Why AI is the key to hiring and retaining developers

By Bryan Kirschner, Vice President, Strategy at DataStax

It’s high time to make HR as important to your organization’s AI strategy as IT.

Along with all the evidence that getting your developers to work on AI is good for your business, there’s growing evidence that even providing the opportunity to work on – and with – AI is beneficial job satisfaction, hiring and employee retention.

Getting this right is very important today. In 2022, McKinsey’s State of AI Report states that “[s]Software engineers emerged as the AI ​​role organizations surveyed most frequently hired over the past year, more so than data engineers and AI data scientists… another clear sign that many organizations are largely moving from experimenting with AI to actively embedding it in Enterprise applications have migrated.”

And the stakes are high. In the data collected for the latest State of the Data Race report, developers made the most use of next-gen technologies (those developers who describe themselves as “the first in their organization to learn about new tools and technologies”) , and those others rely on for answers about emerging technologies) 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 where both AI and ML are prevalent said that “technology is more exciting than ever” 15 percentage points more often than those in organizations where AI and ML are “in the early days” of deployment. Similarly, they were 18 percent more likely to say they felt “excited” about their work.

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AI: An opportunity for your developers to make a difference

It’s not difficult to understand why. Developers have always relied on technology that allowed them to increase their impact and keep their skills sharp. (In the State of the Data Race data, for example, about three-quarters rate opportunities to upskill and use the latest technologies as important to their jobs.)

And now, as many CIOs feel pressure from corporate teams to build AI apps that could quickly reduce costs, AI offers the prospect of recession-proofing their workplaces.

Therefore, it is important that your staffing strategy keeps pace with the pace at which your competitors are pushing their developers into production, but also with the way competitors are equipping them to not only be happier but also more productive.

AI: A way to help your developers be more productive

AI also plays a role in this. New research showing GitHub Copilot’s impact on developer productivity and satisfaction really hits this house. Nearly nine in ten (88 percent) of the 2,000 developers surveyed said that using Copilot, a real-time AI assistant that offers code suggestions, has made them more productive. 60 percent said they felt more fulfilled in their work.

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

But it’s arguably a chief technology officer’s perspective that best encapsulates the call to action: “The engineers’ satisfaction in doing outlandish things and that we’re giving them outlandish tools is a factor for me. Copilot makes things more exciting.”

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You already know that the apps that delight your customers the most and will give you market share or margin in the future will be AI-driven. Developers who are already working for you today – and those you might be interested in hiring – are eager to work on them and use AI tools themselves. This is a clear North Star for your business, your people and your IT strategy to align with as soon as possible.

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 corporations build and execute strategy as they seek new paths and a future vastly different from their past. He specializes in removing fear, uncertainty and doubt from strategic decision-making through empirical data and market observation.