AI and tech overload is making workers less productive, Quickbase study reveals
As I wrote this newsletter in a Google Doc, I found myself toggling between an overwhelming mix of programs with different functions: Slack, Asana, my company’s HR management software, various spreadsheets, and my Microsoft OneDrive—not to mention the AI applications ChatGPT and Perplexity. I started to wonder: Am I the only one feeling tech fatigue?
Apparently not. In a new study, software company Quickbase found that while 80% of companies are investing more in new tech to improve productivity, more than half of the 2,000 workers surveyed across 10 industries are finding it harder than ever to be productive. The reason? Too many new tools with little connection or compatibility between them—and, it seems, a lack of clarity from up top.
This is not the revolution in worker productivity that AI companies have been promising. Indeed, nearly 60% of workers surveyed said they spend 11 hours or more each week chasing down information that is located in a handful of disconnected technology solutions. That’s more than a quarter of a standard work week! And 90% reported just feeling plain overwhelmed by the number of tech programs they needed to get work done on a typical day. I certainly feel validated.
The study calls this phenomenon “gray work,” which it defines as the work done in ad-hoc situations when technology isn’t connected properly. It’s “the hidden cost of inefficiency—the manual tasks employees do to compensate for disconnected systems and rigid tools,” the report explains. Those in the financial services/insurance and professional services industries felt it the most, reporting the largest increases in this kind of work this year.
It may be costing business leaders more than they realize. In addition to wasting time, half of the workers surveyed said they’d experienced project delays, miscommunication, duplicate work, or budget overruns in the past year. Some 53% said they spend just half their week on meaningful work that drives results for key projects.
So how can companies solve this? After diagnosing where the friction is occurring, business leaders should do a full tech stack audit, cutting redundant tech and prioritizing programs that offer interoperability, the report advises. Then, decide who’s in charge of overseeing and simplifying tech systems and create a plan. Only deploy AI in areas where it offers clear advantages—and make sure employees understand how they can (and how they should not) use it.
Kristin Stoller
Editorial Director, Fortune Live Media
kristin.stoller@fortune.com
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