At Microsoft, which rolled out AI widely internally, executive vice-president Ryan Roslansky recently publicly<\/a> lamented the prevalence of AI slop in his day-to-day work. After receiving \u201cwhat was clearly an AI-generated doc\u201d from a co-worker, he used his AI to summarize it and came away with no new thinking about the idea, he said. He warned his followers against falling into this potential \u201cdoom loop\u201d, where AI does the reading and writing and leaves behind an \u201cocean of sameness\u201d.<\/p>\n Meanwhile, Walmart store and warehouse employees are being plagued by unreasonable expectations, errors and false alerts from AI tools that assign tasks, schedules and monitor performance, Business Insider reported<\/a>.<\/p>\n Employers are navigating a flood of errors and low-quality work that are sapping employee time, raising privacy and security risks and pushing up costs. Now, some businesses that started off fast and furious on AI are pumping the brakes, implementing restrictions where experimentation was once encouraged, bringing back experienced workers and upping training efforts.<\/p>\n C-suite leaders say when it comes to AI, there\u2019s a sense that \u201cwe\u2019re driving the truck and building it at the same time, and that\u2019s a problem,\u201d said Johnny C Taylor Jr, president and CEO of the Society for Human Resource Management. \u201cIf we could all rewind \u2026 we would have introduced [this] in a more thoughtful, slow way.\u201d<\/p>\n Despite billions of dollars that firms around the globe have invested in AI over the past few years, major returns remain to be seen: 90% of executives say AI efforts have yet to translate to productivity gains at their companies, according to an Atlanta Federal Reserve working paper<\/a>. And an Ernst & Young survey<\/a> published last month found that 36% of senior AI executives at companies with at least $1bn in annual revenue reported an AI incident that led to issues including data loss, financial damage, brand damage or operational disruptions.<\/p>\n Firms from Microsoft to McKinsey are limiting usage for employees, as the flood of new tools and rapacious consumption weighs on bottom lines. Others, such as Palantir, Booz Allen Hamilton and Nvidia, are restricting employee use over growing concerns about the security of their organizations\u2019 data with AI companies, Reuters <\/a>reported.<\/p>\n Microsoft and Walmart declined to comment. Meta, Palantir, Nvidia and Booz Allen Hamilton did not respond to requests for comment.<\/p>\n \u201cWe initially treated AI like a traditional technology rollout: deploy the tools, provide training, drive adoption,\u201d Kathleen Hogan, Microsoft\u2019s chief strategy and transformation officer, said in a recent blogpost<\/a> about the company\u2019s AI adoption journey. \u201cWe learned that access and usage do not equal transformation.\u201d<\/p>\n Expertise gaps and errors<\/p>\n AI remains a mixed bag for managers and employees alike: more than half of employees said they \u201caren\u2019t getting the AI training they need\u201d, while most managers said they were outskilled in AI by their staff, according to an Indeed survey<\/a> published in July. Just 45% of managers said they felt \u201cequipped to effectively lead AI natives\u201d.<\/p>\n Many workers feel \u201clike they\u2019re being asked to make use of these tools without any guidance about how they best could be deployed\u201d, said Zack Mabel, director of research at the Georgetown University Center on Education and the Workforce. Meanwhile, managers are balancing orders to \u201croll this out, find productivity gains and don\u2019t compromise on quality\u201d, he added.<\/p>\n Companies are trying to address these perceived gaps by moving away from one-off webinars for broad swaths of staff and toward \u201csustained, role-specific training\u201d, Taylor said.<\/p>\n Microsoft found that \u201cadding agents to a broken process still leaves a broken process\u201d and \u201cspeeding up one step just creates a longer queue at the next\u201d, Hogan\u2019s blogpost reads. The company found that focusing on employee training, particularly pairing up early-career engineers with more seasoned employees, boosted productivity.<\/p>\n One barrier to bigger AI-induced gains is the technology\u2019s tendency to produce \u201cplausible-looking output\u201d with weaknesses or mistakes that are not immediately apparent, explained Jessica Reif, assistant professor of management at the Wharton School of the University of Pennsylvania.<\/p>\n \u201cThis makes it more likely that an error propagates through a workflow instead of being immediately corrected,\u201d which can cause problems to snowball, said Reif.<\/p>\n Meanwhile, AI\u2019s limited ability to assess human workers is still limited, which is creating tension at some companies. At Walmart<\/a>, frustration is mounting among some rank-and-file store employees over inconsistent and inaccurate AI tools, Business Insider reported.<\/p>\n Employees described bots that set unreasonable standards for human workers while introducing a host of their own inefficiencies and errors. AI tools plotted nonsensical routes for fulfilment workers that made it harder to fill orders quickly, pumped out useless safety alerts and set unrealistic schedules that left store employees cutting corners to keep up.<\/p>\n These bots assume that workers are \u201cgoing to be perfect every single time\u201d, one manager told Business Insider. \u201cWe\u2019re not going to hold people to these impossible standards.\u201d<\/p>\n Walmart declined to comment.<\/p>\n Rising risks<\/p>\n Neil Elan, attorney at Stubbs Alderton & Markiles LLP, said he had observed \u201ca growing gap\u201d between how his corporate clients think AI is being used and how it is actually being used, which is creating issues with confidentiality, intellectual property, efficiency and employee conduct.<\/p>\n It\u2019s also creating headaches for companies when workers\u2019 use of ChatGPT<\/a> spills into public view.<\/p>\n skip past newsletter promotion<\/a><\/p>\n Sign up to TechScape<\/p>\n A weekly dive in to how technology is shaping our lives<\/p>\n after newsletter promotion<\/p>\n The night before Will Moye was set to face 3M in court over a 2020 gas explosion at a Houston manufacturing plant that killed three and damaged hundreds of homes and businesses, the attorney received a report from the company\u2019s independent expert witness.<\/p>\n Skimming on his iPad, Moye noticed telltale signs of AI: strange formatting and fonts and time stamps showing that 14,500 pages were assembled in a matter of hours. Moye suspected that the author, Josh Autenrieth of Knighthawk Engineering, lacked expertise and had relied on ChatGPT, despite billing 3M $90,000 for a report arguing the company was not liable.<\/p>\n Autenrieth\u2019s chat logs, which Moye requested and shared in court, show he prompted ChatGPT, \u201cWhat am I looking at?\u201d after uploading a picture of the gas detector at the heart of the case.<\/p>\n The jury found that 3M had failed to properly inspect the gas detection system and ordered the company to pay $61.5m to 24 homeowners. Moye said after the verdict, the jury \u201cexpressed a profound disbelief\u201d that the company would hire an expert who would make claims \u201cwithout any foundation\u201d.<\/p>\n \u201c[3M] were trying to reset the narrative,\u201d Moye said. \u201cAnd they hired an expert who\u2019d never touched the machine.\u201d<\/p>\n A 3M spokesperson said that \u201cafter independently reviewing the facts and reaching his own conclusions\u201d, Autenrieth \u201cused AI as a tool in preparing his report\u201d.<\/p>\n Autenrieth\u2019s legal counsel Janina Wojtkowski said ChatGPT didn\u2019t produce his opinions or replace his \u201cprofessional judgment\u201d but assisted in formatting, structuring and drafting amid \u201csevere deadline constraints\u201d.<\/p>\n Performance boost? Not so much<\/p>\n As companies and workers muddle through the unknowns of early AI adoption, costs are still coming into focus, while broad productivity gains remain elusive.<\/p>\n In a study published in May<\/a>, University of Pittsburgh researchers concluded that productivity didn\u2019t rise after companies invested in AI and cut staff. Although executives have been overwhelmingly optimistic about AI\u2019s potential impacts for years, \u201cmanagement optimism does not effectively translate into \u2026 better performance,\u201d the paper states.<\/p>\n More than 112,000 job cut announcements in the US so far in 2026 have mentioned AI, making it a top reason for layoffs, according to Challenger, Gray & Christmas.<\/p>\n Earlier this year, Meta paused its practice of tracking employees\u2019 computer activity to train its AI, according to Reuters<\/a>. Meta also recently told employees that their adoption and usage of AI tools would no longer be part of performance reviews, the Information reported.<\/a><\/p>\n Meta did not respond to a request for comment.<\/p>\n Mark Ma, University of Pittsburgh professor and researcher on the AI layoff study, said leaders are focused on short-term performance, \u201cwhich is why they tried to rush ahead by investing in AI and laying off workers\u201d.<\/p>\n![\"\"](\"https:\/\/www.newsbeep.com\/uk\/wp-content\/uploads\/2026\/10\/1791920175_242_500.jpg\")
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