Microsoft lowers AI software sales quota, shares fall nearly 3%, marking the biggest drop in half a month.

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Microsoft has lowered sales targets for some AI software, as enterprise customers have been slower than expected to adopt new artificial intelligence products.

On December 3, according to media reports, Microsoft’s Azure cloud division has reduced sales quotas for specific AI products after its sales team failed to meet targets for the fiscal year ending June this year. Insiders say such quota reductions for specific products are rare at Microsoft, reflecting the company’s strategy adjustment based on actual market acceptance, responding to customer caution in increasing AI budgets.

Last fiscal year, a Microsoft Azure sales team had required salespeople to increase customer spending on a product called Foundry by 50%, but less than one-fifth of the sales staff met the target. Therefore, in July this year, Microsoft lowered this product’s growth target for the current fiscal year to about 25%.

Affected by this news, Microsoft’s stock price once fell by 2.9%, its largest drop since November 18. Subsequently, according to media reports, Microsoft stated in an email that the company had not reduced sales quotas for sales staff, trimming the decline to 1.7%.

Industry analysts point out that this adjustment reveals common challenges companies face when deploying advanced AI tools: On one hand, the actual cost savings from technology are difficult to clearly quantify; on the other hand, in fields such as finance and cybersecurity where tolerance for error is low, the reliability and business value of AI tools still need further validation over time. Although Microsoft’s cloud infrastructure business continues to grow due to demand for training large models like OpenAI's, progress in getting traditional enterprises to buy more complex automation software has not met previously optimistic expectations.

Microsoft is not the only one facing similar challenges. OpenAI recently slashed its five-year revenue forecast for “AI agents” by $26 billion, while companies like Salesforce are using significant discounts to attract customers. This shows that, although generative AI remains a hot technology, it still faces many real-world obstacles on the path from concept demonstration to large-scale business application.

Enterprise Customers Face Implementation Difficulties

Private equity firm Carlyle’s case highlights the real challenges companies face when adopting AI tools. Last year, the company began using Microsoft's Copilot Studio, a tool that allows companies to develop AI applications by writing code to automate tasks like meeting note organization and Excel financial model generation.

However, after several months of use, Carlyle reported to Microsoft that the tool struggled to stably extract data from other business systems such as Salesforce, which is crucial for some of its automation processes. According to sources, this autumn, Carlyle reduced its spending on the tool. This adjustment is part of the company’s overall plan to optimize AI spending and integrate its tools.

Industry-wide Lowered Expectations

Microsoft is not the only company to adjust revenue expectations for AI agents. For example, OpenAI recently cut its five-year revenue forecast for AI agents by $26 billion. The company plans to fill this gap by increasing revenue from ChatGPT subscriptions and launching new products that may include advertising. In fact, its CEO Sam Altman said this Monday that the company would temporarily pause its agent business in fields like advertising and healthcare to focus on solving existing issues with ChatGPT.

For enterprise software companies such as Salesforce, the challenge of increasing AI agent revenue is even greater, since they lack large cloud infrastructure businesses like Microsoft's to support them.

To address this, Salesforce and ServiceNow are offering significant discounts to clients trying their AI agent products, which aim to automate tasks such as IT ticket processing and new employee onboarding workflows. Meanwhile, other tech companies including AWS and Anthropic are providing consulting-like services and investing resources to help clients configure and deploy AI applications correctly.

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