Generative AI for Developers: Brace for Disruption

Industry thought leaders see 2024 as the year of “generative AI impact.”


While a great deal of hype surrounded generative artificial intelligence (AI) over the past year, businesses, including many software companies, now consider it a must-have part of their tech stack. Industry leaders predict huge growth across the board as generative AI for developers offers solutions for security, generating and testing code, project management, application development, and more. They also offer caution regarding introduced bias, as well as threats to privacy and security.

Generative AI Will Play a Bigger Role in Generating and Testing Code

David DeSanto, chief product officer at GitLab, says AI will dominate code testing workflows in 2024. “The evolution of AI in DevSecOps will transform code testing over the next couple of years. Currently, 50 percent of all testing is conducted with the help of AI. Expect this to reach 80 percent by the end of 2024, approaching 100 percent automation within two years.”

Shomron Jacob, head of applied machine learning and platform at, agrees. “Many organizations will prioritize these increasingly powerful tools to enhance developer productivity and accelerate the delivery of innovative products and customer experiences. The evolution of generative AI, particularly in new code-generation large language models (LLMs) like our own Interplay-AppCoder, is becoming integral to software development workflows. These tools amplify developer team efficiency, helping give businesses a competitive edge in agility and speed. By automating routine coding tasks, resources can be reallocated to innovation and strategic growth. Advances in code-generation tools will continue to move rapidly in 2024 as they integrate the latest coding practices and undergo continuous refinement.”

Tiago Cardoso, principal product manager at Hyland, adds, “These tools will play a supportive role in amplifying developers’ capabilities, hastening routine coding tasks, and highlighting potential issues that often result in extensive debugging sessions. Such technological augmentations can result in boosted productivity and, on average, superior code quality. Moreover, generative AI tools open doors for companies to offer a new breed of software that relies not only on pre-determined logic but also on historical data and content. This enables these systems to perform advanced functions and carry out capabilities not conventionally practicable to set in code.”

With The Right Tools, Developers Will Be More Productive

Sean Mahoney, general manager and vice president at Ensono, says generative AI’s greatest potential to provide value is helping people do their jobs better. “The key to unlocking value is fine-tuning appropriate foundational models. Equipping people with the knowledge, resources, governance, and training to use AI correctly will make the difference.” He believes some companies “are moving too fast and not considering the negative implications of uneducated, ill-informed, or unregulated AI use.”

Yingqi Wang, CEO and founder of ONES, points out, however, “Organizations should be focused on defining AI’s role and developing guidelines for its use. AI systems should be held to the same level of accountability as a human to help ensure it produces reliable content.”

“A metaphor I like to use to understand this is how we can compare the implementation of AI to an autopilot in aviation, “ Wang says. “When the autopilot system reached a standard of reliability, workflows were rebuilt, impacting the pilot’s job. In the example of AI-powered virtual meetings, AI can take on time-consuming tasks that silo individual team members, like note-taking and transcription, or it can supplement highly skilled positions with real-time translation. In both cases, as it becomes more widely adopted, the better we understand its capabilities and reliability.”

DeSanto points out that users must overcome AI bias. “In the short term, the rapid development and adoption of AI tools and products leveraging AI services will lead to an increase in biased outputs. As most AI services scrape the internet to build training data, the inherent biases of the internet will propagate into these offerings until needed controls can be added,” he says.

Generative AI’s Impact on Security

In DeSanto’s view, AI’s escalating threat to IP and privacy is a code-red situation.  He states, “As AI-powered code creation is increasingly adopted by organizations within their software development practices, the risk of significant AI-introduced vulnerabilities and intellectual property loss emerging in the next year is high. The situation will only worsen unless privacy and intellectual property (IP) protections are prioritized around how AI-powered code creation is adopted and deployed.”

Joey Stanford, VP of data privacy and compliance at, says, “President Biden’s executive order on AI is certainly a step in the right direction and the most comprehensive to date; however, it’s unclear how much impact it will have on the data security landscape. AI-led security threats pose a very complex problem, and the best way to approach the situation is not yet clear. The order attempts to address some of the challenges but may end up not being effective or quickly becoming outdated. For instance, AI developers Google and OpenAI have agreed to use watermarks, but nobody knows how this is going to be done yet, so we don’t know how easy it’s going to be to bypass/remove the watermark. That said, it is still progress, and I’m  glad to see that.”

Total Impact

Eric Purcell, senior vice president of global partner sales at Cradlepoint, says 2024 will be a turning point for generative AI for developers.

“If 2023 was the year of flashy AI investments, 2024 will be the year of AI impact — which may not be as visible to the naked eye. AI will move from a “tool you go to” (such as ChatGPT) to being integrated into the applications we are using everyday and empowering network connectivity. As such, we’ll begin to see the benefits of AI being integrated into all applications related to the network, bolstering network predictability, troubleshooting, security, and more,” Purcell says.

DeSanto concludes, “Integrating AI into products and services will become a standard, not a luxury. With organizations pushing the boundaries of efficiency through AI adoption, 2024 will be the year that more than two-thirds of businesses will embed AI capabilities within their offerings.”

Kelly Allred

Kelly Allred is a contributing editor for DevPro Journal.

Datacap - We Solve Payment Problems
Kelly Allred
Kelly Allred is a contributing editor for DevPro Journal.