In an internal memo to employees on Tuesday, Microsoft’s CEO stated that the company will merge the teams responsible for developing Copilot for both consumer and enterprise users. The goal is to streamline product development and enable the AI assistant to reach a broader customer base more quickly.

Under the new structure, senior executives from Microsoft’s AI division will lead the unified Copilot development teams across both individual and enterprise segments. At the same time, the head of the AI division will shift more focus toward artificial intelligence model research, with an emphasis on strengthening Microsoft’s in-house AI capabilities.

Microsoft’s early integration of AI models into its product ecosystem has been largely driven by its partnership with OpenAI. Leveraging technologies such as ChatGPT, Microsoft has launched a series of AI tools under the Copilot brand, embedding them into a wide range of products, including office software and consumer applications.

As competition in artificial intelligence intensifies, Microsoft has been simplifying its Copilot product lineup in recent years by reducing the number of standalone offerings, aiming to deliver a more unified AI platform experience. Meanwhile, the company is clearly strengthening its foundational AI capabilities. The shift of focus toward model development rather than individual products signals Microsoft’s intention to reduce its reliance on OpenAI and gradually build its own core model ecosystem — transitioning from an application integrator to a provider of foundational AI capabilities.

Market Interpretation:

This restructuring marks Microsoft’s AI strategy entering its second phase — shifting from rapid expansion and user acquisition toward mid-term integration and capability enhancement. In the short term, this move is expected to improve product clarity and operational efficiency. However, it also reflects that Microsoft’s earlier AI deployment may have been somewhat fragmented and still requires time to optimize. Microsoft is now significantly increasing its investment in research and development, aiming to build AI models that can deliver meaningful impact in real-world applications.