Why AI is key to hiring and retaining developers

By Bryan Kirschner, Vice President, Strategy at DataStax

It’s high time to treat HR as every bit as important to your company’s artificial intelligence strategy as IT.

Alongside all the evidence that getting your developers working on AI is good for your business, there’s mounting proof that even providing the opportunity to work on—and work with—AI has a positive effect on job satisfaction, recruitment, and retention.

Getting this right matters a lot today. In 2022, McKinsey’s State of AI Report notes that “[s]oftware engineers emerged as the AI role that survey responses show organizations hired most often in the past year, more often than data engineers and AI data scientists … another clear sign that many organizations have largely shifted from experimenting with AI to actively embedding it in enterprise applications.”

And the stakes are high. In the data gathered for the latest State of the Data Race report, the developers most tapped into next-generation technologies (these are developers who describe themselves as “the first in their organization to learn about new tools and technologies” and those upon whom others rely on for answers about new tech) describe interacting with real-time data and building AI and ML-powered apps as the most important factors in deciding where to work.

Overall, developers in organizations with both AI and ML widely deployed were 15 percentage points more likely than those in organizations where AI and ML are in “the early days” of deployment to say that “tech is more exciting than ever.” Similarly, they were 18 points more likely to say they felt “energized” about their jobs.

AI: An opportunity for your developers to make an impact

It isn’t hard to grasp why. Developers have always leaned into technologies that enabled them to increase their impact and keep their skills up to date. (In State of the Data Race data, for example, about three quarters rate opportunities to learn and to use the latest technologies as important in their work.)

And now, with many CIOs feeling pressure from corporate teams to create AI apps that could quickly cut costs, AI offers the prospect of helping to recession-proof their jobs.

So it’s vital that your people strategy keeps up with the pace at which your competitors are pushing their developers to produce, but also the ways rivals equip them to not only be happier, but also more productive.

AI: A way to help your developers be more productive

AI has a role to play in this, too. New research that details GitHub Copilot’s impact on developer productivity and happiness really hammers this home. Nearly nine out of 10 (88 percent) of 2,000 developers surveyed said that using Copilot, a real-time AI assistant that offers code suggestions, made them more productive. Sixty percent said they felt more fulfilled with their job.

The words of one software engineer illustrate why: “(With Copilot,) I have to think less, and when I have to think it’s the fun stuff. It sets off a little spark that makes coding more fun and more efficient.”

But it’s arguably the perspective of one chief technology officer that tees up the call to action best: “The engineers’ satisfaction with doing edgy things and us giving them edgy tools is a factor for me. Copilot makes things more exciting.”

You already know that the apps that will most delight your customers and win you market share or margin going forward will be AI-driven. Developers who already work for you today—and those you might be keen to hire—are eager to get to work on them, and to use AI tools themselves. That’s a clear North Star for your business, people, and IT strategy to align toward, ASAP.

Learn how DataStax enables real-time AI here.

About Bryan Kirschner:

Bryan is Vice President, Strategy at DataStax. For more than 20 years he has helped large organizations build and execute strategy when they are seeking new ways forward and a future materially different from their past. He specializes in removing fear, uncertainty, and doubt from strategic decision-making through empirical data and market sensing.