Is AI smart enough to accurately measure an employee’s value?


Artificial intelligence (AI) and machine learning are supposed to help enterprises become more efficient by streamlining processes and taking over tasks currently performed by those unfocused, under-motivated humans known as employees.

For those enterprise workers who don’t lose their jobs to automation and machine learning, smart technologies can be used collaboratively by employees to make themselves more productive and effective. At least that’s the theory, as reflected in comments by a couple of prominent CEOs appearing in a “future of work” panel at the recent World Economic Forum (WEF) in Davos, Switzerland.

Ulrich Speisshofer, chief executive of ABB Group, a Switzerland-based power and automation technology company: “It’s not about technology replacing people, it’s about technology augmenting people and creating wealth and prosperity.”

Bill McDermott, chief executive of Germany-based software giant SAP: “We should be optimistic. We see augmented humanity as the opportunity. It’s there to enrich our lives, not take anything away from us.”

At the risk of fomenting class war, I would argue that CEOs of giant corporations have more reason to be optimistic about “augmented humanity” — or, really, anything — than the rank and file, many of whom not only won’t be sharing in any created “wealth and prosperity,” but will have something taken away from them — their jobs.

Indeed, Mark Weinberger, chief executive of London-based professional services firm EY, alludes to this: “I do agree that in the long-term everything’s going to be great” (more of that irrepressible CEO optimism!) . . . “but there’s a lot of disruption that’s going to happen as we get from point A to point B.”

Disruption means job losses, and in some cases, the extinction of certain jobs and even certain industries. To be fair, these CEOs simply are acknowledging an unstoppable trend and viewing it favorably from 10,000 feet high. And, realistically, anybody who wants a job in the future economy had best understand the dramatic changes in the workplace.

There’s plenty of advice out there for workers who want to flourish (or even just survive) in the face of automation, machine learning and robots, most of which falls along the lines of “be more creative,” “develop emotional intelligence” and “build a personal brand.”

The question, though, is whether creativity, emotional intelligence and other “soft skills” can be measured and assessed an accurate “value.” And that’s a genuine concern, based on results of a recent global survey of more than 800 enterprise decision makers on the impact of AI and automation in the workplace by Massachusetts-based Pegasystems, a vendor of customer engagement and business process software. Among the survey’s findings:

  • Two-thirds (66%) of respondents “believe the widespread use of AI will give rise to a more transparent meritocracy in the workplace.”
  • Nearly three-quarters (74%) predict that “within 10 years, AI will become standard practice for evaluating employee performance.”
  • 84% agree it “will be commonplace for AI to calculate the true value added by each worker within a decade,” while 44% say this could happen within five years.

Can AI measure “emotional intelligence”? Can AI recognize and assess the value of creativity? Can it measure the ability to inspire and motivate colleagues, or to defuse a hot-headed CEO before he or she makes another ill-advised decision?

I don’t know that it can. That’s why it’s important to enterprises and employees that decision makers use AI measurements of employee performance to augment their own judgment and experience. After all, “augmented humanity” — to use SAP CEO McDermott’s term — should include “augmented leadership.” In fact, any enterprise decision makers who think it’s a good idea to make cold-blooded decisions based on AI-derived performance metrics might be good candidates themselves to be replaced by a machine.


  1. I agree with your all points.
    Artificial intelligence (AI) and machine learning are used to help enterprises become more efficient by streamlining processes And it helps in to find better candidates.
    Thanks for sharing this nice article.

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