How Southeast Asia And India Are Leading In AI Adoption While Developers Stay Cautious

According to Agoda’s AI Developers Report 2025, most AI developers in Southeast Asia and India use AI tools in their development workflows to boost productivity. AI tools like ChatGPT and GitHub Copilot have become an integral part of the development workflow in these regions. Developers are concerned that, due to the unreliability of these tools, the gap between the adoption of AI and trust in it remains unclosed. Reported productivity gains are impacted by the lack of trust of developers in the ability of AI to support software development and the increasing use of AI.
The Report develops Regional Skills Snapshot Reports. These analyses provide the incremental impact of AI through the development of virtual circuits in the Indian and Southeast Asia markets. These Reports highlight an increasing gap in trust and use of AI among developers, which strengthens the need to build successful confidence in AI systems if efficient resource allocation and the maximization of economic development in AI circuit systems are to be realized.
Extensive use of AI in the developer community, but it lacks confidence
According to Agoda, almost 90% of the developers in Southeast Asia and India have started using AI, but only 43% believe it can perform at the level of a mid-level engineer. This speaks to a sizable confidence gap in the technology’s capability and the actual outcome. Furthermore, developers are still reluctant to use AI for more meaningful objectives.
Countries such as Thailand, India, and the Philippines have expressed a good amount of negativity, as many of the developers do not believe that AI can compete with the skills and reasoning of a human engineer. The Philippines has the most pronounced negativity, with 11% of the developers stating that AI will never be able to perform at the level of a mid-level engineer regarding the quality of output. Additionally, countries such as Singapore, Vietnam, and Thailand are showing a great amount of negativity as well.
With the development of Artificial Intelligence technologies, the positive and negative aspects of AI systems are being addressed. Developers are finding that AI tools are useful, but can generate outputs that are poor quality or inaccurate. This does not sound like the biggest problem, but it underscores the need for human involvement to steer things in the right direction.
AI’s biggest challenge
Being able to create and maintain workflows using AI systems that provide consistent and predictable results is one of the biggest challenges, especially in the software development industry. Over 75% of all developers in Southeast Asia and India view poor quality, unreliable, and unpredictable tools as their biggest challenges. This almost always takes precedence over the availability of the tools, the price of the tools, or any other challenges that may be present.
Thailand and the Philippines are among the countries that exhibit the strongest need for reliable outputs from AI tools, at 88% and 84%, respectively. Even developed countries like Singapore and Malaysia have 77% and 73%, respectively, for unreliable outputs when using AI tools. This shows that in almost all countries, irrespective of AI development in the region, the outputs from AI systems are very unreliable and inconsistent. Developers do not like unreliable AI outputs, and that is one of the biggest barriers to using AI systems in their workflows.
How Developers Deal with AI Issues
In response to reliability, developers have modified their workflows again to keep reliability in AI-generated code. About 66% of developers report that they always double-check AI-generated code before they pull it into production, and in terms of keeping standards high, this review process is vital. It is common for developers to revise AI-generated code before it is even close to production standards.
In fact, the implementation of AI in software development has increased the accountability, review, and oversight required in the process. Developers are still customarily “stuck” with the output due to the AI’s unreliable output. AI tools are being relied upon further and further, and that reliance is being justified by a lack of confidence in the AI.
Building Confidence Through Testing and Repetition
The report is saying that AI and software development will most likely not depend on early adoption, but on the ability to create a detailed structure for consistent and productive use of AI tools. While developers in Southeast Asia and India are shifting to the use of AI in a more integrated and automated way, confidence is still being built through repetition, testing, and real-world application.
Using AI to help streamline the development process is still providing benefits, especially in the process of completing repetitive and mundane tasks that have the ability to increase overall development team productivity. Developers are also not ready to place critical tasks in the hands of AI. Developers use AI for the more mundane portions of tasks, but are still working on building confidence. Structured reviews are leading to more confidence and less skepticism about AI for developers, while non-structured reviews are leading to skepticism.
Looking Ahead: Improving Trust in AI
As developers continue to use AI tools, they have learned to combine the benefits of the technology with careful supervision. Agoda’s findings suggest that AI is helping to improve productivity, but has not yet achieved the consistency necessary to substitute for human decision-making. Even though AI tools can accelerate development and enhance efficiency, the trust deficit toward the quality of the resulting output has developers as the final decision makers of the software’s quality.
Agoda’s Chief Technology Officer, Idan Zalzberg, mentioned that confidence built through structured frameworks is what will allow the further advancement of AI adoption in Southeast Asia and India. Developers will have to improve their fine-grained control frameworks in a manner that will allow AI tools to be trusted more as time progresses.
Conclusion: A Step Toward AI Maturity
In the Agoda AI Developer Report 2025, a comprehensive picture is drawn of that which outwards appears to be AI’s role in the software development ecosystem of Southeast Asia and India. Productivity and the rate of adoption of AI technology are commendable, but confidence in the reliability of technology needs to improve to eliminate the bottleneck in the development cycles. The route toward trust not only involves adoption but hinges more on the reliability, consistency, and oversight of structured work.
The potential of AI in software development is not determined by who is the most rapid adopter of the technological advancements, but instead by who is the most effective at weaving it into their development processes. The more developers streamline their workflows and enhance their revision processes, the more AI can be relied upon as a tool, fostering further productivity and innovation in software development.
The post How Southeast Asia And India Are Leading In AI Adoption While Developers Stay Cautious appeared first on Travel And Tour World.
























