AI in APAC: Developer Productivity & Challenges

AI's Rise: Real-World Impact

The Agoda report, as summarized in this InfoQ article, provides valuable insights into the practical application of AI tools by developers in Southeast Asia and India. The core finding—that AI is mainstream but not yet mature—is particularly noteworthy. The article effectively highlights the gap between widespread AI tool adoption and the lagging development of formal organizational policies and frameworks. This disparity leads to a bottom-up approach to AI usage, where developers are actively managing the reliability and consistency of AI-generated code. This creates both opportunities and challenges. While it fosters a culture of responsible AI adoption through review and rework, it also underscores the need for organizations to catch up by providing structured training, clear guidelines, and frameworks that align experimentation with security and compliance. The focus on self-directed learning, with developers relying heavily on online resources and peer learning, is also significant, reflecting a broader trend of continuous professional development in the tech industry. The limitations of the article are primarily related to its summary nature; it is based on a report and lacks the raw data or detailed methodologies that would allow for a deeper understanding of the findings, such as the specific types of AI tools used or the precise criteria for evaluating 'reliability' and 'inconsistent outputs'.

The article also implicitly raises the question of scalability and long-term sustainability. While AI tools provide incremental productivity gains, the reliance on human oversight and rework, while beneficial for ensuring quality, may not be scalable in the long run. As AI-generated code becomes more complex and the scale of projects increases, the review-by-default culture might become a bottleneck. Furthermore, the article does not delve deeply into the potential impact of AI on developer roles and skill sets. While it notes that AI is viewed as an augmentative tool, the long-term implications of AI-driven coding on job responsibilities and career paths are not fully explored. The article’s focus on the region, while valuable, could be strengthened by comparing and contrasting the findings with AI adoption trends in other global regions, to provide a more comprehensive perspective. Finally, the article's reliance on a single source, the Agoda report, limits its ability to offer a broader view, and corroboration with data from other sources would make the findings more robust.

Key Points

• AI adoption is high among developers in Southeast Asia and India, with 95% using AI tools weekly.
• Developers report productivity gains, primarily in coding, debugging, and learning new APIs, but AI is mainly used as an assistant.
• Organizational governance lags behind tool adoption, with few formal AI policies in place.
• Developers practice 'review-by-default' for AI-generated code, indicating a responsible approach despite lacking formal frameworks.
• Self-directed learning is prevalent, with developers relying on online resources and peer learning for AI skills development.

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📖 Source: How Developers in Southeast Asia and India Are Really Using AI in 2025