AI agents redefining software development as developers embrace automation, says Salesforce report

A new study by Salesforce has unveiled a strong wave of optimism among software developers regarding agentic AI and its impact on the software development landscape. According to the State of IT report, 92% of developers believe AI agents will help advance their careers, while an overwhelming 96% anticipate a significantly improved developer experience due to AI-driven automation.

The global survey, which gathered insights from over 2,000 software development leaders and an additional 250 frontline developers in the United States, highlights the growing recognition of AI agents as essential tools in software engineering. More than 80% of respondents predict that AI agents will soon be as fundamental to app development as traditional software tools.

AI Agents Transforming Developer Workflows

The perception of AI in software development has undergone a notable shift. While AI was once met with skepticism due to concerns over job displacement, developers now view agentic AI as a means to enhance efficiency, reduce tedious tasks, and focus on more strategic, high-impact projects. AI agents are being widely adopted to handle routine coding tasks such as debugging, error resolution, and test case generation. With low-code/no-code tools making AI more accessible to a broader range of developers, the barriers to leveraging AI agents are rapidly diminishing.

Alice Steinglass, Executive Vice President and General Manager of Platform, Integration, and Automation at Salesforce, emphasized that AI agents are a “revolutionary force in software development.” She explained that AI tools are streamlining software engineering by automating repetitive tasks, allowing developers to focus on architecture, innovation, and strategic decision-making.

A Shift Towards High-Impact Software Development

The survey underscores how AI agents are changing how productivity is measured within development teams. Traditionally, developer performance was gauged based on output volume, but now, 92% of developers prioritize impact-driven metrics over raw coding output. With AI agents taking over time-consuming tasks, developers are increasingly dedicating their efforts to designing and overseeing AI-driven architectures, enhancing AI oversight and monitoring complex systems, and engaging in higher-level problem-solving and innovation.

Developers have particularly embraced AI agents for debugging and fixing errors efficiently, generating automated test cases, and handling repetitive coding tasks. The rise of low-code/no-code platforms has further accelerated the adoption of AI agents, with 85% of developers using agentic AI currently relying on these tools. Additionally, 77% believe that low-code/no-code solutions will democratize AI development, making it more accessible to non-traditional developers.

Case Study: Secret Escapes Adopts AI Agents for Faster Development

A notable example of AI’s efficiency in action is Secret Escapes, a global luxury travel company. By implementing Salesforce’s low-code Agent Builder, the company significantly reduced its development time for AI-powered customer service solutions. Previously, the company required six months to build and train a customer support bot. However, with agentic AI, Secret Escapes developed, tested, and launched a fully functional AI-driven customer support agent in just two weeks. This case study illustrates how businesses can rapidly integrate AI-driven automation into their operations, improving efficiency and customer experience.

Developers Seek More AI Training and Infrastructure Support

Despite the widespread enthusiasm for AI agents, developers have highlighted several challenges that need to be addressed for broader adoption. Infrastructure limitations remain a significant hurdle, with 82% of developers believing their organizations need to upgrade their systems to effectively deploy AI agents. Data quality has also emerged as a concern, as 56% of developers report that their company’s data is insufficient to support reliable agentic AI applications.

Testing frameworks are another critical area that requires improvement, with nearly half of developers stating that their organizations lack robust testing processes for AI-powered development. Additionally, more than 80% of developers expect AI expertise to become a core requirement in their profession, yet over half acknowledge that they lack sufficient training to fully leverage AI agents. To bridge this gap, developers are calling for comprehensive training in technical AI skills, updated role definitions, and more accessible resources to facilitate AI integration in their workflows.

AI Agents Shaping the Future of Software Engineering

As agentic AI continues to gain traction, the role of software developers is evolving from manual coding to more strategic, high-value responsibilities. AI-powered agents are no longer just assistants; they are becoming essential tools that enhance productivity, creativity, and efficiency in software development. For developers, this shift presents opportunities to engage in more impactful work, focusing on system architecture, AI oversight, and long-term innovation rather than routine coding tasks. As organizations embrace AI-driven development, investing in infrastructure, training, and data quality will be crucial in maximizing the potential of AI agents.

With increasing adoption rates and ongoing technological advancements, AI agents are set to play a defining role in the next era of software development—one where developers and AI collaborate to drive innovation at an unprecedented scale.