The company plans to combine chat, agents and business workflows into a single AI workspace while separating memory, context and orchestration from any one foundation model.
All of the major AI providers want you to use, and ideally stay within, their super apps, and now Microsoft is looking to capture that attention, too.
During an earnings call this week, CEO Satya Nadella confirmed that the tech giant is building a Copilot ‘super app’ that will be rolled out this quarter. The new platform will bring together various Copilot tools, including chat, Cowork, long-running Autopilot agents, and the always-on Microsoft Scout, powered by OpenClaw.
Microsoft said the super app will be wired into many of its other governance platforms, including Agent 365, IT Ops, SecOps, FinOps, and business processes. And, it said, CRM and ERP systems will “serve as skills and plug-ins that go into core work.”
“You’re able to take that enterprise-wide workflow and wire it into the super app,” Nadella said, describing it as “the coming together of a new way to work.”
With this move, Microsoft will compete with OpenAI’s ChatGPT Work, Claude Cowork, and a growing number of others trying to capture as much of a user’s workflow as possible. It could prove a strong contender, as everyday Copilot “usage intensity” is at the same level as that of Outlook or Teams, Nadella said, and paid seats now surpass 30 million.
Every model should be ‘swappable’
Even as it builds a super app to bridge workflows, Microsoft is acknowledging enterprise demand for model choice. Customers are making it clear that they don’t want to be locked into one model; they want the ability to move between open, closed, and frontier options based on the best tool for the job.
This trend is reflected in Redmond’s own usage statistics: Since the beginning of the year, it has tracked a 5x increase in the number of customers building with models from multiple providers featured on its platform.
The company claims it has the broadest model catalog in the cloud, offering more than 11,000 models from OpenAI, Anthropic, Mistral, its own MAI family, and others.
“We are building a new model system, where the harness, context, memory, and action space are separate from any one model family, thereby moving the frontier on the cost-to-outcome curve,” Nadella said. “That’s really the enterprise design architecture that we are going to evangelize.”
He described enterprises as “learning machines” that need their own internal learning machines, and said that they will be evaluating how providers are helping them reach their business goals and support knowledge creation.
“The models are an input, not some extraction of the knowledge of the enterprise,” Nadella said. “This is not going to be about, ‘come in and take all my knowledge and benefit yourself, [and] I am not getting anything out of it.’”
The key is in balancing the advantages of frontier models with lower-cost options, open weights with closed weights, and having the ability to train internal models based on outputs, traces, and context. “You should and you can use frontier models,” Nadella said. “There’s no reason not to.”
However, he said, any given model at any given time should be swappable to democratize design.
For instance, data from cybersecurity evaluation framework CyberGym showed that Microsoft’s new MAI-Cyber-1-Flash coding agent achieved Claude Mythos-level performance at 50% of the cost. This is because 90% of tasks were completed by Cyber-1-Flash and 10% by frontier models from OpenAI, Anthropic, and others.
This ability to use the right model for the right task in what is essentially a pipeline job is a “super important characteristic,” Nadella said. Microsoft Copilot, Security Copilot, and GitHub Copilot are all built to support movement between different models based on the task.
This strategy is also reflected in the company’s new Project Perception cybersecurity offering. The platform features three specialized types of agent (red, blue, and green), and the underlying harness decides which AI model is best suited for a given task. Guided by specialized playbooks, red team agents discover vulnerabilities, blue team agents triage, and green team agents propose remediation plans.
“You create your own agentic system that’s continuously operating to create the cyber defense you need,” Nadella explained. “Especially in cyber[security], it becomes critical to have that multi-model approach.”
Nadella also pointed to the recent Hugging Face incident, in which an OpenAI model went rogue, broke out of its sandbox, and launched an attack against the popular open-source platform, noting that enterprises will likely need to use multiple models to offset and remediate the various challenges of each, and should not be “subject to the refusals of one model.”
“We talk about the frontier as if it’s one thing,” Nadella said. “The frontier is about every firm having a frontier, the choice, the cost control, and the capability that they need in order to be able to control their destiny.”
Increased push to usage-based pricing, closing demand gaps
As Microsoft emphasizes its model-agnostic architecture, it is also shifting from per-seat to per-seat-plus-consumption pricing; the company recently added usage-based billing to Cowork and Agent 365, and plans to continue that trend across its products.
While these moves have resulted in sticker shock and ‘tokenmaxxing’ at many companies, Nadella framed it as a revenue driver. “We are advancing the frontier on the cost-to-outcome curve, ensuring every customer can turn tokens into business results.”
Meanwhile, Microsoft said it will continue to close data demand-capacity gaps.
The company added 88 data centers in FY 2026, including 31 across five continents this past quarter. It contended that it is bringing capacity online “faster than ever,” reducing dock-to-live times for new GPUs in its largest regions by nearly 50% over the fiscal year.
However, CFO Amy Hood acknowledged during the earnings call, “the situation is obviously that demand exceeds available supply in a relatively extreme moment.”
Reflecting this, revenue for Azure and other cloud services grew by 43% in Microsoft’s fiscal year ended June 30, and the company expects similar revenue growth (45%) in fiscal year ‘27.
Hood said that Microsoft remains “focused on delivering efficiencies,” including in its CPU and GPU fleets, and engineers are also working on process improvements. The company added another gigawatt of capacity this quarter and is on track to roughly double its overall capacity in two years.
“We are also getting more from the infrastructure we already have by optimizing across silicon, systems, and software,” Hood said.
This article originally appeared on CIO.com.
