The human side of generative AI: Creating a path to productivity


Ever since OpenAI’s ChatGPT exploded into public view in late 2022, the possibilities of generative AI (gen AI) have captured imaginations throughout the business world.

When it comes to crafting an effective talent strategy, organizations have focused mostly on how gen AI can increase productivity levels. This is understandable, given the trillions in value at stake. However, it may not be the most strategic approach. To match the right talent to jobs, leaders first must understand how gen AI is changing the way employees view their work experience.

McKinsey recently surveyed a cross-section of employees as part of our continuing research into how organizations can improve workforce engagement, retention, and attraction (see sidebar, “About the research”). Respondents provided several intriguing insights that can help organizations as they build gen AI talent capabilities.

  • In any given organization, the pool of gen AI talent is likely broader than many leaders realize—and it’s poised to grow rapidly. This cohort isn’t limited to technical talent such as data scientists, software engineers, and machine learning specialists, important as those roles are. In fact, just 12 percent of our respondents fall into this tech-heavy category of traditional gen AI talent. The vast remainder of respondents, or 88 percent, are in nontechnical jobs that use gen AI for help with rote tasks. These jobs include middle managers, healthcare workers, educators, and administrators, among others (Exhibit 1).
  • Fifty-one percent of respondents in technical and nontechnical roles who identify as gen AI creators and heavy users of the technology say they plan to quit their jobs over the next three to six months. This is sobering news for those executive respondents in the survey who say they want to build gen AI talent in-house; it’s hard to reskill and upskill people when they are looking to leave.
  • Although those who self-identify as heavy users and creators of gen AI represent an in-demand employee group, these workers aren’t staying in jobs or attracted to them because of compensation. In fact, the survey shows that this group strongly emphasizes flexibility and relational factors such as meaningful work, caring leaders, and health and well-being over pay.
  • Finally, and perhaps most surprising: heavy users and creators of gen AI overwhelmingly feel they need higher-level cognitive and social-emotional skills to do their jobs, more than they need to build technological skills. As workers increasingly use gen AI to tackle more repetitive tasks, the human-centric skills of critical thinking and decision making will become ever more important.

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These revelations have broad implications for employers as they try to attract and engage their workforces. Organizations are on the cusp of gen AI pushing either positive or negative change when it comes to the nature of work. Leaders have an opportunity to humanize that work by deciding where, when, and how their teams use gen AI so that people are freed up from routine tasks to do more creative, collaborative, and innovative thinking. Gen AI talent agrees.

In this article, we break down crucial segments of workers who are at the forefront of gen AI usage or creation and dig deeper into the job factors and skills they say they need. We then discuss how organizations can enhance productivity by crafting jobs that put people before tech—not the other way around. Companies that set a people-centric talent strategy will give themselves a competitive edge as more workers and jobs are affected by the changes gen AI brings.

The workforce: Who is in the gen AI mix?

If companies are to take advantage of the productivity gains from gen AI, they first must consider the broad range of skills required for its successful deployment across the enterprise.

While there are many categories of workers who can be described as gen AI talent, we focus on four distinct archetypes in our survey based on gen AI use:

Creators: These employees help build the gen AI models for their organizations and develop the tools and interfaces most of us use to interact with these models. Creators (2 percent of employees surveyed) tend to be predominantly software engineers, programmers, and machine learning scientists who develop the tools and interfaces most of us use to interact with gen AI.

Heavy users: These employees use gen AI to help them perform most of their core tasks or to enhance their work functions. Heavy users (8 percent of our sample) include a wide range of workers, from designers who use gen AI to expedite 3D modeling to data scientists who use gen AI to verify the accuracy of their coding language semantics.

Light users: Workers in this category use gen AI to perform less than 50 percent of their primary tasks. Representing about 18 percent of the sample, they include middle managers, educators, and communications professionals. For example, a manager might use gen AI to create meeting notes or to help delegate tasks, while a teacher may use it to innovate classroom activities. Journalists and writers researching topics might use gen AI to give them a baseline of facts or to help write a first draft.

Nonusers: These are individuals who are either unaffected by or unaware of the impact of gen AI on their jobs. Examples in our sample include nurse practitioners and healthcare workers engaged in direct patient care, as well as retail associates whose primary role is face-to-face interactions with customers. Although these employees currently represent about 70 percent of the survey, our expectation is that a majority of nonusers will become light or heavy users as the scope and usage of gen AI changes.

People over pay: The job factors that workers value most

The COVID-19 pandemic revealed that for many workers, what they want most from their work experience has fundamentally changed. Employees increasingly value relational elements such as caring leaders and coworkers, as well as support for health and well-being, more than compensation (though pay is always important). In 2021, we saw workers quitting in droves—in fact, 40 percent of respondents across jobs, industries, and geographies said they planned to quit their jobs in the next three to six months. That figure has since dropped to 34 percent.

Certain worker segments, however, remain a greater flight risk. Of self-identified gen AI creators and heavy users, 51 percent of respondents to our latest survey say they plan to leave in the next three to six months.

Early creators and heavy adopters, in particular, wield power when it comes to job choice and shaping their careers. Many company leaders believe that workers in these groups are leaving at higher rates because they can find better compensation elsewhere. Yet an examination of the employee-value-proposition (EVP) factors that resonate most with these segments busts the myth, once again, that compensation is a primary motivator.

Our survey shows that creators and heavy users prioritize workplace flexibility more than total compensation, and that they are seeking a sense of belonging, care, and reliability within their work community. They stay in their jobs when they are given flexibility, and they leave when they aren’t. The other factors that make them stay are meaningful work, support for health and well-being, reliable and supportive coworkers, and a saf

Fuente: PMideas (The human side of generative AI: Creating a path to productivity).