For IT pros, AI in job postings needs clarity

For years now, employers have pushed job candidates to explain how they’ll deploy AI within an organization.

But employers are often vague when it comes to stating how candidates are expected to use AI, with many job postings missing AI-related details. It’s becoming a serious concern, with an October report from Indeed finding 25% of listings do not clarify the details of use cases for the AI they require.

Run it back. Cory Stahle, an Indeed senior economist, told IT Brew this lack of precision has wide-ranging impacts.

New employees hired to work on AI systems without a sense of what those systems are will be unclear on their role at the organization. Integrating AI solutions into existing frameworks without understanding the implications can also add unnecessary complications. And confusion can mean an expansion of the attack surface.

“Responsibility around the use of these models is key right now—thinking about, ‘Okay, how do we use this model in a way that not only protects our data but still continues to provide a good experience for our customers?’” Stahle said. “At the end of the day, the goal of implementing AI shouldn’t be to implement AI; the goal of implementing AI should be to provide a better product, better service, to increase productivity.”

Draup CEO Vijay Swaminathan agrees. He told IT Brew that internal and external job postings that each have different wording and skills can become tangled.

“There is a ton of work that is yet to be defined in terms of how to make the machines very intelligent so that they, the agents themselves, can communicate with each other and communicate with other data sets and then go get the task done,” Swaminathan said.

No matter what aspect of the technology you’re working with, Swaminathan added, clarity is important—and requirements will only become more critical as AI technology integrates more fully into IT workflows.

Making a difference. An unclear job description leaves prospective employees in the lurch. October data from Dayforce indicates that 71% of workers have not been AI-trained in the last year. Without adequate training, AI implementations are unlikely to succeed.

“The good-functioning companies know what they are doing, and they are absolutely making sure that they can not only dominate the market, but also be in the winning lane within their chosen domains,” Swaminathan said.

Making a point. Conveying the complexity of the AI space to higher-ups is important, especially since those executives adopt the technology at higher rates than subordinates. Stakeholders need to have a full picture of what they’re allowing into their workspace and how it works. Job postings that highlight AI usage but don’t offer specifics can indicate a greater problem with how much higher-ups and the broader organization actually understand AI.

“For workers, that’s a really important thing right now—communicating to leadership that, yes, these technologies are really powerful in these ways, but they’re also very limited in these other ways,” Stahle said.