77% of engineering leaders cite AI integration in apps as major challenge: Gartner Survey

While the integration of AI into software engineering is fraught with complexity, it is also a catalyst for meaningful change—driving innovation in team composition, hiring practices, and development methodologies across the tech landscape

Engineering leaders are facing significant challenges as they work to integrate artificial intelligence (AI) into software applications and workflows, according to a survey conducted by Gartner, Inc. between October and December 2024. The study, which included 400 software engineering and application development leaders from the US and UK, revealed key pain points and emerging trends shaping the future of AI in the industry.

The survey found that 77% of respondents view building AI capabilities into applications to improve features and functionality as a major or moderate pain point. Additionally, 71% identified using AI tools to augment software engineering workflows as a significant challenge. These results reflect the growing complexity organizations encounter when adopting AI, despite high expectations and industry momentum.

Jim Scheibmeir, Vice President and Analyst at Gartner, explained, “CEOs recognize AI as the most transformative technology for their industries, driving increased interest in AI agents and platforms. However, turning that interest into successful execution remains difficult.” Both established hyperscalers and emerging vendors are continuously enhancing AI application development platforms to address these pain points. Gartner estimates this market’s value at $5.2 billion, signaling rapid innovation and investment.

Scheibmeir advises engineering leaders to favor AI platforms with strong ecosystems rather than assembling fragmented tools and services. “This strategy supports scalability, reuse, and consistency in a field that is still very new to many software teams,” he added.

AI’s impact on engineering talent

Beyond technology, AI is reshaping talent within software engineering teams. AI agents currently act as collaborative learning partners, freeing engineers to focus on complex and creative tasks. This shift allows professionals without traditional computer science backgrounds to enter the field, diversifying the talent pool.

Nitish Tyagi, Principal Analyst at Gartner, noted, “Incorporating team members from design, psychology, and the arts introduces fresh viewpoints and encourages innovative problem-solving.” Gartner predicts that by 2028, 40% of software teams will include members from nontraditional technical backgrounds, up from 20% today.

Despite AI’s expanding role, human oversight remains essential. Organizations still need engineers skilled in logic, algorithm design, and software fundamentals to review AI-generated work. Nontechnical team members contribute creative approaches to problem-solving enhanced by AI tools.

Tyagi envisions the future dominated by composable teams made up of software engineers, UX designers, product managers, and data scientists from varied educational backgrounds. To support this, companies are shifting toward skill-based hiring, utilizing AI-driven assessments and personalized learning paths to cultivate necessary capabilities.

The survey also showed that 38% of respondents believe AI-assisted learning is the most effective way to develop new skills, highlighting AI’s growing influence in workforce training.

Overall, the findings underscore that while integrating AI into software engineering remains complex, it also offers opportunities to transform team composition, talent acquisition, and software development practices—paving the way for more innovative and inclusive technology solutions.