Starbucks Just Fired a Warning Shot at AI Apps from Microsoft and IBM (Photo Illustration by Budrul Chukrut/SOPA Images/LightRocket via Getty Images)
SOPA Images/LightRocket via Getty Images
According to Yahoo Finance, Starbucks spends about $400 million annually on software. This week, Bloomberg reported that the coffee giant is developing its own AI-powered replacement solutions for a Microsoft inventory tracking system and an IBM maintenance management platform. Some of the new AI tools could be rolled out by the end of next year, pending testing.
The market reacted immediately.
IBM fell about 3% in premarket trading. ServiceNow fell 3.5%. Salesforce fell 4%, according to Yahoo Finance. None of these companies lost a contract that morning. What they lost was part of the story that supported enterprise software valuations for two decades.
The story that big companies will always buy because building is too difficult.
Now look at who barely moved. Microsoft, one of only two vendors actually named in the report. That’s because Microsoft sells the inventory application that Starbucks is replacing, and also sells the Azure cloud and AI infrastructure on which Starbucks will build the replacement. Starbucks’ barista tool Green Dot Assist already runs on Azure OpenAI.
IBM, ServiceNow and Salesforce live at the application layer, the very layer that Starbucks just proved a coffee company can rebuild internally.
ServiceNow and Salesforce were never mentioned by name. The market sold the presence, and pure-play application providers own most of it.
This story is groundbreaking.
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Why this Starbucks moment is different
Companies remained tied to suppliers for years for two reasons.
Developing software from scratch was slow and expensive, and ripping out a system that runs thousands of sites was daunting. So companies paid for platforms that were perhaps 70% true to how they actually worked, and then paid consultants to whip the remaining 30% into shape.
AI-powered development changes this math.
Starbucks CTO Anand Varadarajan told employees that there are clear opportunities to reduce software spending and the company is now reviewing every contract and service as part of a broader $2 billion cost reduction under CEO Brian Niccol, according to MSN.
The logic is simple.
If your engineers already have to heavily customize a vendor’s product to make it usable, and AI now enables those same engineers to create a useful tool in a fraction of the time, why should you continue to pay the license fee?
This is not a Starbucks story.
It’s a preview of the build vs. buy recalculation that’s currently taking place in every Fortune 500 technology budget.
Mati Greenspan talks about the power of AI to transform the software industry.
Dead Greenspan
“Companies are realizing that AI isn’t just a function. It’s becoming the central nervous system of their operations,” Mati Greenspan, founder and CEO of Quantum Economics, told me. “This move signals a strategic shift in which companies demand comprehensive ownership and customization of their AI and withdraw critical technologies from external providers to secure a unique competitive advantage.” Note that his assessment came from his AI financial assistant, Korra AI.
The part of the Starbucks story that everyone skips
There is something that is missing from current stories.
Starbucks isn’t completely leaving Microsoft and IBM. It still runs on third-party software, including Microsoft’s cloud and AI infrastructure. And earlier this year, Starbucks discontinued an AI-powered inventory counting system after it provided inaccurate counts and switched stores to manual inventory counts.
Microsoft Azure, as the AI infrastructure has not suffered a collapse. Success came with these application providers. (Photo by Jaque Silva/NurPhoto via Getty Images)
NurPhoto via Getty Images
This failure is important and makes the current move more credible, not less.
Starbucks learned the hard way what I called AI Hollowing. Embedding AI into a broken process will not fix the process. It reinforces the fracture while the underlying capability silently erodes.
The new approach initially targets the workflow. Correct how inventory and maintenance actually work, then build the system around the corrected process, and then let AI speed up the build.
Aaron Levie, CEO of Box, put it well in his Linkedin post: “The best use cases for AI tend to be those that fundamentally change the work being done, rather than just replacing an existing process and making it more efficient. Companies work through their versions of this individually because it varies by industry, but this often remains both the most exciting and promising use of AI.”
Aaron Levi discussed the power of redesigning workflows as a path to AI project success. (Photo by Justin Sullivan/Getty Images)
Getty Images
This order is everything.
Data consolidation, process redesign, then AI. Companies that skip the middle step end up with expensive tools that automate bad decisions more quickly. This is a best practice to ensure you redesign the process.
What happens next, driven by the Starbucks story
Expect four ripple effects, and business leaders should pay attention to these steps.
First, providers will fight back on the terrain that is hardest to reproduce. Depth of integration, governance, security and decades of accumulated domain knowledge. Watch as Microsoft, IBM and Salesforce reposition themselves from application sellers to infrastructure and trust providers.
Second, more companies will run the Starbucks game on their most expensive and least popular systems. Internal tools don’t have to replace commercial software overnight. They begin as targeted replacement solutions where vendor fit is worst and licensing costs are highest.
Third, a new service economy will emerge around the transition. Someone needs to map the processes, consolidate the data, and design the systems that these companies will now have. The winners will be operators who understand that the technology is the easy part. Redesigning how a company actually works is the hard part and a deeply human job. Judgment, context, and change management do not come from a coding wizard.
Fourth and furthest out, motivation itself begins to wane. Once agents have consolidated systems with sufficient historical and personal data, they no longer have to wait for instructions. They automatically complete repetitive tasks, respond to them, and predict needs through pattern matching with millions of similar users. This future is coming whether we design for it or not. The only question is who owns the data these agents run on. Companies and individuals who control their own systems receive accommodations on their terms. Everyone else is predicted by someone else’s platform.
The lesson from Seattle is not that AI writes software cheaply.
It’s that AI has once again made it possible for companies willing to do the inglorious process work first to take over their own operations.
Starbucks just showed us what that looks like on a $400 million line item.
https://www.forbes.com/sites/sandycarter/2026/07/12/starbucks-just-fired-a-warning-shot-at-microsoft-and-ibm-ai-apps/
