It’s rapidly becoming a key question for tech professionals everywhere: will the rise of generative A.I. result in more jobs… or far fewer?

Pundits and analysts have suggested a handful of possible futures. Some think companies will reduce their human staffs and trust more workday functions, such as generating code and customer service, to generative A.I. But others believe A.I. will only enhance existing jobs—and we won’t see many cutbacks, if any.

Upwork recently surveyed 1,400 U.S. business leaders, from senior managers to C-suite executives, and found that nearly half (49 percent) plan on hiring more full-time staff and freelancers as a result of generative A.I. However, while C-suite honchos seem to have overwhelmingly embraced the possibilities of generative A.I. (with 73 percent saying their organizations are actively using it), lower-level executives seem a bit more reluctant, with only 53 percent of senior managers saying they’re embracing the technology.

What’s making those managers leery about A.I.? “Early signals from our open-ended survey questions suggest that concerns regarding early adoption and potential risks associated with generative A.I. are paramount,” read Upwork’s note accompanying the data. “Other respondents were skeptical and unsure of the ROI their organization would gain from these new tools.” 

No matter what the executive enthusiasm for the tech, fears of job loss still persist. Companies debating whether to adopt A.I. should come up with a communication strategy that clearly explains future plans, Upwork suggested: “This strategy should include communicating the expected outcomes for their workforce in relation to generative A.I. adoption, setting clear policies, and embracing a culture of a learning orientation.” Training employees on how to integrate generative A.I. into their workflows could also help ease fears.

According to a recent report by Goldman Sachs, some 29 percent of computer and mathematical jobs are potentially vulnerable to A.I. takeover. If you want to “future proof” your career, it’s worth exploring how to integrate machine learning and A.I. into your current workflow; for example, you could utilize A.I. for repetitive functions, such as debugging, which would free up your time to engage in creative and job-enhancing pursuits, such as ideating new features or expanding your management abilities. And remember that “soft skills” are always valuable; machines can’t replicate empathy and effective teamwork, for instance.