600 developers from seven countries indicated weekly AI use, productivity gains, reliance on self-directed learning, inconsistent output quality and governance gaps.

Based on an August–September 2025 survey of around 600 software developers* across Indonesia, Malaysia, Singapore, Thailand, the Philippines, Vietnam, and India on how AI is used in developer workflows across Southeast Asia and India, a digital travel platform has shared several findings about regional AI adoption trends with the media.

First, 95% of respondents indicated that they used AI weekly, with 56% reporting they always kept an AI assistant open. They cited productivity as the main motivation, with 80% selecting speed and automation as key drivers. About 37% indicated they saved four to six hours per week through AI use. Some 22% reported using AI to solve unfamiliar problems, and 43% indicated AI performed at the level of a mid-level engineer. AI use was strongest for code generation, with 94% relying on it for this task, but dropped for downstream tasks like documentation, testing, and deployment.

Second, 79% cited inconsistent or unreliable AI outputs as a barrier. About 67% indicated they always reviewed all AI-generated code before merging, and nearly 70% cited routinely reworking AI outputs to ensure correctness. Formal AI policies were reported as rare, with one in four respondents citing operating under official guidelines.

Other findings

Third, 71% of respondents reported learning AI skills primarily through self-directed methods such as tutorials, side projects, or community engagement, while 28% had cited receiving employer-led training. Also:

  • 87% of respondents had indicated they had adjusted their learning or career plans to incorporate AI skills, and 62% expected AI to expand career opportunities
  • 72% had indicated that AI improved code quality, although they indicated that collaboration improvements lagged behind productivity gains

Said Idan Zalzberg, Chief Technology Officer, Agoda, the firm that commissioned the survey, “What began as a way to speed  up tasks like writing, testing, or debugging code has grown into a broader shift in how software is built.  Today, AI helps teams move faster, learn continuously, and solve problems in new ways… The real opportunity lies in supporting this ground-up maturity with structured practices  and responsible experimentation, turning high adoption into consistent, lasting capability.”

*Methodological disclosure declares without supporting data, that “Participants spanned a mix of  experience levels, company sizes, and industry sectors, providing a representative view of how AI is  being adopted, integrated, and experienced across the region’s developer ecosystem.”