The report, which surveyed 578 engineering and product leaders, confirms that AI is now a fixture in the software development lifecycle. Approximately 84% of teams utilize AI during the build phase, with 83% of respondents observing a meaningful reduction in code defects. Despite these performance metrics, the transition has created a friction point: 67% of developers admit that code generated by AI requires more rigorous testing than human-authored work. This shift effectively reallocates developer time from initial coding to intensive validation and review.

Brian Jackson, principal research director at Info-Tech, warns that speed should not be mistaken for finished quality. Currently, only 37.4% of organizations maintain formal procedures for managing AI-assisted output, leaving many teams to operate in an ad hoc environment. Security remains the primary barrier to broader integration, cited by 48% of firms, while legacy infrastructure continues to hamper AI effectiveness. As organizations scale, experts suggest that prioritizing clear production-readiness standards and security guardrails is essential to ensure that AI-driven efficiency does not evolve into unmanaged technical debt.