Freshworks acquires FireHydrant, eyes AI-native IT operations management

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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Freshworks said it will acquire FireHydrant in a move that will build out its IT service and operations management efforts.

Terms of the deal weren't disclosed.

FireHydrant specializes in AI-driven IT operations management software. The plan for Freshworks is to combine FireHydrant with its ITSM platform. FireHydrant was backed by Menlo Ventures and Salesforce.

Here's a look at FireHydrant's platform documentation. FireHydrant, founded in 2018, offers a complete alerting and incident management system. Using AI, FireHydrant automates manual workflows, continually looks for signals about upcoming problems, standardizes processes, alerts and pages responders and integrates with multiple monitoring systems.

• Freshworks delivers strong Q3, ups outlook, targets business teams
• Liz Miller on Freshworks’ pivot

Dennis Woodside, CEO and President of Freshworks, said FireHydrant will accelerate the company's vision of unifying IT and employee experiences. With FireHydrant, Freshworks can move up to compete better with ServiceNow and PagerDuty.

The companies said they will be able to provide a unified AI-native experience that includes:

• Unified visibility for finding IT problems and fixing them.
• Fast responses using FireHydrant's AI to summarize incident context and playbooks to deal with them.
• Proactive IT and asset management.

Freshworks said the FireHydrant purchase will close in the first quarter of 2026.

Rimini Street’s second act will include heavy dose of agentic AI, UX

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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Rimini Street's first act took 20 years, but the second one will move much faster as the company aims to layer agentic AI over legacy enterprise resource planning systems. The strategy: Enable enterprises to accelerate their automation and AI plans while relegating reliable yet legacy systems to plumbing.

At its Dec. 3 Analyst and Investor Day, Rimini Street held what could be called a long overdue roadshow. Rimini Street was founded in 2005 with the mission of providing maintenance and support services to ERP customers of Oracle and SAP. The win for customers: Rimini Street could offer maintenance at a lower cost and enable enterprises to put off ERP upgrades.

As you can imagine, Rimini Street's value prop didn't go over well with ERP vendors. Oracle and Rimini Street legal battle started in 2010 and ended July 7 in a settlement. During that 15-year legal battle, Rimini Street went public via a special purpose acquisition company (SPAC) merger in 2017. Yes, Rimini Street SPACed well before it became trendy.

Rimini Street's second act, which will run from 2026 to 2030, includes an AI spin to its traditional ERP services. The company plans to maintain ERP systems, give customers the ability to put off costly upgrades and relegate them to systems of record plumbing. The new UI for these legacy systems will be agentic AI. The company launched Rimini Street Agentic UX, which has been deployed across multiple customers, in a move that aims to abstract away ERP systems by focusing on AI workflows and processes.

In many ways, Rimini Street Agentic UX is the product of a year-old partnership with ServiceNow. Rimini Street and ServiceNow have a broad partnership to use the Now Platform to enable AI agents to run on legacy infrastructure. ServiceNow and Rimini Street formed a partnership in late 2024 designed to move processes forward with AI and now the two companies have 26 joint pilots underway.

• ServiceNow launches AIx as AI becomes the platform UI
• CCE 2025: AI agents: Dreams, reality and what's next
• AI agents, automation, process mining starting to converge
• Agentic AI: Is it really just about UX disruption for now?
• Lessons from early AI agent efforts so far

Rimini Street CEO Seth Ravin laid out the company's strategy. Rimini Street generates more than $400 million in recurring revenue, serves clients with two-minute response times or less and has a diverse customer base that's more than 50% international.

Ravin's case for Rimini Street revolves around evolving from providing maintenance and support for various enterprise systems to enabling AI. Rimini Street today supports legacy systems such as SAP, Oracle, Dayforce and VMware as well as SaaS applications including Salesforce, Workday, ServiceNow and multiple open-source databases. Going forward, Rimini Street is looking to build on that support and make enterprise AI deliver returns.

"Think of us as AI for the real world. We're the guys who are helping to drive down costs. We're helping to automate processes, streamline businesses and drive #1 problem of every single company we work with, profits," said Ravin.

Ravin argued that boards of directors globally are mandating AI and transformation but also cutting budgets. "How do I make ends meet?" asked Ravin. "CIOs wander out of these meetings punch drunk."

The needle CIOs need to thread is innovation vs. cost cutting. Integration of systems is also a big issue. "We have all these great systems now. The problem is they really don't work together. You've probably heard they're all integrated and there's all these integration tools. It's just not the case. In most organizations, these systems are still very separate," said Ravin, who said every vendor wants customers on the latest release and "CIOs literally cannot do it all."

Ravin estimated that about 9% of the average budget is spent on innovation. "This is a formula for disaster in the long term," he said.

ERP at its technical limits

Rimini Street's Ravin said "we believe that ERP software is reaching its technical limitation."

The company will support ERP for years and decades, but a transition to an AI paradigm is coming. "We believe agentic AI is going to be the downfall of the software we see in the world today and it's happening fast," said Ravin.

Rimini Street Agentic UX is designed to be a simplified window into ERP systems.

And Rimini Street certainly has the installed base to prove its Agentic UX approach will work. Rimini Street manages the ERP systems across automaker Hyundai. The company also serves companies such as Catalyst Brands, which has rolled up companies such Aeropostale, JCPenney, Eddie Bauer, Lucky, Nautica and Brooks Brothers, and KnitWell, a private company that owns eight apparel brands including Ann Taylor, LOFT, Talbots and Chicos. Catalyst and KnitWell each have a handful of ERP systems to roll up. Agentic UX could give these companies an exit ramp to ERP consolidation and upgrades.

Todd Treonze, VP Integration and Corporate Systems at Catalyst Brands, said his company launched a year ago with multiple brands on their own ERP systems. Catalyst Brands consolidated support and maintenance and now plans to build on top of them as systems of records. "I think that there's a really big future opportunity for us here, to reinvest some of the savings we're seeing at the support level and put into the innovation side of the business," said Treonze.

It's a similar story for KnitWell.

"An ERP platform is almost the perfect platform to put agentic AI on top of it. It is well structured. The data underneath is also well structured. And it's all around business rules. There is no easier use case to automate with Agentic AI," said Jaap van Riel, CTO of KnitWell "I really hope I never have to upgrade an ERP in my life again. It's not good for my sleep, and it's not good for kind of the P&L either."

Now this phase out of ERP software as the work interface will take time. Ravin said the reality is that transitions in the enterprise must be orderly and there are processes to consider.

For enterprises to find money for innovation, they'll need to run those ERP processes well. However, don't confuse ERP processes for ERP software.

"We believe we could take 40% of the labor cost out of running the processes that run a business or government agency. That is monumental in terms of driving bottom line profits, streamlining operations and leapfrogging over the competitors with technology. This is what AI can do in the real world, in ERP and transactions," said Ravin.

Ravin's pitch is something we're hearing anecdotally from customers and vendors. The reality is that AI is changing the enterprise technology cycle to one that revolves around more efficient processes and use cases. The software matters, but optimized processes matter more.

The game will revolve around abstracting ERP software away so you can focus on the process.

The long AI game (sped up)

CIOs will need to realize it's a long game. AI agents will require governance, protocols and orchestration. Processes will be retooled.

"There are a lot of questions. We still have a lot of things to do. This is not all baked yet," said Ravin. "You have to recognize we're in the middle part of this inning in getting the technology figured out and then deployed in the real world. That's why we keep focusing on process, not the software."

To Ravin, enterprises will need to focus on process over software because "we don't have years to change."

Enterprises will need to think through the 10 processes that run businesses. Rimini Street's plan is to help enterprises extract the processes out of the ERP software.

"We are going to extract these processes out of the ERP software and move them up into the Agentic AI ERP like it's surgery. And eventually, eventually, there won't be a need for the underlying software anymore. Because we will have moved piece by piece over time, from one paradigm of technology to another," said Ravin. "Their tools, our know-how, our knowledge, our ability to go to market with credibility because we know these processes. We'll just put the new technology right over the top. We won't take the risk of ripping and replacing your massive global system. We then will move pieces one at a time."

Rimini Street's portfolio includes methodology called Smart Path, which revolves around a gradual move to a process-driven system and out of the ERP software game.

Vijay Kumar, Chief Innovation Officer at Rimini Street, Smart Path revolves around providing a foundation and roadmap to move to agentic AI ERP. Core tenents include:

• Use legacy ERP systems for what they're good at: Data.
• Layer a framework on top of it with Agentic UX.
• Leverage an architecture that is headless. "We're going to keep the SAP systems the way they are. We're going to preserve the data, the customizations and a lot of the work that customers have done," said Kumar. "What we're doing is really modernizing the front end of it, adding AI agents, which is absolutely critical, improving the UX, and finally being able to automate."
• Be prepared to evolve architecture since it's early in the AI game.

Rimini Street reckons it can get enterprises to a pilot in 30 days. Kumar said the ideal customer is one that has complex workflows, manual workflows and things that are hard to automate. The end state may feature agentic AI ERP apps to handle processes and use cases. "Once we start building credibility app by app, use case by use case, we're going to layer agentic AI across the enterprise," said Kumar.

Broadcom CEO comments highlight build vs. buy AI debate

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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The companies that are looking to leverage artificial intelligence for competitive advantage are increasingly choosing to go custom. It's build over buy at massive scale.

Broadcom's fourth quarter earnings results were an eye opener for the industry after CEO Hock Tan laid out a few interesting tidbits. Broadcom is benefiting from XPUs, custom AI accelerators. Google's TPUs, which have emerged as a threat to Nvidia, account for a big chunk of Broadcom's revenue.

• Custom AI processors mean Broadcom printed money in Q4

Tan also revealed that Anthropic is buying Google Ironwood TPUs, the latest generation. Some choice quotes:

• "Our custom accelerated business more than doubled year-over-year, as we see our customers increase adoption of XPUs, as we call those custom accelerators in training their LLM and monetizing their platforms through inferencing APIs and applications."
• "These XPUs, I may add, are not only being used to train and inference internal workloads by our customers, the same XPUs in some situations have been extended externally to other LLM peers, best exemplified at Google, where the TPUs use in creating Gemini, have also been used for AI cloud computing by Apple, Coherent and SSI as an example."
• "Last quarter, Q3 '25, we received a $10 billion order to sell the latest TPU Ironwood racks to Anthropic. And this was our fourth customer that we mentioned. And in this quarter Q4, we received an additional $11 billion order from the same customer for delivery in late 2026."
• "That does not mean our other two customers are using TPUs. In fact, they prefer to control their own destiny by continuing to drive their multiyear journey to create their own custom AI accelerators or XPU racks, as we call them. And I'm pleased today to report that during this quarter, we acquired a fifth XPU customer through a $1 billion order placed for delivery in late 2026."

The big takeaway is that custom is the thing right now. For AI workloads at scale, this build over buy conclusion isn't that surprising. Google's TPUs are gaining favor. AWS launched its Trainium 3 processor and outlined Trainium 4. These hyperscalers are going custom to optimize for costs and monetize as soon as they stand up data centers.

Tan said customers are choosing to go custom for multiple reasons, but price-performance is the big one. Rivian also noted that agility is a big factor. Rivian's custom AI processor enables it to get started on software well before the chip lands.

• Rivian’s AI strategy: Four takeaways

The move toward custom components for AI systems is notable, but the market is immature. When markets are young, you tend to build your own stuff. Ask Amazon and Google. The big question is whether this custom-all-the-time approach lasts. Tan provided a bit of history when asked about the future of the XPU.

He said:

"You is don't follow what you hear out there as gospel. It's a trajectory. It's a multiyear journey. And many of the players, and not too many players, doing LLM wants to do their own custom AI accelerator for very good reasons. You can put in hardware if you use a general purpose GPU, you can only do in software and kernels and software. You can achieve performance-wise so much better in the custom purpose-designed, hardware-driven XPU."

• Oracle Q2 mixed, says it will be neutral on GPUs
• AWS launches Graviton5 as custom silicon march continues
• AWS launches AI factory service, Trainium 4 with Trainium 4 on deck
• Google Cloud's Ironwood ready for general availability
• Anthropic to use Google Cloud TPUs as it diversifies capacity

Will that mean custom approaches will be dominant over time? Not at all. Tan said:

"Will that mean that over time, they all want to go do it themselves? Not necessarily. And in fact, technology in silicon keeps updating, keeps evolving. And if you are an LLM player, where do you put your resources in order to compete in this space, especially when you have to compete at the end of the day against merchant GPUs who are not slowing down in the rate of evolution. I see that as this concept of customer tooling is an overblown hypothesis, which frankly, I don't think will happen."

These comments are notable if you expand it to broader enterprises. My take:

• Buy over build makes a lot of sense right now for enterprises, not necessarily at the hardware stack. If you can use AI to code and transform it's possible that you don't need to pay your SaaS tax. As for hardware, you’ll consume custom compute from cloud providers.
• Agentic AI interfaces could relegate a lot of your applications to plumbing. See: The enterprise LLM questions you should be asking | Agentic AI: Is it really just about UX disruption for now?
• OpenAI and Anthropic see this trend and are increasingly tapping into enterprise processes. See: AI agents, automation, process mining starting to converge
• Vendors will tell you repeatedly that building your own systems is a fool's errand, but if the focus is on process the strategy makes sense. However, Tan noted repeatedly that the custom route is a multiyear journey. The same multiyear approach matters for software too.
• In the end, enterprises want to control their own destinies and be agile. Locking in to any one vendor means you have no leverage. This fact applies to your data layer too and vendors like Databricks and Snowflake. See: AI strategies and projects: The hope, the fear and everything in between
• Enterprises are likely to think about custom apps because they're tired of SaaS costs rising as much as health care costs. Perhaps the suite always wins, but that phase in the AI app market may not arrive for years.

Related:

• Among CxOs, SaaS platform fatigue setting in
• The big AI, SaaS, transformation themes to watch in 2025’s home stretch
• LLM giants need to build apps, ecosystems to go with the models
• Pondering the future of enterprise software

Rivian’s AI strategy: Four takeaways

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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Rivian's vertically integrated approach to autonomous driving and AI is enabled by its data flywheel that it uses to train its models and optimize.

The automaker held its first Autonomy & AI Day and perhaps the biggest lesson is that Rivian is an example of a company using its first-party data to develop new opportunities.

Rivian CEO RJ Scaringe highlighted the company's strategy, which revolves around owning its AI stack. That stack includes purpose-built silicon and a platform that used ingest data and train models. Rivian is looking to get into the AI and autonomy game, which includes the likes of Tesla as well as Alphabet unit Waymo.

"Directly controlling our network architecture and our software platforms in our vehicles has, of course, created an opportunity for us to deliver amazingly rich software. But perhaps even more importantly, this is the foundation of enabling AI across our vehicles and our business," said Scaringe.

Key news items from Rivian's investor meeting:

• Rivian unveiled its Rivian Autonomy Processor (RAP1), a custom 5nm processor that integrates processing and memory on a single multi-chip module.
• RAP1 features RivLink, which is a low latency interconnect technology that networks chips for more processing power.
• The company outlined its third-gen Autonomy computer, or Autonomy Compute Module 3 (ACM3). ACM3 can process 5 billion pixels per second.
• Rivian has an in-house developed AI compiler and platform. The platform, the Rivian Autonomy Platform, features an end-to-end data loop and its Large Driving Model (LDM), which is an LLM for driving. The LDM will distill strategies from Rivian's datasets.

Going forward, Rivian plans to integrate LiDAR into its upcoming R2 models at the end of 2026. LiDAR augments Rivian's multi-sensor strategy. Rivian also said it will add Universal Hands-Free driving features to its second-gen R1 vehicles. The system will be available on 3.5 million miles of roads in the US and Canada.

• What you can learn from Rivian's AI, data strategy
• Rivian: AI, data power customer experiences

Rivian's AI strategy beyond autonomy includes Rivian Unified Intelligence, a foundation of multi-modal and multi-LLMs and data. The platform is designed to enable Rivian to roll out features, improve service and offer predictive maintenance. Rivian is also launching a next-gen voice interface in early 2026 that uses its edge models, third party integrations, and reasoning LLMs.

Beyond the news barrage from Rivian, there are multiple takeaways from the company's strategy meeting. Here are a few:

Rate of change only increasing. Rivian has created an architecture that can adapt to the pace of change. Enterprises will need to work under the assumption that the rate of change over the next five years will be much faster than the last five years.

"If we look forward 3 or 4 years into the future, the rate of change is an order of magnitude greater than what we've experienced in the last 3 or 4 years," said Scaringe.

Also: Uber outlines its autonomous vehicle plan | GM to integrate Google Gemini, delivered unified software defined vehicle architecture

First party data is everything. "Our approach to building self-driving is really designed around this data flywheel. We're a deployed fleet, has a carefully designed data policy that allows us to identify important and interesting events that we can use to train our large model offline, before distilling the model back down into the vehicle," said Scaringe.

AI will touch every process. Rivian is leveraging its AI backbone for its vehicles and autonomous efforts. But Rivian's AI backbone also runs through the enterprise. Scaringe said its AI strategy will impact its sales and service model, supply chain and manufacturing infrastructure.

You may need to build your own. Vidya Rajagopalan, Senior Vice President of Electrical Hardware at Rivian, explained why the company had to develop its own processors. She said:

"It's important to address why we chose to build in-house silicon. The reason for doing it is velocity, performance and cost.

With our in-house silicon development, we're able to start our software development almost a year ahead of what we can do with supplier silicon. We actually had software running on our in-house hardware prototyping platform well ahead of getting first silicon. Our hardware and software teams are actually co-located and they're able to develop at a rapid pace that is just simply not possible with supplier silicon."

Rajagopalan said the ability to customize is also critical for designing for current use cases and the future. In addition, Rivian can optimize to save money.

Think multiple models. Wassym Bensaid, Chief Software Officer at Rivian, said the company has developed its own model for driving, but has a "suite of specialized agents."

"Every Rivian system from manufacturing, diagnostics, EVR planning, navigation becomes an intelligent node through MCP. And the beauty here is we can integrate third-party agents. And this is completely redefining how apps in the future will integrate in our cars," said Bensaid. "We orchestrate multiple foundation models in real time, choosing the right model for each task. And we support memory and context, allowing us to offer advanced levels of personalized experience."

Bensaid said the use of multiple models and Rivian's architecture is designed to move workloads from the cloud to the edge. Rivian Unified Intelligence is the connective tissue.

Custom AI processors mean Broadcom printed money in 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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Broadcom reported better-than-expected fourth quarter results as it continued to see a revenue surge due to custom AI chips.

The company reported fourth quarter net income of $8.52 billion, or $1.74 a share, on revenue of $18.01 billion, up 28% from a year ago. Non-GAAP earnings for the fourth quarter were $1.95 a share.

Wall Street was expecting non-GAAP earnings in the fourth quarter of $1.86 a share on revenue of $17.49 billion.

As for the outlook, Broadcom projected first quarter revenue of $19.1 billion, up 28% from a year ago.

Broadcom, despite acquiring VMware to beef up its software business, is still a hardware story. CEO Hock Tan said revenue growth was "driven primarily by AI semiconductor revenue increasing 74% year-over-year." Broadcom makes chips for Google and inked a deal for custom processors for OpenAI. 

Tan added that it expects momentum to continue in the fourth quarter driven by demand for custom AI accelerators and Ethernet AI switches.

In the fourth quarter, Broadcom's semiconductor business was 61% of sales and infrastructure software was 39%. Chip revenue was up 35% in the quarter and software was up 19%.

As a result, Broadcom is just printing money. Cash flow from operations in the fourth quarter was $7.7 billion, up 37% from a year ago. Free cash flow was up 36%. Broadcom's cash and cash equivalents checked in at $16.18 billion, up from $10.72 billion in the previous quarter.

For fiscal 2025, Broadcom reported net income of $23.13 billion, or $4.77 a share, on revenue of $63.89 billion, up 24% from fiscal 2024. 

Tan said on the earnings call:

• "Our custom accelerated business more than doubled year-over-year, as we see our customers increase adoption of XPUs, as we call those custom accelerators in training their LLM and monetizing their platforms through inferencing APIs and applications."
• "These XPUs, I may add, are not only being used to train and inference internal workloads by our customers, the same XPUs in some situations have been extended externally to other LLM peers, best exemplified at Google, where the TPUs use in creating Gemini, have also been used for AI cloud computing by Apple, Coherent and SSI as an example."
• "Last quarter, Q3 '25, we received a $10 billion order to sell the latest TPU Ironwood racks to Anthropic. And this was our fourth customer that we mentioned. And in this quarter Q4, we received an additional $11 billion order from the same customer for delivery in late 2026."
• "That does not mean our other two customers are using TPUs. In fact, they prefer to control their own destiny by continuing to drive their multiyear journey to create their own custom AI accelerators or XPU racks, as we call them. And I'm pleased today to report that during this quarter, we acquired a fifth XPU customer through a $1 billion order placed for delivery in late 2026."

OpenAI calls GPT-5.2 its most advanced model for work

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-5.2 in what appears to be its answer to Google's Gemini 3.0. According to OpenAI GPT-5.2 is its most advanced mode for work and long-running agents.

The company leaned into the productivity case for GPT-5.2. In a blog post, OpenAI said:

"We designed GPT‑5.2 to unlock even more economic value for people; it’s better at creating spreadsheets, building presentations, writing code, perceiving images, understanding long contexts, using tools, and handling complex, multi-step projects."

OpenAI touted the usual benchmarks for GPT-5.2 improvements, but it's notable that it is also using its GDPval benchmark too. GDPval looks at how models perform in knowledge work in 44 occupations.

• OpenAI touts enterprise mojo with 1 million business customers
• Anthropic, OpenAI look to Accenture for partner scale
• OpenAI sets SDKs for app integrations, agentic AI building blocks
• Why CxOs, enterprises need to follow OpenAI’s GDPval LLM benchmark

With the positioning of GPT-5.2, OpenAI is clearly making the return on investment case for its latest foundational model as it competes with Google and Anthropic. Microsoft said it has added GPT-5.2 to Microsoft 365 Copilot, Copilot Studio, Microsoft Foundry and GitHub Copilot.

• Google launches Gemini 3, Google Antigravity, generative UI features

"GPT‑5.2 Thinking beats or ties top industry professionals on 70.9% of comparisons on GDPval knowledge work tasks, according to expert human judges. These tasks include making presentations, spreadsheets, and other artifacts. GPT‑5.2 Thinking produced outputs for GDPval tasks at >11x the speed and <1% the cost of expert professionals," said OpenAI.

The compare and contrast of the GPT-5.2 vs GPT-5.1 models is worth noting.

The upshot here is that OpenAI is pivoting on real world tasks for judging models. Perhaps, OpenAI is tired of ceding the corporate use cases to Anthropic's Claude.

As for the rollout, OpenAI said:

"In ChatGPT, we’ll begin rolling out GPT‑5.2 (Instant, Thinking, and Pro) today, starting with paid plans (Plus, Pro, Go, Business, Enterprise). We deploy GPT‑5.2 gradually to keep ChatGPT as smooth and reliable as we can; if you don’t see it at first, please try again later. In ChatGPT, GPT‑5.1 will still be available to paid users for three months under legacy models, after which we will sunset GPT‑5.1."

OpenAI, Disney deal foreshadows where media is headed

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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Disney will license its stable of characters in a three-year licensing deal that will enable Sora users to create social videos.

Terms of the agreement include:

• Sora will have access to more than 200 Disney, Marvel, Pixar and Star Wars characters.
• Sora users can create videos that will be available to stream on Disney+.
• Disney will use OpenAI models throughout its enterprise and become a major customer. Disney employees will use ChatGPT.
• OpenAI APIs will be used to build new products.
• Disney will invest $1 billion in OpenAI and have warrants to buy more shares.

On its own, the OpenAI-Disney partnership is standard issue. However, Disney is opening the door for other media companies to license IP and characters to models. After this deal, it's not a stretch to see Google Gemini do something similar. This OpenAI-Disney deal is the equivalent of putting Mickey Mouse on the Apple Watch.

Short term, media giants will license IP to AI players just like they do streaming companies like Netflix.

But the real thing to watch is whether media companies use LLMs to leverage their own IP. Media companies have historically been behind on new technology and AI isn't much different.

Here's what media companies should be doing:

• Develop their own models powered by their own data just like enterprises do.
• Create new experiences so customers can spin up their own episodes. The Simpsons may be the best training set ever for a model. Why not be able to spin up my own Bart adventure? AI can monetize vast libraries of content.
• With an AI-driven approach, there's no reason why media companies couldn't create what essentially is the next streaming market.
• Given that backdrop it's not surprising that Netflix and Paramount Skyworks are dueling to buy Warner Bros. Discovery. Rest assured the Ellison family, which controls Paramount Skydance, knows where this game is going. We're at the IP and data gathering phase of this game. The media company with the best first party data (characters, franchises and audience) can win the AI era.

At a panel at AWS re:Invent 2025, Albert Cheng, VP of AI for Prime Video, said AI is becoming the next streaming moment. Cheng said:

"I feel the same way today about AI as I did when I first started pushing streaming at Disney. It's the start of another transformation. Streaming transformed distribution and I think AI is going to transform the way content is created."

This mashup of AI and media is just starting. The deal between OpenAI and Disney is just the first volley.