not in this room, our federal agency customers, leaders, dedicated public servants and the entire contracting community, this government shutdown is creating profound uncertainty and difficulty," said Dahut. "Your missions are critical. The work you do matters."

• Google Public Sector, Lockheed Martin pair up for on-premises AI
• Old Dominion, Google Public Sector create AI incubator
• City of Los Angeles bets on Google Workspace with Gemini as it preps for big events

Dahut added that Google is upping its capital expenses to $85 billion to build out its AI infrastructure. She also emphasized security and options to deploy AI off the cloud. “There is security everywhere all the time. We believe agencies of the future will be powered by a zero trust security foundation that shifts the advantage back to cyber defenders,” said Dahut.

The big themes

At Google Public Sector 2025, there were a few big themes hit by executives.

• There was an emphasis on Google Cloud's integrated AI stack including its custom TPUs that generate AI performance and cost efficiency. That said, Google Public Sector's keynote featured an extended partnership with Nvidia. Nvidia's Ian Buck, VP of Hyperscale and HPC, filled in for CEO Jensen Huang, who was in the neighborhood for Nvidia GTC Washington, DC, but had to fly for trade talks with China.
• Google noted that it has an extensive global network to support missions including 42 regions, 124 zones and 202 edge locations. Google executives didn't say it directly, but the subtext is that the company's AI infrastructure is already built instead of merely announced and gigawatt press releases extending into the next decade.
• Google Public Sector is gaining beyond just the US federal market and outlined a series of state and city customer wins.
• There's still a healthy dose of federal AI deals as Google Public Sector ran through multiple use cases for US departments and agencies such as the Department of Defense, Pacific Northwest National Laboratory, Department of Energy, FAA, NOAA, National Cancer institute and others.

Gemini for Government as an orchestrator

Thomas Kurian, CEO of Google Cloud, highlighted Gemini for Government and the ability to build models and AI agents.

Kurian cited the US Postal Service, which is using Vertex AI, to modernize legacy systems and the National Cancer Institute, which is automating research processes.

According to Kurian, AI agents and AI conversational platforms will be embedded into "every employee and process workflow for every government agency."

Gemini for Government is designed to connect to data stores and keep context as well as use multiple models.

In a demo of Gemini for Government, executives highlighted agents and connectors to various systems as well as mission specific efforts from partners. 

Kurian also emphasized on-premise and air-gapped deployments of Gemini.

"We also bring our AI to wherever your mission sits, whatever your mission is. The same Gemini model that is available in the public cloud is also available on Google Distributed Cloud," said Kurian. "We call it GDC for connected on premise environments and fully air gap deployments. Together with our partner, Nvidia, we're bringing Gemini on Blackwell GPUs to your data centers."

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Lockheed Martin will integrate Google Gemini models into the Lockheed Martin AI Factory in a partnership with Google Public Sector.

The partnership will bring Google's AI tools into Lockheed Martin's on-premises air-gapped infrastructure.

Google Public Sector announced the deal at its Google Public Sector Summit in Washington DC.

According to the companies, Google AI will be deployed in Lockheed Martin infrastructure in a phased deployment. Google's generative AI, including Google Gemini on Google Distributed Cloud, will be deployed in unclassified systems and then classified systems for aerospace, space exploration and cybersecurity.

Google's AI tools and Gemini will be used for accelerated multi-modal data analysis, advanced research and development and logistics including supply chain management and route optimization.

Lockheed Martin said the Google Public Sector partnership "equips our engineers with powerful tools—safely and at scale—to accelerate innovation in support of our business and critical missions."

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Google Public Sector and Old Dominion University are aiming to embed AI throughout the university including research, teaching and operations workflows via an incubator.

The incubator, called MonarchSphere, Old Dominion University (ODU) is looking to use AI to accelerate discovery, personalize learning and advance student career paths.

Google Public Sector announced the deal at its Google Public Sector Summit in Washington DC.

The ODU partnership includes Google Cloud's Vertex AI platform, various Gemini models and agentic AI services. MonarchSphere is designed to be a central hub for education connecting various ODU departments.

Dr. Brian O. Hemphill, President of Old Dominion University, said the Google Public Sector pact is a "defining moment" that will make ODU a "future-ready institution." ODU is one of many universities looking for ways to embed AI into curriculum, research and operations and advance student outcomes.

Here's a look at the moving parts of the ODU-Google Public Sector partnership.

• Research. ODU researchers will have access to Google Cloud compute for AI and big data projects. Faculty can run models quickly for use cases such as genomics. ODU previously used over-taxed on-premise clusters.
• Google AI for Education Accelerator. ODU is an early member of the accelerator designed to bring AI to education institutions. Google AI for Education Accelerator includes no-cost access to Google certificates and AI training that can be integrated across curriculum and workforce training.
• Curriculum will be mapped to Google's career pathway tools. ODU faculty are also piloting Google Colab Enterprise in advanced AI courses to give students access to GPUs for model training.
• Tools for courses including Gemini Pro and Notebook LM. Course designers can generate summaries, outlines and learning materials using genAI. Workflow tools can also speed up delivery. ODU will develop an AI course assistant tool.
• ODU said it is planning to move beyond a one-size-fits-all model to one that's personalized for each student. MonarchSphere will be extended to local municipalities and small businesses in Virginia.

Dr. Chrysoula Malogianni, Associate Vice President of Innovation at ODU, said the key to the project with Google Public Sector is data management.  Your data is everything.

Malogianni said your AI success largely depends on your data. "Have a data plan," she said. "AI is not a catastrophe or panacea. AI can't do anything. You need robust data. You need infrastructure and a data foundation so you can validate AI. You need to also start preparing your target population for AI adoption. If we don't understand the AI you won't have a plan."

She added that ODU put a lot of work into the data foundation along with Google Public Sector. Key assets included:

• 20 years of recorded courses and data can be combined with real time data from interactions. 
• Notebooks for mind maps and course outlines to create assistants with the help of instructional designers. 
• Data types from transcripts, advisors and student interests.
• The combination of course data and public data with students to create personalized journeys. 

And don't forget the leadership. "It's important to have visionary leadership because transformation doesn't start from technology. It starts from visionary leadership, appropriate partnership and having a good plan," said Malogianni.