Microsoft Joins AI Cost Cutting Trend by Relying More on Its Own Models

As artificial intelligence costs continue to rise, companies across the tech industry are looking for ways to cut back. The most recent example is Microsoft, which has reportedly begun to deploy a cost savings strategy by relying less on software from OpenAI and Anthropic and instead deploying its own in house models.

Shifting Away From Third Party Providers

When it comes to two of its most widely used programs, Excel and Word, Microsoft has begun to use its homemade MAI models to respond to a certain percentage of user prompts, Bloomberg reported Tuesday. In the past, the company had advertised the fact that large parts of Office 365 are powered by models from both OpenAI and Anthropic.

While Microsoft still relies on those third party models, it has also increasingly sought to stand up its own AI agents. Last month, at its annual Build conference, the company announced the launch of seven new MAI models, including an agentic coder and a text to image generator. When reached for comment by TechCrunch, Microsoft said that it had nothing further to share.

Part of a Broader Industry Trend

Microsoft’s apparent cutbacks are part of a broader trend. After a brief blitz of “tokenmaxxing” earlier this year, the last few months have seen a news cycle awash in stories about tech companies acting significantly more thrifty. Other large companies like Amazon, Uber, Meta, and Accenture have also reportedly made moves to curb spending.

The Rising Cost of AI Services

The immense cost of providing and buying AI services has become a controversial part of the industry. The sticker shock has gotten so bad in some parts of Silicon Valley that some companies are reportedly looking to Chinese models for more affordable agentic solutions, despite some concerns over potential security issues.

What This Means for the Future

Microsoft’s move to rely more heavily on its own AI models represents a significant shift in strategy. By developing and deploying its own MAI models, the company can potentially reduce its dependence on expensive third party providers while maintaining competitive capabilities in its core productivity software. This approach mirrors a wider industry movement toward cost efficiency in AI development and deployment.

As the AI landscape continues to evolve, it is likely that more companies will follow this path, seeking to balance innovation with fiscal responsibility. The trend toward building in house AI capabilities may reshape the competitive dynamics of the industry, potentially challenging the dominance of major AI providers like OpenAI and Anthropic.

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