A new generation of AI tools is poised to transform software engineering as we know it. Unlike conventional AI code assistants, AI agents are autonomous systems that can independently perform tasks across the software development lifecycle, making decisions, taking action, and optimising outcomes with minimal human intervention.
These agents promise to dramatically reduce friction in developer workflows, accelerate release cycles, and improve code quality.
They’re not just about boosting productivity, they’re reshaping how developers work, what skills they need, and how engineering teams deliver business value.
According to Sydney, Australia-based Adrian Leow, Vice President within the Applications and Software Engineering Leaders Group at Gartner, the shift is already underway.
“AI code assistants aren’t new,” Leow said. “Developers already use these tools powered by large language models. But AI agents step beyond AI code assistants to act as autonomous autopilots for software development and testing tasks.”
Unlike basic assistants, these agents bring a new level of intelligence. “Their capability to perceive their environment, make decisions, act and achieve goals… will redefine the developer experience,” he explained.
As AI agents remove repetitive or routine work, developers are freed to focus on more complex, creative challenges.
“Developers are free to focus on more creative, complex challenges for increased productivity and engagement,” Leow continued.
But this shift is not without risks.
“AI agents will also likely introduce new challenges, including security risks and vulnerabilities that developers must address,” he warned.
Leow emphasised that developers and QA teams must adapt quickly. “AI agents will disrupt traditional software engineering roles, and software developers must adapt and learn new skills in response.”
He outlined two emerging types of agents: “Role-specific AI agents are assigned specific tasks related to a particular role in the workflow, such as assisting with prioritising features, analysing a market or creating a business case.”
“AI agents will disrupt traditional software engineering roles, and software developers must adapt and learn new skills in response.”
– Adrian Leow
Meanwhile, “Goal-specific AI agents solve complex tasks in enterprise contexts. For example, they might perform code generation or performance tuning,” Leow explained.
Beyond engineering teams, the impact is enterprise-wide. “AI agents will enable organisations to deliver more business value with the same number of people and resources,” he said.
Faster delivery is just one benefit. “This reduced time to market gives organisations a competitive edge,” he added. Quality also improves: “As AI agents autonomously optimise code, detect bugs and automate testing, developers can deliver more reliable and secure software.”
And the insights AI agents generate can guide smarter decisions. “AI agents can provide predictive analytics and insights that help to optimise resource allocation,” said Leow.
“These capabilities enable organsations to be more agile, further enhancing their competitive position.”
While these tools bring undeniable advantages, Leow cautioned that challenges remain. “They will also create new challenges,” he said.
For software leaders willing to embrace change, however, AI agents mark the beginning of a new era, one in which engineering is increasingly autonomous, intelligent, and business-critical, Leow concluded.
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