The Financial Times recently reported an interview with Rebecca Hinds, head of the Work AI Institute. Hinds was discussing a new survey of 6,000 digital workers, which included the following arresting statistic: although respondents claimed that AI saved them 11 hours a week on average, only 13% reported any improvement in company performance.
Hinds offers three explanations for this paradoxical result:
- When calculating the 11 hours saved, workers aren’t counting all of the time they spend waiting for AI agents to complete tasks (an activity some are now calling “botsitting”).
- The workers often ignore the cost of toggling between multiple AI tools as they attempt to get a usable response (60% of the sample reported running queries across several tools in search of better outputs).
- Workers may also be participating in what Hinds calls “workplace theater,” in which they are “visibly performing work for bosses and colleagues, rather than focusing on the actual grind of getting things done.”
These findings are probably not what companies like OpenAI and Anthropic want to hear just months before their planned IPOs. But what interests me here is not the shortcomings of AI technology.
What caught my attention about this interview is that essentially all of these issues are discussed in my book Slow Productivity, which came out in early 2024, and doesn’t mention AI at all. An earlier generation of digital tools – like email, Slack, video conferencing, and mobile computing – also led workers to vastly underestimate the time wasted wrangling diverse devices, applications, and rapidly toggling back and forth between different tasks and channels. Workplace theater isn’t new either (in my book, I called it “pseudo-productivity”).
In this way, AI isn’t so much creating new problems as it is magnifying the types of problems that have long existed. Here I find a potential silver lining. This technology is sufficiently new and exciting that business leaders are paying more attention to its impacts. In seeking to understand how to make AI effective in the workplace, they might finally recognize what has long been broken.
