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Gen AI skills are in short supply. Is your organization prepared?

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ESSENTIALS FOR LEADERS AND THOSE THEY LEAD

Brought to you by Liz Hilton Segel, chief client officer and managing partner, global industry practices, & Homayoun Hatami, managing partner, global client capabilities

Generative AI (gen AI) has caught the public’s fancy, but not everyone may be comfortable using the technology in the workplace. Research shows that many employees believe they lack the skills to use gen AI safely and effectively—and expect their organizations to provide those skills. While initiatives to reskill and upskill workers have been on the corporate agenda for years, the advent of gen AI brings a new urgency to these efforts. Organizations may need to consider revving up their skill-building programs as both employers and employees learn to adapt to this powerful new technology.

AN IDEA

An image linking to the web page “The organization of the future: Enabled by gen AI, driven by people” on McKinsey.com.

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While gen AI may not necessarily eliminate human jobs, it will make them different. “Gen AI applications will have unprecedented effects on organizations’ approaches to talent management,” observe McKinsey’s Sandra Durth, Bryan Hancock, Dana Maor, and Alex Sukharevsky in an article on how business leaders need to prepare their organizations for a gen AI-driven future. For example, deploying gen AI to take over a task could diminish the mentorship and learning opportunities that were previously inherent in that task. Leaders may need to be exceptionally hands-on when it comes to training employees—and themselves—on using gen AI in day-to-day work. “It’s not a one-and-done process,” caution the McKinsey experts. “Leaders will need to continually assess how and when tasks are performed, who is performing them, how long tasks typically take, and how critical different tasks are.”

A BIG NUMBER

That’s the percentage of respondents to a McKinsey survey who said their organizations had skill gaps or expected to face them in the next five years—before gen AI burst onto the scene. With gen AI, automation will likely take over tasks accounting for 30 percent of the hours worked in the US economy by 2030, up from 21.5 percent without it. Our respondents expect data analytics and mathematical skills—critical to working with smart technologies—to be in particularly short supply over the next few years. Many organizations are tackling this challenge through hiring and employee skill building, the two most common tactics to match skills to needs.

A QUOTE

“The underpinnings of generative AI systems are appreciably more complex than most traditional AI systems.”

That’s from a new McKinsey article on seizing opportunities in the gen AI value chain. The time, cost, and in-house skills required to deploy gen AI technology for large-scale value creation may be challenging for new entrants and small companies. For example, developing foundation models—the heart of gen AI—requires deep expertise. But fine-tuning an existing model “requires less data, costs less, and can be completed in days, putting it within reach of many companies,” note the article’s authors. “Companies that use specialized or proprietary data to fine-tune applications can achieve a significant competitive advantage over those that don’t.”

A SPOTLIGHT INTERVIEW

An image linking to the web page “Generative AI: How will it affect future jobs and workflows?” on McKinsey.com.

Partnerships between the federal government and educational institutions may be an effective way to build workforce skills for gen AI roles, suggests McKinsey senior partner Kweilin Ellingrud in an episode of The McKinsey Podcast. With an estimated 12 million occupational transitions potentially taking place between now and 2030—especially in lower-wage jobs—workers will need “a lot of reskilling, upskilling, and support” to adapt, she says. McKinsey partner Saurabh Sanghvi adds that “there’s a huge role that employers can play in this.” In addition to hiring for skills rather than degrees, organizations could view occupational shifts as “a real opportunity to think about pipelines and pathways,” he says. “Everybody is learning about these new technologies. Everybody needs to upskill. Companies can really think about opportunities to hire from within instead of externally for an open role.”

IT’S NO JOKE

Gen AI can do many things, but good judgment may still be a people thing. Despite their entertainment value, gen AI’s quirks and inaccuracies may not be amusing in “real” work output. For example, a newspaper’s chatbot-written sports articles and another news outlet’s AI-generated stories have sparked outrage on social media. “The accuracy and reliability of AI-generated content will only be as good as the data sets that are used to train the gen AI algorithms,” notes McKinsey’s Michael Korn, suggesting that leaders set up knowledge management programs “for ensuring that the curated data sets upon which gen AI functionality is built are up to date and relevant.”

Lead skillfully.

— Edited by Rama Ramaswami, senior editor, New York

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by "McKinsey Leading Off" <publishing@email.mckinsey.com> - 01:06 - 2 Oct 2023

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“The underpinnings of generative AI systems are appreciably more complex than most traditional AI systems.”

Out now: New issue of McKinsey Quarterly