Microsoft (MSFT +5.25%), a global software and cloud solutions provider, closed Friday at $450.24, up 5.45%. The stock moved higher on reports of stronger AI-driven revenue, in-house model development to cut costs, and Xbox and software strength. Investors are watching how its evolving usage-based pricing and hybrid AI-cloud model sustain growth.
The company’s trading volume reached 77.2 million shares, which is about 124% above compared with its three-month average of 34.5 million shares. Microsoft went public in 1986 and has grown 463000% since its IPO.
The S&P 500 (^GSPC +0.22%) added 0.23% to finish at 7,580.06, while the Nasdaq Composite (^IXIC +0.20%) gained 0.22% to close at 26,972.62. Within software – infrastructure names, industry peers Apple (AAPL 0.20%) closed at $312.06 (-0.14%) and Alphabet (GOOGL 2.54%) ended at $376.43 (-2.51%), trailing Microsoft’s strong session.
Microsoft shares rose after the company said its AI business surpassed a $37 billion annual revenue run rate, giving investors a clearer measure of how AI demand is translating into cloud and software revenue. The figure reinforces Microsoft’s advantage in tying AI tools to Azure, Microsoft 365, and developer workflows rather than treating AI as a separate product cycle.
Reports that Microsoft is preparing more in-house AI models add a cost-control angle to that growth. The company is not stepping away from OpenAI, but internal models could give Microsoft more flexibility over which AI workloads it runs, how those features are priced, and the margin pressure that comes with higher usage. Future earnings and product updates will show if more Azure use, Microsoft 365 Copilot adoption, and usage-based AI pricing are helping AI revenue grow while keeping the cloud business profitable.
Eric Trie has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Alphabet, Apple, and Microsoft. The Motley Fool has a disclosure policy.
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The $37 billion AI run rate gives Microsoft a clearer monetization benchmark, while in-house models could help manage the cost of serving AI demand across Azure and Microsoft 365.
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