C3 AI cuts Q1 revenue outlook, revamps sales org amid search for new CEO

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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C3 AI said its fiscal first quarter sales will be well below expectations and that it has reorganized its sales operations.

The news, announced at 7:30 PT EST on a Friday, lands a few days after C3 said it would look for a successor to CEO Tom Siebel, who is stepping down due to visual impairment due to an autoimmune disease.

In a statement on the sales reorg, Siebel said:

"The good news is we have completely restructured the sales and services organization, including new and highly experienced leadership across the board to ensure a return to accelerating growth and increased customer success at C3 AI. The bad news is that sales results in Q1 were completely unacceptable.

Having given this a lot of thought, I attribute this to two factors. One: It is clear that in the short term, the reorganization with new leadership had a disruptive effect. Two: As we have previously announced, I have had a number of health issues in the past six months including multiple hospitalizations and vision impairment. Unfortunately, dealing with these health issues prevented me from participating in the sales process as actively as I have in the past. With the benefit of hindsight, it is now apparent that my active participation in the sales process may have had a greater impact than I previously thought."

The sales disruption had a big impact on C3 in the first quarter. The company said that it will report first quarter revenue of $70.2 million to $70.4 million with a non-GAAP loss of $57.7 million to $57.9 million. Wall Street was looking for sales of $104.02 million in the first quarter with a non-GAAP loss of 13 cents a share.

In the fourth quarter, C3 delivered revenue of $108.72 million, up 26% from a year ago, and Siebel said partnerships with hyperscale cloud providers were faring well.

That drop-off in sales spurred the sales restructuring, which is now complete. Here's a look at the reorganization, which revolves around executives with years of enterprise sales experience.

• Rob Schilling joined C3 as Chief Commercial Officer, took over June 16. Schilling has held sales leadership roles at Oracle, SAP and Siebel.
• John Kitchingman took over as C3 General Manager for EMEA effective June 30. He had been a sales leader at Dassault Systèmes and IBM Global Services.
• Jeff Cosseboom, another alum of SAP and Oracle as well as Siebel, will be C3's Group Vice President of North America East Sales.
• Lars Färnström joined C3 AI as Group Vice President, Nordics. Färnström had been CEO of Crate.io and is a previous exec at C3 as well as Siebel.
• Alex Amato, Group Vice President of Customer Services at C3, was promoted and now has responsibility for all professional services and customer services operations.

Siebel noted that he is "fully engaged" as CEO and his health "has improved dramatically" except for his vision impairment. The search for a successor is underway, said Siebel.

The road to AI Exponential will be bumpy

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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Companies that are AI native are likely to deliver better returns, run autonomously and thread the needle between human and digital labor. The catch? Getting to that AI native status isn't going to be easy.

Constellation Research CEO Ray Wang outlined an AI maturity model that ranges from AI Luddites to AI Exponentials.

The five levels look like this:

Most companies are trying to get to AI native and that aspiration will lead to a lot of IT spending. The reality is that many companies are going to be AI enabled and way more efficient than they are today.

AI Natives are going to be largely digital and autonomous with heady growth figures. AI Exponentials probably don't exist today, but there will be a few.

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For most the journey starts with the chase to be AI Native. Wang wrote: "While at first this may sound like more AI hyperbole, the early indications for organizations who begin their journey as AI Natives by design show a tremendous advantage versus the AI Enabled who have to reduce their legacy technology, cultural, and financial debt."

Given that framework, I went on a quick tour of enterprises reporting results in recent weeks. Here's a look at a few household names and where they land in the matrix.

Marriott: AI Aware

Marriott CEO Anthony Capuano said the company has a multi-year transformation plan that revolves around its three main systems: Loyalty, property management and central reservations.

"We expect to start deploying the new cloud-based central reservations, PMS (property management system) in the U.S. and Canada select service hotels later this year," said Capuano. "It should make the experience for our guests, both on property and when they're engaging with our customer engagement centers, much more seamless, much more efficient."

That transformation, built on AWS, is designed to make Marriott more agile and ready for AI. Marriott has also set up a team focused on AI. "We have stood up a Marriott AI incubator that is working on a variety of proof of concepts," said Capuano. "Some of those early proof of concepts were in areas like reimagining the concierge function where we think there's a real opportunity to take advantage. We're also looking at pilots in our customer engagement centers to help those agents navigate such a broad and diverse portfolio."

Marriott has incorporated AI into the Marriott Homes and Villas platform and launched an ambassador trip planning tool. At AWS re:Invent 2024, Adnan Haq, Managing Vice President of Cloud, DevSecOps and Infra Platforms at Marriott, said the company started its cloud transformation in 2022 to create a differentiated guest experience with AI, integrate digital experiences, drive revenue with customized promotions and offers and move faster.

Wayfair: AI Aware to AI Enabled

Wayfair, which reported earnings this week, has moved to Google Cloud and is starting to reap the rewards with a strong second quarter despite a sluggish home market.

Niraj Shah, CEO of Wayfair, said the company now is in a position to grow and take market share.

Shah said that Wayfair has a 2,500 person technology organization that has been focused on the replatforming of core systems to Google Cloud. Now that migration is complete, that team is focused on increasing product velocity and innovation.

"Now that we're very far into that replatforming effort, a lot of the cycles of the team are now back building features and functions to improve the customer experience and supplier experience," said Shah. "And you see that affect things, whether it's conversion rates, enabling suppliers to do more, launching new genAI-powered features and delivering efficiency gains in our operations."

Intuit: AI Enabled aiming for AI Native

Intuit has been setting itself up well for each technology inflection point. Before AI, Intuit focused on honing its data game and creating the flywheel that connected its platform to customer experience.

Those data efforts, which included a strong cloud game, enabled Intuit to take advantage of generative AI early.

Now Intuit is well on the way to leveraging AI agents. At AWS Summit New York, the company outlined some of its agentic AI plans. It's early in Intuit's AI agent plans, but the focus is on driving returns and cash flow improvements for customers and ultimately the company.

• Intuit embraces LLM choice for multiple use cases
• Intuit sees 'green shoots' from its generative AI strategy
• Intuit’s bets on data, AI, AWS pay off ahead of generative AI transformation

Airbnb: AI Enabled aiming for AI Native

Airbnb CEO Brian Chesky made it really easy to categorize his company. Speaking on a second quarter earnings call, Chesky outlined a retooled tech stack, expanded product and feature cadence and AI strategy that revolves around making its app AI native.

Chesky said Airbnb will become an AI-native app. He said today, the top 50 applications on Apple's App Store aren't AI native. ChatGPT is the top app with a few other AI natives, but for the most part the top players are not AI-native.

He said:

"You've got basically AI apps and kind of non-AI native apps. And Airbnb would be a non- AI native application. Over the next couple of years, I believe that every one of those top 50 slots will be AI apps--either start-ups or incumbents that transform into being AI native apps. And I think at Airbnb, we are going through that process right now of transitioning from a pre- generative AI app to an AI native app. We're starting to customer service. We're bringing into travel planning. So it's really setting the stage."

Uber: AI Native

Uber was using machine learning and AI before it was the big thing. Now the company is using its models to drive interaction between its mobility and delivery services.

Speaking on Uber's second quarter earnings call, CEO Dara Khosrowshahi said Uber is using larger models that can take contacts from a consumer, history and seasonality to send promotions at the right time. With its models, Uber has extended into advertising and other additional businesses.

"Larger and more sophisticated AI models are also improving our ability to encourage cross-platform activity for the right consumers at the right time—for instance grabbing coffee on your way to the office, or having your groceries delivered right as you arrive at your vacation rental. This is a key focus area that’s still in its early innings, and you will continue to see us innovate in both the Uber and Uber Eats apps to supercharge cross-platform activity," said Khosrowshahi.

Uber is also pondering a super app that will combine its services and build on top of the platform.

And by the way, Uber is offering its own AI services on its platform. In addition, Uber's data flywheel will also play a big role in autonomous vehicle and the AI models behind them.

• Uber AI Solutions expands, targets enterprises
• Uber outlines its autonomous vehicle plan

Maybe everything should be a holding company

Over time, most leading enterprises will become AI native. In fact, many of the category leaders are well on the way there.

However, the AI exponential companies--which will operate 80% of the business by machine and generate more than $5 million in profit per employee--are going to have to start from scratch. These companies are lean and mean and frankly may never get beyond 10 employees.

Simply put, a legacy company with a thriving business isn't going to cut and transform its way to the growth of AI exponentials. It's quite possible that every category leader will be a holding company to stand up companies that could become AI exponentials. Think Alphabet and Waymo. Given you can start a company today that's saddled with tech debt and legacy infrastructure after six months it may be better to invest in AI exponentials than transform into one.

Atlassian outlines partnership with Google Cloud, strong fiscal Q4

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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Atlassian said products such as Jira, Confluence and Loom will run on Google Cloud and integrate with Gemini models in a broad partnership.

Separately, Atlassian announced better-than-expected fiscal fourth quarter results.

• Atlassian: A look at its system of work strategy, enterprise uptake, AI approach

Key parts of the Atlassian-Google Cloud partnership include:

• Atlassian's products will run on Google Cloud and be integrated with Vertex AI and Gemini models.
• The integration will enable customers to build AI agents.
• Atlassian apps will be available on Google Cloud Marketplace for the first time and joint customers can use cloud computing credits for Atlassian subscriptions.
• Atlassian Rovo, the company's AI agent, will be able to use Vertex AI and Gemini models. Customers can build Rovo agents that can utilize documents in Google Workspace and leverage data from across Jira, Confluence, Google Docs and Gmail.
• Rovo will support Agent2Agent (A2A) agents.
• Jira and Confluence users will be able to act within Gmail, Chat and Docs.

For its fourth quarter, Atlassian reported a net loss of $23.9 million, or 9 cents a share, on revenue of $1.38 billion, up 22% from a year ago. Non-GAAP earnings for the fourth quarter were 98 cents a share, 13 cents a share better than Wall Street estimates.

Mike Cannon-Brookes, CEO of Atlassian, said the company ended the quarter with 2.3 million AI monthly active users.

In a shareholder letter, Cannon-Brookes said:

"Jira Product Discovery has already amassed over 20,000 customers, Loom MAU is growing more than 30% year-over-year, and Jira Service Management Premium and Enterprise edition sales are up over 50% year-over-year."

For fiscal 2025, Atlassian reported a net loss of $256.7 million, or 98 cents a share, on revenue of $5.2 billion, up 20% from a year ago. Non-GAAP net income for the year was $975.9 million.

The company also said President Anu Bharadwaj will leave to pursue other opportunities. She has been at Atlassian for 12 years in multiple roles.

As for the outlook, Atlassian said first quarter revenue will be between $1.395 billion to $1.4 billion with cloud revenue of 22.5%. For fiscal 2026, Atlassian is projecting revenue growth of 18% and cloud revenue growth of 21%.

OpenAI launches GPT-5, a system of models

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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OpenAI launched GPT-5, a system of models that are the company's most advanced with the promise of advanced reasoning, coding abilities and agentic features.

CEO Sam Altman said GPT-5 is like having "superpower on demand" and critical for enterprises and developers. GPT-5 will become the default across OpenAI services.

"GPT-5 is great for a lot of things, but we think it's going to be an especially important moment for businesses and developers, and we're very excited to see what they're going to build with this new technology.

For OpenAI, the stakes are huge as large language models (LLMs) take performance leaps almost daily. "GPT-5 is like talking to an expert, a legitimate PhD level expert in anything, about any area you need, on demand, which can help you with whatever your goals are," said Altman.

• OpenAI's open weight models gain AWS distribution: Why it matters
• The rise of good enough LLMs

OpenAI launched the following flavors of GPT-5. As noted in its system card, OpenAI outlined the following progression.

• GPT-4o is replaced by gpt-5-main
• GPT-4o-mini replaced by gpt-5-main-mini
• OpenAI o3 replaced by gpt-5-thinking
• OpenAI o4-mini replaced by gpt-5-thinking-mini
• GPT-4.1-nano replaced by gpt-5-thinking-nano
• OpenAI o3 Pro replaced by gpt-5-thinking-pro

OpenAI said that GPT-5 is faster, more reliable and accurate on multiple tasks, including health.

The company said GPT-5 will roll out on all tiers--including free--and launch for enterprises and education next week. OpenAI plans to deprecate its previous models.

According to the GPT-5 system card:

"GPT?5 is a unified system with a smart and fast model that answers most questions, a deeper reasoning model for harder problems, and a real-time router that quickly decides which model to use based on conversation type, complexity, tool needs, and explicit intent (for example, if you say “think hard about this” in the prompt). The router is continuously trained on real signals, including when users switch models, preference rates for responses, and measured correctness, improving over time. Once usage limits are reached, a mini version of each model handles remaining queries. In the near future, we plan to integrate these capabilities into a single model."

It remains to be seen whether GPT-5 moves the needle for Open-AI’s enterprise share. According to Menlo Ventures, Anthropic has 32% share of enterprise AI followed by OpenAI at 25% and Google at 20%. OpenAI spent a lot of time talking about GPT-5's ability to address health care use cases. 

Microsoft said GPT-5 is now included into its consumer, developer and enterprise products including Microsoft Copilot, Microsoft 365 Copilot, Copilot Studio, Copilot Studio, GitHub Copilot, Visual Studio Code and Azure AI Foundry.

Key points include:

• GPT-5 is priced at $1.25/1M input tokens and $10/1M output tokens.
• GPT-5 mini is $0.25/1M input tokens and $2/1M output tokens.
• GPT-5 nano is $0.05/1M output tokens and $0.40/1M output tokens.
• OpenAI is offering four present personalities for GPT-5 including Cynic, Robot, Listener and Nerd. 
• The API now has a verbostity setting for answers. I've been guilty of calling GPT a wordy 7th grader. 

Airbnb: A look at its AI strategy

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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Airbnb has launched an AI agent built on 13 different models for customer service in its app and plans to add more AI tools in the quarters to come. The goal: Transform the Airbnb app into one that is AI native.

CEO Brian Chesky said on Airbnb's second quarter conference call that the company's move into complementary services paid off in the second quarter with better-than-expected results. Airbnb has retooled its tech stack and is now rolling out improvements to its app and services at a faster pace.

"We are massively ramping up development of product development pace at Airbnb. We do these typically biannual releases, but we are now iterating very, very quick even between these releases," said Chesky.

Airbnb is navigating multiple shifts. The company is expanding into complementary markets including home market services and experiences, shifting its marketing approach to focus more on social over search and TV and optimizing everything from pricing to customer service as it expands share globally.

In the second quarter, Airbnb delivered strong metrics as it expanded its AI-powered customer service agent to 100% of US users and scaled new offerings. The company said it saw travel demand accelerate from April to July despite an uncertain economy. Airbnb reported second quarter net income of $642 million on revenue of $3.1 billion, up 13% from a year ago.

• Here Come the AI Exponentials

As for the outlook, Airbnb said it expects revenue growth of 8% to 10% in the third quarter with stable nights and seats booked compared to the second quarter. The company did say it expects lower margins due to investments in new markets including Airbnb Services and Airbnb Experiences.

In addition, Airbnb redesigned its app to make bookings across services in one place. The company has optimized continually since the May launch. That product cadence will be necessary as Airbnb carries out its AI strategy. Chesky outlined Airbnb's approach to AI and agents. Here's a look:

Start with the hardest problem. Chesky said most AI efforts in travel have revolved around trip planning and inspiration. Airbnb has gone with customer service as an AI use case because it is "the hardest problem because the stakes are high, you need to answer this quickly and the risk of hallucination is very high."

"You cannot have a high hallucination rate. And when people are locked out, they want to cancel reservation, they need help, you need to be accurate. And so what we've done is build a custom agent built on 13 different models that have been tuned off of tens of thousands of conversations. We rolled this out throughout the United States in English. And this has reduced 15% of people needing to contact a human agent when they interact instead with this AI agent," said Chesky.

The plan now is to bring that customer service agent to more languages, he added.

Increase personalization and context. Chesky said the customer service AI agent will become "more personalized and more agentic" throughout the next year. "The AI agent will not only tell you how to cancel your reservation, but it will also know which reservation you want to cancel, cancel it for you and it can start to search and help you plan and book your next trip."

Expand AI into travel search and planning from customer service. Chesky said the plan is for Airbnb to leverage AI throughout its use cases and app. Airbnb is looking at multiple expansion areas including hotel bookings "especially boutiques in bed and breakfast" and independents in Europe.

Become AI native. Chesky said Airbnb will become an AI-native app. He said today, the top 50 applications on Apple's App Store aren't AI native. ChatGPT is the top app with a few other AI natives, but for the most part the top players are not AI-native.

"You've got basically AI apps and kind of non-AI native apps. And Airbnb would be a non- AI native application.

Over the next couple of years, I believe that every one of those top 50 slots will be AI apps--either start-ups or incumbents that transform into being AI native apps. And I think at Airbnb, we are going through that process right now of transitioning from a pre- generative AI app to an AI native app. We're starting to customer service. We're bringing into travel planning. So it's really setting the stage."

Here's a look at the characteristics of AI natives per the Constellation Research grid. 

Stay focused and strategic. Chesky said it's premature to think of AI chatbots and agents as the Google replacement. The concept of one AI tool to rule all isn't proven. Chesky's bet is that there will be specialized AI models in categories.

Chesky said that ChatGPT is a great product, but the approach isn't exclusive to OpenAI. He said:

"Airbnb can also use the API, and there are other models that we can use. In the coming years, you're going to have a situation where these large AI models can take more and more, and more things will start there, but people won't often go to one chatbot.

You're going to also have start-ups that are going to be custom-built to do a specific application, and you're going to have incumbents that make a shift to AI. It's not enough to just have the best model. You have to be able to tune the model and build a custom interface for the right application.

The key thing is going to be for us to lead and become the first place for people to book travel on Airbnb. As far as whether or not we integrate with AI agents, I think that's something that we're certainly open to. Remember that to book an Airbnb, you need to have an account, you need to have a verified identity. Almost everyone who books uses our messaging platform. So I don't think that we're going to be the kind of thing where you just have an agent or operator book your Airbnb for you because we're not a commodity. But I do think it could potentially be a very interesting lead generation for Airbnb."

Cohere North generally available

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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Cohere North, a collaborative agentic AI platform, is generally available following testing by a bevy of large enterprises. Cohere launched Cohere North in January in a move that aims to broaden the company's reach beyond large language models (LLMs).

The availability of Cohere North is part of a larger trend by foundational model companies to surround models with workflows and enterprise use cases. A big selling point of Cohere North is that it can be deployed privately to ensure privacy of enterprise data.

• Cohere launches North, aims to be an AI agent workspace
• Cohere rolls out Embed 4, an enterprise multimodal search model
• The rise of good enough LLMs

Enterprises that have used Cohere North to deploy AI agents include RBC, Dell, LG CNS, Ensemble Health Partners and Second Front. Cohere recently announced a strategic partnership with Bell Canada to provide full-stack sovereign AI solutions for government and enterprise customers across Canada, and to deploy proprietary, secure AI solutions within Bell. That partnership will improve Cohere North.

In addition, Cohere and RBC developed North for Banking, which is a configuration designed for financial services. North has also been deployed withing LGS CNS in South Korea. Dell also includes Cohere North in its Dell AI Factory stack.

Cohere North includes the following:

• Generative and search models.
• Customizable agents.
• Built-in workflow automations.
• Integration with enterprise data across systems and services.
• An architecture that enables Cohere North to run privately with as few as two GPUs.

Features of Cohere North include:

• Chat and search across data repositories and content.
• Custom tools and integrations with Gmail, Slack, Salesforce, Outlook and SharePoint.
• The ability to integrate with any Model Context Protocol (MCP) server.
• Asset creation of documents, financial reports and research.
• Automated workflows for processes.

According to Cohere, Cohere North is designed for secure deployments across on-premises infrastructure, hybrid clouds, VPCs and air gapped environments. Cohere is aiming for regulated industries with Cohere North.

Cohere North incudes access controls and permissions, autonomy policies, security testing, system observability, flexible deployment options and compliance with various regulations.

OpenAI's open weight models gain AWS distribution: Why it matters

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

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OpenAI released two open-weight models--gpt-oss-120b and gpt-oss-20b--but the real news revolves around distribution. These two new OpenAI models have a wide distribution including availability on Amazon Web Services for the first time.

The new OpenAI models, which can run locally, on-device and through third party providers, are not-surprisingly available on Microsoft Azure, but also Hugging Face, vLLM, Ollama, llama.cpp, LM Studio, AWS, Fireworks, Together AI, Baseten, Databricks, Vercel, Cloudflare and OpenRouter.

For good measure, OpenAI said it worked with Nvidia, AMD, Cerebras and Groq to optimize the models.

In a blog post, AWS said gpt-oss-120b and gpt-oss-20b will be available in Amazon Bedrock and Amazon SageMaker JumpStart. The models will also be available in frameworks for AI agent workflows such as AWS' Strands Agents.

The models and why they matter

According to OpenAI, the gpt-oss-120b model "achieves near-parity" with OpenAI o4-mini on core reasoning benchmarks running on a single 80 GB GPU. The gpt-oss-20b model delivers similar results to OpenAI o3-mini and can run on devices with 16 GB of memory for local inference.

OpenAI also outlined safety efforts and early development with AI Sweden Orange and Snowflake. The model card has all the details, but the primary takeaway is that OpenAI's open-weight models perform well.

You'd be forgiven for glazing over a bit with OpenAI's latest models. Alibaba's Qwen just released a new image model, Anthropic released Claude Opus 4.1 and improvements to Opus 4 and Google DeepMind launched Genie 3, which can generate 3D worlds.

Simply put, it's another day, another model improvement complete with various charts of benchmarks.

The rise of good enough LLMs

The big picture for OpenAI revolves around distribution and enterprise throughput. The AWS availability is a win for OpenAI, may open some doors and more importantly adds an option for enterprises.

The LLM game has become one that revolves around spheres of influence. Microsoft Azure has plenty of model choices, but is clearly aligned with OpenAI. Amazon is a big investor in Anthropic. Google Cloud is all about Gemini, but also has a lot of choice including Anthropic. OpenAI models to date have been available either direct or through Microsoft.

Add it up and OpenAI has to be available on multiple clouds so the open weight move makes a lot of sense.

Here's why? OpenAI can't afford to lose the enterprise because that's what'll pay the bills. Sure, OpenAI may upend Google in search. Yes, there are even OpenAI devices on tap for consumers. But the real dough will be in the enterprise.

• OpenAI takes stab at gauging productivity gains, AI economic impact
• OpenAI's CEO of Applications pens intro missive: 5 takeaways
• OpenAI vs. Microsoft: Why a breakup could be good
• OpenAI's enterprise business surging, says Altman

The problem? Enterprises are going to value price performance and practical applications with real guardrails. That's why I find AWS' practical approach so interesting. It may cause some consternation among analyst types, the practical appeal is what CxOs want and need if they're going to take AI agents to production.

• AWS' AI strategy: Jassy's long talking and the big picture
• AWS' practical AI agent pitch to CxOs: Fundamentals, ROI matter

According to Menlo Ventures, Anthropic has 32% share of enterprise AI followed by OpenAI at 25% and Google at 20%. And Google's Gemini models are all over the enterprise as Google Cloud makes a big play to be the AI cloud layer. In a few months, it's highly likely that enterprise models will revolve around Anthropic and Google's Gemini family. We're in the era of good-enough LLMs and enterprises simply want the best model for the use case.

OpenAI's launch of open-weight models with broader distribution can keep it in the game. Also keep in mind that AI spending is going to revolve around inference in the enterprise.

We can haggle over benchmarks and performance all day, but like all things enterprise distribution matters.