How leaders can use AI to create new opportunities, not kill jobs

The threat of automation on labor is nothing new. Humans have a long history of new technologies that disrupt our workflows by automating tasks, from the printing press in 1439 to public access to the internet in 1993. Today, we have available an intelligent technology that can bring down both the costs of labor and the threats of irrational (human) work behavior that deviates from streamlined operational processes. This time, the threat of automation is significantly different because the self-learning abilities of AI allow it to imitate and sometimes even overshadow humans’ cognitive abilities….

For many of my executive students, the advancements in the field of AI are mind-blowing and seem to make it difficult for them to come up with arguments on why they should be careful when adopting this tool. Their focus is entirely on the financial benefits that AI brings with it, ignoring the importance—and in the long term, maybe even the existence—of their own humanity. They often remark that, given the potential of AI to create value for businesses and to contribute more to economic growth than any other worker could do, they, as business leaders, have no choice but to pursue automation strategies single-mindedly. From a short-term perspective, this reasoning seems to make sense. Indeed, companies seeing automation as a priority will report some performance gains. But the crux of this story is that the contribution of automation to the business growth of the organization will eventually slow down and sometimes even work against them. Automation only is at best a short-term solution that in the long term will stall your organization….

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The reality of automation strategies is that people’s jobs get fragmented…. Because of job fragmentation, employees easily fall into lower-paid jobs. In part, this development stems from the well-explored phenomenon of job polarization. Because of the inherent limitations in developing and deploying AI, it is typically too expensive and difficult to automate low-wage manual work (e.g., it is often cheaper and more efficient to hire a cleaner than it is to deploy a cleaning robot). On the other hand, it is too expensive and difficult to automate high-paid creative and strategic work. This leaves a middle segment of jobs—routine administrative, bureaucratic office work—as the main target for automation. And when such workers are displaced, they cannot immediately upskill to take on higher-paid work. As a result, they end up falling to low-wage and low-status work, positions that further exacerbate inequality. …

So, as an AI-savvy leader, you need to be acutely aware that AI efforts focusing only on automation will quickly bring ethical and fairness risks. Your automation efforts can exacerbate job polarization and increase socioeconomic inequality, which can beget unrest, instability, and other volatility, even violence. In turn, these responses to inequality will threaten your organization, which has become less human and therefore less capable of adjusting to volatility.

The way you can combat the negative consequences of too much automation is through long-term investments in building out the human functions in your organization.

Committing to augmentation requires serious investments, as the new jobs will need to have enriched job content and added cognitive responsibilities for employees to learn and grow to become a better version of themselves. In these new jobs, where AI and humans will work together, your employees will need to acquire the necessary skills to help them get used to having a smart machine as a coworker.

What you want most is for your employees to get better at one key ability that humans develop early on in life and that companies benefit the most from: creativity.

In the creative process, the human identifies a problem, which will serve as input to the generation process that is driven by AI, and the generated output is then interpreted, corrected, and employed by the human. A human is thus needed to start and finish the creativity process, whereas AI drives the generation process involving the hard labor of bringing all information together. To take the best advantage of AI, you need to avoid buying into automation as your priority and instead focus on real augmentation. To achieve that outcome, you need to make the following two important decisions.

Push down the tech investment and push up the job enrichment investment in your AI budget: At a lunch meeting to catch up with the CEO of a company that I worked with, he told me that although he was not a tech expert, he felt that something was wrong with the company’s recent AI adoption project. How so? I asked. “Well,” he said, “I see all these fancy algorithms being developed and implemented, but when looking at the numbers, I don’t see much improvement in how our teams perform.”

I asked how much of the budget was still available after investments in the tech were made. He could, I suggested, use that part of the budget to fund training sessions for the new jobs that he was probably creating. He looked at me with a somewhat guilty face and said, “What new jobs exactly are you referring to? And no, most of our budget is already spent.”

It’s a typical response that I have heard when discussing companies’ AI adoption projects. As many change consultants will tell you, when organizations start their AI adoption project, they usually spend up to 90 percent of their budget on the technology itself. The consequence is that little money is left to put AI to work in collaboration with the workforce.

This outcome is both regretful and counterproductive. It will undermine the likelihood of your AI adoption project’s success. If, by now, you have gained good business insight on AI, you know that it’s your obligation to invest more—more time, more money—in creating better, more-human-focused jobs for your workers, both because it’s the right thing to do and because the long-term costs of not doing it are significant. The most successful companies are those that invest heavily in their people when the AI adoption project starts.

Reprinted by permission of Harvard Business Review Press. Excerpted from The AI-Savvy Leader: 9 Ways to Take Back Control and Make AI Work by David De Cremer. ©2024 Harvard Business School Publishing Corporation. All rights reserved.

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