Enterprise AI partnerships, model access and cloud spending lead October 28

OpenAI and ServiceNow extend their enterprise integration

OpenAI and ServiceNow said they are expanding their partnership to connect ServiceNow workflows with ChatGPT and Codex. The companies say a new ServiceNow integration will let customers bring their own instance’s context and selected workflow actions into ChatGPT, such as investigating an incident, assessing a change and updating a ServiceNow record.

That scope matters because the integration is designed around a customer’s existing permissions and business rules, rather than giving a model blanket access. OpenAI says ServiceNow’s Action Fabric will apply each organization’s configured controls. ServiceNow also plans to expand ChatGPT Work and Codex access beyond its engineering organization to all employees.

Much of the roadmap remains prospective. The ServiceNow MCP plugin is available in OpenAI’s marketplace now, but OpenAI says enhanced capabilities are expected by the end of 2026; its planned security offering is slated for early access in January 2027 and general availability in the second quarter. The announcement describes intended workflow and security benefits, not independently measured deployment outcomes.

Google says Carbon will begin with cyber defenders

In Alphabet’s quarterly remarks, Google said it had announced Gemini 4 Carbon, which it describes as its strongest frontier model for cybersecurity and long-horizon work. The company said Carbon will first go to a subset of trusted cyber defenders and is being tested by the U.S. government before wider access.

Google also said Carbon ranks first on the updated Artificial Analysis Intelligence Index, and that it outperforms Gemini 4 Argon across areas including web development, multimodal understanding and scientific reasoning. Those are Google’s characterizations of the model and its external-index result; the company did not announce broad public availability in the remarks.

The staged access is a more concrete detail than the performance language. It means the launch is not yet a general developer or consumer release, and it leaves open how the trusted-defender program will translate into a wider product offering.

Alphabet points to heavier AI use and infrastructure demand

Alphabet reported third-quarter revenue growth of 25% year over year and said Google Cloud revenue grew 103%. In the same presentation, it said its first-party model APIs were processing nearly 32 billion tokens per minute, up 40% from the prior quarter, while the Gemini app had reached one billion users.

The figures are company-reported measures, not an independent comparison of model adoption or quality. Google also said Gemini 4 Argon’s first-week usage on its developer platforms ramped three and a half times faster than Gemini 3, even with capacity constraints. Its leaders framed the figures as evidence that model demand is pulling on cloud and TPU capacity, rather than as proof of a particular customer outcome.

Microsoft reports cloud growth alongside its AI investment accounting

Microsoft reported $92.3 billion in revenue for the quarter ended September 30, up 19% year over year, and said Microsoft Cloud revenue reached $63.9 billion, up 30%. Azure revenue increased 48%, according to the company’s release.

The company separately identified the effect of its OpenAI investment in its non-GAAP presentation. It reported GAAP net income of $36.6 billion and non-GAAP net income of $36.4 billion after the stated adjustment. Microsoft said commercial remaining performance obligations rose 73% to $677 billion, a forward-looking contract measure rather than booked revenue.

The release does not isolate how much of the cloud growth came from any one AI product. Still, it gives a current view of the infrastructure base supporting Microsoft’s AI push and the scale of commitments it says customers have already made.

Meta funds university projects, while the clinical work remains early

Meta said it is providing $2 million in grants and model access across five U.S. university partnerships: Caltech, Ohio State University, Louisiana State University, Indiana University and UTHealth Houston. The company says the projects span medicine, physics, chemistry, biology, computer science and mathematics.

Some of the medical examples are explicitly exploratory. Louisiana State University’s Eyes-On project is developing a computer-vision system to detect possible tracheostomy-tube displacement and distress in infants; Meta says a proof of concept has been published and more work is needed. Ohio State researchers are investigating whether Meta’s open-weight models can help predict future risk of a form of heart failure using imaging, records and ECG data when available.

Those descriptions are research plans and early-stage projects, not clinical validation or evidence of improved patient outcomes. The useful signal is the funding and model-access arrangement; the medical claims will need results, independent review and appropriate clinical evaluation before they can be treated as established care.