Artificial intelligence is one of the most closely watched growth drivers in the technology industry as investors and customers assess whether a sharp jump in AI spending will translate into future revenue. While large vendors are rushing to embed generative AI into cloud services and productivity software, many corporate buyers are still wary about making large-scale commitments. With that as the backdrop for this story, any suggestion of expectations being recast has outsized weight, especially when it involves one of the industry’s largest and most influential players.
Rumours of a reality check
Earlier this week, Microsoft moved quickly to push back against a report that it had cut internal sales targets for certain of its artificial intelligence offerings because customers were slow to buy new products.
The company denied reports that it slashed quotas for AI sales after some sales teams missed aggressive targets. The report, which cited people familiar with the matter, said Microsoft had lowered expectations for some AI offerings after slow adoption. Microsoft disputed the characterization and said overall AI sales targets have not changed.
The aftermath
Shares of Microsoft, which had been down by almost 3 percent in early trading, pared losses after its response. The stock was last down about 1.7%. Reuters, however, was not able to independently confirm the report, which first appeared in The Information.
The report described internal pressure within Microsoft’s U.S. Azure sales organization, where one unit had allegedly set quotas requiring sales staff to get customers to spend 50% more on Foundry, a tool for building A.I.-powered applications. Less than one in five salespeople achieved those targets, the report said. Additionally, Microsoft was rumored to have reduced growth forecasts for its FY during this year to roughly 25%.
“Business as usual” for Microsoft
Microsoft said it regularly updates its sales planning and that demand for its AI tool is strong. AI remains one of the company’s fastest-growing segments, including Azure infrastructure and Copilot features embedded across its software portfolio, a spokesman told Reuters.
Yet the report landed at a time when there is increasing evidence that corporate AI adoption is lagging, and not moving nearly as quickly as those rosy vendor forecasts would seem to indicate. A recent study from MIT found that around 5% of AI projects graduated beyond the pilot, showcasing the challenges associated with scaling delivery.
If we had to choose one word to characterize enterprise buying right now, 'hesitant' would be apt. Companies experimenting with generative AI tools frequently slow down or never move beyond trials because of issues around integrating data, governance demands, and uncertain returns on investment, all of which make it difficult for vendors to translate early interest into sustained revenue.
Big budgets vs a cautious enterprise
The episode highlights a growing mismatch between the pace of AI development and people’s willingness to commit at scale. Microsoft, which also made it clear that there wasn’t enough demand for its computer capacity, is continuing to pump billions into its AI infrastructure.
For now, Microsoft claims it is sticking to both its AI strategy and its sales goals. Whether enterprise adoption will rise quickly enough to meet those expectations remains the big question in the world of AI and technology.
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