AI Is Wreaking Havoc at Starbucks and Pizza Hut. Social Media Is Having a Field Day

AI woes are coming for the food service industry, and social media can’t help but celebrate. This week, both Starbucks and Pizza Hut made headlines for negative news about their internal applications of artificial intelligence. At Starbucks, an inventory tool got the chop after making frequent counting mistakes, while at Pizza Hut, a delivery tool drove a franchisee to file a lawsuit. Social media users are saying the two stories may point to a larger trend—that for the first time in the AI era, more companies will pull away from AI than embrace it. Starbucks walks back an AI tool On Monday, Starbucks told employees it was retiring an inventory-counting tool powered by AI after the technology led to inaccurate counts and mislabeled products. “Starting today, Automated Counting will be retired,” said an internal company newsletter verified by Reuters. “Beverage components and milk will now be counted the same way you count other inventory categories in your coffeehouse.” In a statement to Fast Company, a spokesperson for Starbucks explained that the company’s choice to axe its Automated Counting tool is in line with its larger AI strategy, which is based on trial and error. “We test ideas in our coffeehouses, listen closely to partner feedback, and make changes to deliver a better, more consistent experience.” Starbucks’s move to ditch one AI tool doesn’t mean the company is forgoing the technology entirely. The company is still investing in internal AI applications, including an AI assistant for baristas called Green Dot Assist and an AI-powered order-sequencing system called Smart Queue. The brand is also experimenting with an integrated Starbucks app within ChatGPT. Pizza Hut’s delivery system backfires Where Starbucks’s choice to nix its AI tool came from the top down, the anti-AI sentiment at Pizza Hut started with a disgruntled franchisee. In a lawsuit filed on May 6, franchisee Chaac Pizza Northeast, which operates more than 100 Pizza Hut locations, alleged that the company forced it to adopt an AI tool called Dragontail, which inadvertently pushed average wait times from under 30 minutes to over 45 minutes in more than half of all orders. The complaint explained that the issue wasn’t with Dragontail itself, but with the information the tool provided to DoorDash drivers. Dragontail is meant to optimize food delivery by giving delivery drivers real-time updates on order preparations and timing. But according to the lawsuit, its implementation in 2024 caused “cascading operational breakdowns and customer dissatisfaction,” resulting in more than an estimated $100 million in lost business and enterprise value. Reportedly, once DoorDash drivers could see the real-time status of multiple orders through Dragontail, they would wait inside restaurants until multiple orders were ready, meaning some orders were being held for up to 15 minutes after they were ready for delivery. Because Chaac Pizza Northeast relies on DoorDash for all of its deliveries, the franchisee alleged that the forced change to its delivery model had a major impact on its sales. At its New York City locations, Chaac said its sales swung from positive 10.19% to negative 9.78% after implementing Dragontail. “With the intention to improve efficiency and service to the customer, Dragontail did the exact opposite,” the lawsuit stated. “It caused significant delays and pummeled consumer satisfaction.” Pizza Hut has not responded to Fast Company’s request for comment. Social media sees a trend With the stories from Starbucks and Pizza Hut breaking in quick succession, social media users are drawing connections between the two food service chains’ AI troubles. “Over the next 1-2 years we’re going to start hearing more reports about companies pulling back from AI than adopting AI, and markets aren’t ready,” one X user theorized. “The AI bubble might burst quicker than I thought,” echoed another. “You’re going to be hearing a lot more about forced AI integration and what a disaster it is for businesses and consumers,” a third user agreed. Other users pointed out that all of these problems could have been avoided if tasks hadn’t incorporated AI in the first place. “To err is human,” one person quipped, “but to really screw things up, you need a computer.” By Jude Cramer

Instagram’s AI Support Bot Made a Costly Mistake. It’s a Warning for Every Company

Sometime last weekend, hackers asked Meta’s AI support bot for access to someone else’s Instagram account. The bot said yes. The method, reported first by 404 Media, was almost insultingly straightforward: instruct the chatbot to add a new contact email to a victim’s account, confirm the change with a code sent to that email, then use it to reset the password. In some cases, all that was also needed was a VPN to spoof the victim’s location. Among the accounts taken over: the former White House page from Barack Obamaʼs presidency, cosmetic chain Sephora, and the chief master sergeant of the U.S. Space Force. While this hack was obviously a security flaw, most businesses should consider that this blunder also reveals a management error. The front door is now automated AI customer service is everywhere. According to MarketsandMarkets, the global AI customer service market was valued at $12.06 billion in 2024 and is projected to reach $47.82 billion by 2030, growing at a compound annual growth rate of around 25.8 percent. The economics are hard to argue with: AI scales cheaply, doesn’t require shift management, and doesn’t call in sick. AI has been shown to cut response times by 37 percent and reduce operational costs by 35 percent. Companies have moved quickly. Banks use it for dispute resolution, airlines use it for rebooking, telecoms route complaints through it, and e-commerce platforms use it to handle returns. Around 80 percent of companies are either currently using or planning to adopt AI-powered chatbots for customer service by 2025. Meta is not unusual for deploying AI support at scale. When Meta launched its AI support assistant in March, it was presented as a way to help users reset passwords, regain account access, and report problematic content. These are not trivial tasks. Account recovery involves identity, security, and trust—the kind of territory that, not long ago, companies deliberately kept behind a human review process because the consequences of getting it wrong were considered too serious to automate away. Meta has also reassigned thousands of employees into AI-related roles and used AI to automate risk assessments of updates, safety features, and content moderation—all of which are tasks that previously required human review. Therefore, the support bot exploit arrived in an organization that had been replacing human judgment with automated processes across multiple functions simultaneously. Authority without judgement The exploit worked not because the AI behaved unpredictably, but because the AI behaved more or less as it was designed. A user asked it to update a contact email, and it updated the contact email. The system executed a process it was authorized to execute, but in doing so, handed a hacker the keys. This distinction matters enormously for anyone responsible for deploying AI systems. Authority can be automated, but judgment is a different problem entirely. A junior employee in a similar situation might also make a bad call. Humans fail too, but organizations know how to supervise, train, audit, and escalate human decisions. Real people typically offer something an AI system can’t: the ability to notice that something feels off. In this case, hesitation at an unusual request, the instinct to double-check account history, and the recognition that a request arriving via VPN from an unfamiliar location (asking to change contact details on a high-profile account), warrants a pause that could have prevented disaster. Gartner forecasted that 20 to 30 percent of businesses will replace human customer service agents with AI by 2026. The efficiency case for doing so is well established, but what’s less well examined is the category of decisions that look like processes but aren’t. Account recovery looks like a process, but embedded within that process is a judgment call: Is this request legitimate? Humans often make that call poorly too. The difference is that when a human makes it poorly, the failure is legible. There’s accountability. There’s someone to fire. Victims of the Instagram account takeovers told 404 Media there was no way to escalate their problem and speak to an actual human. Historically, high-stakes support requests — account recovery, fraud disputes, identity verification — were escalated to human agents because the potential for harm was too high to leave it to a scripted response. The escalation path was a precaution for the edge cases that automated systems weren’t designed to handle. Research published in the Journal of Consumer Research found that customers evaluate service provided by bots less favorably than identical service provided by humans, partly because they perceive automation as the firm cutting costs at the customer’s expense. That perception hardens quickly when customers discover there’s no human available at all. The harder problem The lesson here isn’t that companies shouldn’t deploy AI in customer service, but the quality of the decisions being made around where AI gets authority and what happens when it exercises that authority incorrectly. The questions that matter aren’t technical; they’re structural. What decisions can AI make autonomously, and which ones require a human to sign off? What triggers an escalation, and who owns it? When the AI gets something wrong — not if, but when — can a customer reach someone who can fix it? Gartner concluded in mid-2025 that half of the organizations expecting to significantly reduce customer service headcount because of AI would abandon those plans by 2027, and that 95 percent of service leaders planned to retain human agents in a digital-first but not digital-only model. The companies that arrived at that conclusion before Meta’s incident are in a better position than the ones who’ll arrive at it after. The Instagram story will probably be remembered as an AI security vulnerability, and will likely get fixed as one. As of June 3, it reportedly still hadn’t been patched. As companies race to automate customer interactions in pursuit of lower costs and faster resolution times, they’re discovering that it’s far easier to reduce the cost of executing a decision than it is to replace the judgment behind it. With better training, retrieval-augmented verification, anomaly detection for suspicious requests, and well-designed human-in-the-loop escalation, AI systems may be able to take on increasingly sophisticated judgment-like tasks over time. But deciding which requests deserve more scrutiny than the process allows remains, stubbornly, a human problem for now. AI can execute authority at scale, but the question that the Instagram incident forces into the open is a simpler one: When it gets things wrong, who’s responsible? Right now, the answer at too many companies seems to be nobody. BY CONNOR JEWISS

How to AI-proof your job

Meta. Nike. Intuit. UPS. It seems every day a new company announces layoffs, often citing AI as the cause. AI is already reducing US monthly payroll growth by roughly 16,000 jobs in the past year, according to a recent Goldman Sachs report. Knowledge workers face the sharpest exposure, as their output is exactly what AI replicates best, at superhuman speed, around the clock. “The most valuable jobs, the ones that we tell people to go to school for – software engineer, finance professional, accountant, lawyer – a lot of these cognitive professions, those are the ones that are the most vulnerable… to AI automation,” David Shrier, professor of AI & Innovation at Imperial College London, told CNN. But humans will always be needed in some form – and there are steps you can take to increase the chances you’ll protect your own job. Audit your role Before you can future-proof your career, you need a clear-eyed view of what you do in your job. Think of jobs as a “collection of tasks we switch between, often many times a day,” Oded Nov, a professor of technology management at New York University, told CNN. Consider which of those tasks are the most repeatable, rule-based computer tasks, like processing expense reports, which takes raw data and converts it into a different form. The more predictable a function, the more vulnerable it is to automation. The CEO of Cloudflare wrote in an opinion piece for the Wall Street Journal that he recently laid off 20% of his work force, focusing on “measurers”: middle management and those who work on audits, operations, compliance, etc. “AI isn’t coming for builders or sellers, but it is coming for measurers,” he wrote. “Tireless, independent, efficient and available, AI systems can now measure an organization with a level of objective detail and precision that was previously impossible even for the best employees.” Some jobs, such as those in hospitality, healthcare and skilled trades, still need someone physically present to do much of the work. Robotics is at least a decade away from replacing those roles. Invest in skills that are structurally hard to automate After your self-audit, focus on skills that are not repeatable, predictable and rule based. In addition to physical duties, AI is not yet as good at handling tasks that require emotional and social awareness, such as “understanding organizational culture or group dynamics,” Nov said. AI tends to be recursive, rather than inventive or creative. “AI is bad at creativity, but it’s surprisingly good at elaborating on creative prompts,” Shrier said. “But you still need the human to come up with the idea and guide the AI to do something interesting.” Invest in those skills. If part of your job involves sales and convincing people to sign a contract, focus on the interpersonal skills that help you build trust with clients. Customers might go to AI to research, but they usually still want to deal with a human being when making big purchases. Embrace AI and learn how to make it work for you AI will soon become a pervasive part of our lives, just like the internet. Get familiar with the major AI systems – ask various AI chatbots about your job and how they can help make your work more efficient, then give their suggestions a try. Play around with new coding tools that help you create your own app and website without needing to write your own code. But chatbots aren’t what makes AI so useful in the workplace, it’s AI agents, or programs that run automatically, make decisions and take actions autonomously. You can learn how to make your own, and a chatbot can help. Try the prompt: “I want to learn how to make an AI agent. Walk me through the steps to create an agent that can do [specific task]”. “In some ways it’s never been a better time to be an entrepreneur, because if you can think of it, you can make it,” Shrier said. “There are people making robust enterprise-grade software that is built off of a prompt in plain English.” Humans can’t be entirely replaced Even roles that include a lot of AI-achievable tasks will still need humans in some way. AI has particularly affected the coding industry. But Anthropic employees still edit and review code even if they’re not writing it, CEO Dario Amodei said at the World Economic Forum in January. “In best-case scenarios, the more mundane tasks that are part of people’s jobs today will be handed over to AI, while the more interesting and rewarding tasks will be done by humans, probably with some support of AI,” Nov said. “It’s very likely, if history is a guide, that new jobs, consisting of new collections of tasks, will be created.” By Hadas Gold

AI ‘voice cloning’ scams are on the rise. Here’s how to protect yourself

A California mom says she was scammed out of thousands of dollars this month after receiving a call that sounded like her daughter in distress. She now suspects it was an artificial intelligence-generated hoax. She’s one of many who have been targeted by so-called “voice cloning” scams as AI tools allow anyone to create a convincing replica of someone’s voice with only a few seconds of real audio. Americans lost more than $893 million to AI-related scams last year, including voice cloning attacks along with AI-generated phishing emails, romance scams and other hoaxes, according to the Federal Bureau of Investigation. Scammers can mimic anyone from family members and friends to coworkers or professional services workers. Banks including the United Kingdom’s Starling and the Commonwealth Bank of Australia have warned customers to watch out for voice cloning scams. Experts say AI voice replicas have gotten so realistic that most people can no longer reliably distinguish them from real human voices. “For the everyday person, it is just not fair to expect them to be able to spot this stuff,” said Henry Ajder, an expert on AI-generated media who consults for governments and companies. “I struggle with it. Most people do.” How do AI voice scams work? Scammers can create an AI replica of someone’s voice using a short recording of their speech — often pulled from social media or an earlier scam call that was surreptitiously recorded. Social media can also provide a trove of information about family members and close friends who could be targeted. Fraudsters will typically make it sound like the loved one they’re mimicking is in distress, purportedly having been kidnapped or in jail. Then they’ll urgently demand money in exchange for their loved one’s release. “There was no time to think,” Gary Schildhorn, a Philadelphia attorney who was targeted by an AI voice scam mimicking his son, told CNN last year. “It was all, ‘I have to react to help my son. He’s in trouble.’” In some cases, the AI voice may be more than just a single recording. Sophisticated attackers could use text-to-speech tools or “voice skinning,” which manipulate a scammer’s voice so they sound like the person they’re imitating in real time. Those techniques facilitate back-and-forth conversations between the target and the AI clone voice, potentially making the scam more convincing, Ajder said. Hackers can also make it appear as if a call is coming from a known number through a tactic known as caller ID spoofing — so you can’t necessarily trust that a call that appears to be coming from your mom is indeed her. How to avoid falling victim to AI voice scams Strange pauses or vocal fluctuations were previously considered red flags that a caller’s voice might be AI-generated. But those signals may no longer be present now that AI has advanced. Instead of trying to determine whether a voice is authentic, look for other general scam warning signs, Hany Farid, a professor at UC Berkeley and chief science officer at GetReal Security, told CNN last year. Is the person on the other end giving a deadline or introducing a sense of urgency? Are they encouraging you not to tell anyone else what’s happening? Are they asking you to move large sums of money in unusual ways? Those are the types of questions experts say to keep in mind. Targets who receive these types of calls should try contacting their loved one through other means, such as via a text message, calling them on another person’s phone or reaching out to someone who would know where they are. Deborah Del Mastro, the California mom recently targeted, told ABC7 News that she called her daughter only after sending money to the scammers. Her daughter answered right away and was at work. Families or coworkers can also establish a precautionary “code word” that can be used to verify each other’s identity. It should be a word or phrase that only a small group of people know and isn’t discoverable online. “Ultimately, if you suspect that something might not be right, it is much better to have your mum or your brother or your friend laugh at you for thinking that they’re a robot,” Ajder said, “than it is to potentially be running to an ATM.” By Clare Duffy