These are the skills employers are looking for as AI use expands, according to leaders at Davos

  • As generative AI transforms business operations, certain skills will become increasingly valuable.

  • Leaders at the World Economic Forum in Davos highlighted skills they think will be important.

  • These include having a learning mindset, knowing how to optimize data, and knowing AI's limits.

Since the release of ChatGPT just over a year ago, it's become increasingly clear that the world will have to adapt as the influence of generative AI grows.

And that's been borne out at this year's World Economic Forum in Davos, where AI has been a key topic.

While many companies are already embracing the technology, with experts and executives alike saying AI is likely to transform how many businesses operate entirely over the next few years, they are also trying to ensure workers have the right expertise for the future.

Business Insider spoke to industry leaders from companies including McKinsey, KPMG, IBM, and Coursera about the skills they believe will be important in the era of generative AI. Here's what they had to say:

Have a learning mindset, and don't be afraid to experiment.

Katy George, senior partner and chief people officer at McKinsey, said that the company would be looking for people who aren't just capable when it comes to generative AI but are innovative, flexible, and able to evolve quickly.

"They need to be the early adopters," George said, who "are innovating and make the best use of it."

In terms of digital competency, George said a big factor is curiosity.

"It's about the mindset of trying new things," she said. "And kind of adopting and experimenting. It's a learning mindset — learning agility."

Know how to optimize data for generative AI.

Paul Knopp, CEO of KPMG US, pointed out that a big part of using AI effectively is ensuring the technology's underlying information is sufficiently well-prepared.

"How do I get my data prepared and ready to apply generative AI to," Knopp said, "so that I can be more successful selling products or services to my customers, or be more successful in making my internal business processes more efficient so that I have more capacity to invest in other ways or have more profitability?"

That data element "is one that I think most entities are still trying to figure out, or trying to optimize," he commented.

While such data skills have always been valuable, they will become more crucial as a base for AI use.

"Being able to look at data, evaluate data, cleanse data, anonymize data — all that — is going to be even more important than historically it's been," Knopp said. "Those data skills have taken on a new premium in terms of where you might be valuable in the market."

Use AI to augment your job, not just automate it.

AI can help workers do their jobs more efficiently, yes. And that's led some to fear that the technology is coming for their roles. However, many say that effectively using AI in the workplace can free up time for workers to focus on adding real value — instead of doing mundane tasks.

"A lot of the things that the technology is really good at are the kinds of things that people don't like to do," says Jeff Maggioncalda, CEO of Coursera.

"Figure out how these tools might help you enjoy your job more, be more productive," Maggioncalda said. That can free up time to "push into new frontiers that you haven't been in before that ideally will stretch you, will grow you, will create more opportunities."

Know the limits of AI — and the importance of human knowledge.

While it will be important to understand how AI works and how to use it, it will be equally important that employees apply a human element and human values and recognize the technology's limits.

AI users are "going to need to understand what are the constraints, if you will, and what the risks are and how do you ensure that you use this responsibly in order to get the right outcome," John Granger, senior vice president of IBM Consulting, said.

Employees will need to understand what potential problems to look out for and know how to avoid bias and discrimination in AI outcomes, according to both Granger and Maggioncalda.

Companies should be aware of "the ethical considerations, the risks, and the inaccuracies," Maggioncalda said, and to "be sensitive to what the potential downsides are."

It's still important to bring a fundamental human element to whatever work AI is being applied to, Granger said.

"How does this technology help me to reinforce the values that I think are important?"

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