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Workers who use Microsoft software seem to be having as many conversations with Copilot AI as with real humans in Outlook and Teams, Microsoft said Wednesday during its fiscal year 2026 fourth-quarter earnings call.
“The number of conversations per [Copilot] user nearly doubled year over year,” Microsoft CEO Satya Nadella said on the call. “Average weekly engagement is on par with Outlook and Teams.”
There are over 30 million paid Microsoft 365 Copilot seats. And the way these workers are using AI is changing, too. Two months after Microsoft introduced Agent 365, a way for its business customers to build and use agentic AI, it has registered nearly 40 million agents across more than 10,000 companies, Nadella said.
“The agentic era is being built on GitHub,” Nadella said, referring to the developer platform Microsoft owns. “Every major coding agent runs on the platform, and one in three pull requests on GitHub now involves an agent.”
Microsoft beat investor expectations, reporting 18% revenue growth year-over-year for the quarter, which the company attributed to its AI and cloud services. Azure surpassed $100 billion in revenue for the first time ever. The company also attributed a $3.2 billion gain to its stake in Claude maker Anthropic. (Xbox severance and “impairment” charges were noted as hurting Microsoft’s financial health, as the parent company laid off 3,200 Xbox employees earlier this month, but that didn’t stop Microsoft from reporting just over $35 billion in net income.)
Like every other tech company, Microsoft has invested significant money and manpower behind its AI system, Copilot. And it seems its expensive bet on AI is possibly returning some cash on its investment; Nadella said Copilot revenue increased 60% quarter-over-quarter. But the spending isn’t slowing down; Microsoft added 31 new data centers across five continents.
The Redmond-based company has steadily and insistently integrated its AI into its software, which was already the backbone of corporate America. US adults say help with work is one of the main reasons they use AI, second only to searching for information, according to a recent Pew Research Center report.
Now, the company is betting not only that its customers will adopt AI, but that it will be so thoroughly integrated that it “transforms” how work is done – and how success is measured.
Moving past ‘time saved with AI’
In the early days of AI adoption, executives and tech enthusiasts were invested in the idea that AI tech could help employees do their work faster. Stories of AI automating repetitive processes and saving people hours of work were common.
Now, in the age of agentic AI, with agents that can autonomously complete tasks, the way people are using AI is changing.
Ideally, this should lead to “deeper cognitive work across the ecosystem,” Matt Firestone, general manager of product marketing for Copilot, tells me.
AI-native workers can distinguish between when they only need a quick answer from AI and when they need to use more advanced models or tools to handle more complex tasks, where there is also more human direction, engagement and approval.
“It’s not just about automating everything that we need to do to be more efficient. It’s about developing that judgment,” says Firestone.
And Microsoft has been busy building these more advanced, autonomous AI tools to help with those more complex assignments. Its Copilot Cowork uses a team of agents to write reports, send messages and do personalized analysis, all of which is grounded in your documents and messages. It’s very similar to Claude Cowork, which sparked fear across Wall Street when investors saw how productive it is at software tasks when it was released at the beginning of 2025. When testing Copilot Cowork and Claude Cowork with a Microsoft 365 connector, Microsoft found that using its own Cowork tool was on average 30% to 40% cheaper to run.
Microsoft has leaned all the way in on agentic AI. Scout, which Microsoft calls an “always-on personal agent,” was introduced shortly after at Microsoft Build; it’s specific to your Teams and Outlook messages, flagging important notes and helping you with meetings and assignments.
Having agents assist with deeper cognitive work, not just answering questions, helps companies prove the usefulness of AI – a way to expand the metrics by which we judge its success or failure. Instead of just looking at time saved, companies are now looking at how agents enhance workflows, do analysis that couldn’t be done by hand and handle specialized tasks outside of just software development.
Take Kantar, for example. The marketing data and analytics company has been steadily and thoroughly integrating Copilot AI and agents into its operations over the past two years, with its HR team, not software, leading the way. It used a system of 10 agents, grounded in the company’s existing policies and procedures, to handle some employee inquiries to HR, like requesting and generating employment verification letters. AI took over 40% of those kinds of requests since the tech was implemented, with a goal of reaching 95% by the end of the year.
The human HR experts’ time was saved, but the AI agents also increased output, allowing human workers to focus on other projects. John Dicken, senior director of AI people solutions, says that applying an organizational lens to the company’s AI integration helped the company.
“A lot of people I talk to think of AI tooling as tech. I think of it as capability,” Dicken says. “It’s a technical solution to bring in capability to the organization in a different way, to bring new skills, new understanding, new knowledge, new approaches, new thought design.”
For some folks, that ability to take on more work means getting to tackle projects they’ve been waiting to have the time to do. But for others, it means having to do more work for the same pay. That can lead to a kind of AI-powered burnout, a University of California, Berkeley study found, where even with AI, we end up with longer workdays and worse work-life balance.
The ROI on AI is not just a matter of corporate talking points. Big and small businesses are paying big bucks to tech companies for the ability to run, license and personalize AI tools. And those tech companies, in turn, are asking investors for eye-watering sums to keep developing the models that power chatbots and agents.
It’s created a monster of a trillion-dollar industry, and measuring its success in multiple ways, beyond time saved, may be vital to proving its usefulness and avoiding popping the AI bubble.
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