AI reshapes enterprise IT! Starbucks launches "self-developed software," posing new challenges for Microsoft and IBM

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AI is not only changing the way software is developed, but also transforming the logic by which enterprises procure software.

On July 9, according to an internal presentation obtained by Bloomberg, Starbucks is accelerating its internal software development, hoping to leverage AI to boost development efficiency and gradually replace some of the commercial software it has long purchased. The targets include Microsoft’s inventory tracking system, IBM’s equipment maintenance management tool, and the Oracle Simphony point-of-sale (POS) system that has been implemented for years.

If these projects proceed as planned, some replacement software could complete testing and be put into use as early as the end of next year. This means AI-driven changes are evolving from enhancing development efficiency to prompting large enterprises to reassess their software procurement model, bringing new competitive pressure to traditional enterprise software vendors.

Since the start of this year, both Microsoft and IBM’s stock performance have lagged behind the S&P 500 Index, as concerns continue to rise in the market about whether AI will erode the moats of traditional software suppliers.

$400 million annual software spend becomes cost-cutting focus

The most direct reason for Starbucks to push internal software development is cost reduction.

Starbucks CTO Anand Varadarajan stated in an internal forum earlier this year that the company spends about $400 million on software annually, “there is obvious room for optimization here.” He made it clear to employees that the company hopes to reduce reliance on external software.

Software costs are just one part of Starbucks’ overall cost reduction plan. The company is currently advancing a $2 billion cost-cutting plan. According to the internal presentation, by the end of the fiscal year at the end of September, the enterprise technology department expects to save about $30 million in budget, around $10 million from software purchasing expenses, and another $13 million from reducing external consulting and professional services, shifting these tasks to internal teams.

At the same time, Starbucks is adjusting its technology team layout, expanding tech centers in Nashville, USA and India, while retaining the R&D team at its Seattle headquarters. Since February last year, the company has eliminated about 2,300 positions, with the tech department also affected.

AI programming lowers internal development barriers

AI is an important catalyst for Starbucks’ push towards internal software development.

Internal data shows that in the process of developing a platform to replace IBM’s equipment maintenance system, AI-assisted programming has undertaken core development tasks, greatly boosting development efficiency. Starbucks has continually promoted the use of generative AI internally in recent years. Bloomberg previously reported that the company has even included employees’ use of AI tools in performance bonus evaluations to accelerate AI adoption in R&D teams.

An official blog released by the company earlier this year also stated that AI and other digital technologies will become important pillars for long-term growth in the future, and will help baristas reduce back-end tasks, allowing them to spend more time on customer service.

Besides developing new systems, Starbucks is also comprehensively reviewing existing IT contracts. Internal documentation shows the company is reassessing “every contract and every service,” and for software that originally requires heavy customization, internal development is gradually becoming the preferred option.

Internal development still faces long-term challenges

However, developing software in-house does not come without costs.

While self-development can reduce license procurement costs, long-term maintenance, ongoing upgrades, and technical team expansion often mean higher labor and operational costs. This is the classic trade-off faced by large enterprises. A recent attempt by Starbucks reflects this reality. The company previously launched an AI-driven inventory management system that has since been withdrawn, reverting to manual stock counting to address accuracy issues encountered in actual operations.

Meanwhile, Starbucks still uses multiple third-party software products—including Microsoft—in the short term, and has not completely freed itself from external suppliers. More importantly, there remain clear disagreements in the market about the extent to which AI can autonomously develop complex enterprise software.

For the entire software industry, Starbucks’ attempt may just be the beginning. As AI continues to push down software development costs, more large enterprises with sufficient technical teams may begin to recalculate a question that has rarely been seriously discussed: whether to continue buying software or build it themselves.

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