WHY THIS MATTERS IN BRIEF
If you can use AI to get your under performing staff to be as good as your expert staff then why would you need to pay more to retain your experts?
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Everyone’s talking about how Artificial Intelligence (AI) is going to revolutionize how we work, but a new study suggests it might do the same for how companies pay their workers. Researchers at Stanford University and the MIT tested the impact of Generative AI — an algorithm that can create text based on prompts, like ChatGPT — at a Fortune 500 software company among 5,000 customer service agents. They trained the tool using previous chats with clients, teaching it things like the best language to pacify customers and what technical documentation to use in different situations.
Turns out, access to AI does make a difference: the company’s lowest-skilled workers became 35% faster with the tool. The researchers think this was because the AI essentially transferred top performers’ knowledge to less-experienced colleagues through the automatically-generated recommended responses.
The Impact of AI on Employability, Opportunity, and Pay, by Keynote Matthew Griffin
Meanwhile, the highest-skilled employees didn’t get much out of the tool, probably because their responses were already top-notch. But as their colleagues got better, they stopped standing out.
This all means that a time may be coming when companies need to compensate star employees for their input to AI tools rather than their just their output, which may not ultimately look much different from their AI-assisted colleagues.
“It wouldn’t be far-fetched for them to put even more of a premium on those people because now that kind of skill gets amplified and multiplied throughout the organization,” said Erik Brynjolfsson, a Stanford professor and one of the study’s authors. “Now that top worker could change the whole organization.”
Of course, there’s a risk that companies won’t heed that advice. If AI levels performance, some executives, myself included, say that this may flatten the pay scale accordingly. Businesses would then potentially save on costs — but they would also risk losing their top performers, who wouldn’t be properly compensated for the true value of their contributions under this system.
Ben Granger, chief workplace psychologist at survey firm Qualtrics, said the time is now for organizations to start thinking about the pay implications of AI, like what it means to put a market price on the so-called knowledge transfer from their best and brightest.
“We would have to find better ways to measure the total impact of the highest performers — just looking at their individual-level performance could disguise the massive impact that they have in influencing best practices that get shared through AI,” Granger said. “This has major implications for performance management systems — your most valuable employees might not always be the ones hitting the best numbers and could get missed and under compensated.”
