Microsoft is trying to show that some of the work that happens in cloud computing centers can be moved to Windows devices at work and at home, according to the report. In these environments, it is the customers paying the hardware bills. Apple is pursuing the same opportunity with its new computers.
The move also gives Nvidia a chance to pursue one of the last major markets dominated by competitors such as Intel and Advanced Micro Devices, the report said.
A major challenge for Microsoft and Nvidia is demonstrating that AI agents can be contained on personal computers following a series of incidents in which agents at several tech giants hacked third-party websites, according to the report.
Analysts said an even bigger question will be the price of the new offerings after a memory-chip shortage has ramped up costs for desktop and laptop machines, per the report.
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Anshel Sag, an analyst at Moor Insights & Strategy, said the memory prices are impacting Apple and Microsoft’s efforts alike, according to the report.
Two years ago, “the software wasn’t ready, but the hardware was,” Sag said, per the report. “Now the software is ready, and the hardware is too expensive to actually run it locally. So, it’s becoming this thing where only the people who have the budget can really afford to run AI locally.”
In June, Microsoft and Nvidia announced a new type of Windows PC designed for agentic computing, PYMNTS reported June 1.
“For years, enterprise artificial intelligence has lived in the cloud,” the report said. “Employees typed prompts into browser windows, queries traveled to data centers and responses came back. That model suited hyperscalers. It suited corporate IT and security teams less.”
The pitch to enterprise customers is a chance to keep data, decisions and agents in-house.
“For enterprise buyers, the case centers on what stops leaving the building,” the report said. “Agents running locally can work across files, calendars and internal applications without sending data to a third-party server, cutting the latency, privacy exposure and usage costs that come with constant cloud inference.”
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