Managers’ increasing use of artificial intelligence for core responsibilities traditionally performed by humans may be hindering employee development, according to a Tuesday report from Highwire, a performance conditioning coaching program by Knopman Marks, which provides exam training for global investment firms.
Nearly 8 in 10 (78%) of the more than 300 U.S. people managers surveyed in August said they have used AI tools in the past 12 months to handle employee feedback or a performance review, Highwire found. Yet, while 54% of employees found AI-generated feedback more specific and actionable, about a third said it’s become more generic (34%) or less useful (32%).
Additionally, only 16% of the more than 700 individual contributors surveyed said they were told AI played a role in their most recent review.
This has ramifications, the survey found. Although most professionals believe making mistakes is critical to learning new skills, more than half of employees feel they can’t make a mistake without it being held against them. As a result, two-thirds said that to protect themselves, they change their behavior — such as by avoiding a reasonable risk (27%) or a challenging responsibility (23%), delaying asking for help (27%), holding back an idea (21%) or hiding or downplaying a mistake (16%).
“When employees suspect a tool shaped their review, and no one has told them how, playing it safe starts to feel like the smartest move,” Liza Streiff, co-founder and CEO of Highwire and CEO of Knopman Marks, explained to HR Dive.
The difference in views on AI-powered feedback comes down to how involved a manager remains in the process, Streiff continued. “So HR can really help by making sure managers are open about how AI was used, and that the time it saves goes back into the conversation itself,” she added.
Recent studies confirm that AI tools have limitations, and employee development requires human involvement in fundamental, people-oriented actions like employee evaluations.
“AI can help you write a faster review, but it doesn’t replace human judgment, context, nuance and empathy,” Streiff stated in a media release.
AI tools aren’t conditioned to know their workers, Streiff said to HR Dive. The tool’s “knowledge is an amalgamation of millions of other people, essentially the textbook version of what feedback should sound like. [It doesn’t] know how someone has grown over the year, and that context is the whole point of a review,” Streiff said.
For example, “a good manager can tell the difference between a smart risk that didn’t pay off and a careless mistake, but that takes context, and context is exactly what AI doesn’t have,” Streiff pointed out.
When it comes to accurately interpreting how employees experience work, AI models are adept at navigating themes requiring clear answers, but much less effective at deciphering “incomplete, emotional or context-dependent signals,” according to a July study from PYX Labs, a research arm of Perceptyx.
Research released earlier this year by Radical Candor highlighted another issue. In a survey of 600 employees across the U.S., 73% of respondents said they reported inaccuracies in AI-assisted work, but half also noted that managers rarely or only sometimes act on their reports.
One reason may be untrained managers, who tend to punish employees for the criticism instead of rewarding their candor, according to Radical Candor’s co-founder. Recent findings from the American Management Association that two-thirds of professionals say they’re not getting frequent support from managers may back this up.
“Developing people will always require people,” Streiff said. “We have to make sure we’re not replacing the human development employees actually need with the version that’s just easier to reach for.”
