How AI application development for business is changing in the APAC

For tech leaders – CIOs and CTOs – in Asia-Pacific, AI is becoming the foundation for how applications are built and maintained.

A recent report from Information Services Group (ISG) shows that companies in the region are integrating AI directly into their development processes. The push hasn’t come about because of a need for speed; rather, it’s about modernising older systems and making software more reliable.

The change is significant as it’s coming from the top, down. Governments in Southeast Asia, Australia, and India are encouraging the shift with national strategies focused on innovation and getting people trained in new technologies.

The impact from code to competition

AI tools can predict potential bugs, generate snippets of code, and do deep analysis – freeing up engineers to focus on building innovative features instead of maintenance tasks.

Testing is getting smarter too: AI-powered quality assurance tools can automate test script creation and fix broken tests – reducing testing timelines and making products more stable.

And monolithic systems? AI is helping to refactor and map legacy dependencies, making it easier to move to modern, cloud-based architectures. This is important for agility, especially in industries like banking and logistics.

The result is faster delivery of digital services and a better experience for customers, which can lead to measurable improvements in efficiency and overall risk reduction.

Michael Gale, ISG’s Asia-Pacific regional leader, is on the record as saying, “Asia Pacific is quickly becoming a hub for delivering AI-powered application development services, and the focus is squarely on innovation and advanced technologies.”

Challenges, & how to tackle them

While AI-powered tools can offer potential, implementing them isn’t as simple as flipping a switch. Companies face challenges around integration, governance, and making sure their teams are right-skilled.

The thorny issue of integration with older systems remains, too. Often, AI can be used to extract the logic from legacy systems, but it’s vital to understand where the data comes from, and to test AI’s best-guesses as to how it’s processed.

There’s also the issue of AI governance: as code and testing become automated, companies need to establish rules and safeguards around things like code quality, security, intellectual property, and potential headaches in future code maintenance.

Getting developers and testers on board requires training. There’s a perception that staff need to learn how to work with AI tools as an augmentation, not a replacement, for their skills.

Finally, navigating the AI vendor landscape can be challenging. Leading providers – including Accenture, Capgemini, Cognizant, IBM, Infosys, and Wipro – use AI in their services, often tied to platforms like Azure AI Foundry, AWS Bedrock, and Google Vertex AI. Like the leaders of these global giants, CIOs need to ensure all tools work together.

Maharshi Pandya, ISG’s lead analyst, emphasised the role of service providers: “The rise of AI tools for application development is happening at the same time that companies in Asia Pacific are undergoing massive digital transformations. Service providers have a crucial role in helping companies adopt these innovations, a trend that’s being championed by leaders in Southeast Asia and elsewhere.”

Tech leaders’ checklist

For CIOs, CTOs, and CDOs considering AI adoption, ISG’s findings suggest five steps or priorities:

• Modernise first. Use AI to update and migrate legacy systems before rolling out AI tools.
• Automate with oversight. Build transparency and accountability into AI-based debugging and code generation.
• Prioritise compatibility. Align tools with enterprise data platforms proven to work, like Azure AI Foundry, or Google Vertex AI.
• Invest in the team. Train development teams in AI litreacy and DevOps automation.
• Track progress. Measure success using metrics like release velocity and ongoing maintenance & improvement costs of applications.

Asia-Pacific is leading the way in AI-powered software engineering. For business leaders, the advantage won’t come from the presence of some element of AI, somewhere in the technology stack worn like a badge of progress. It’s about building governed, metrics-driven application development ecosystems that aid digital transformation and effectively maintain control and security.

(Image source: “Singapore skyline in black and white” by gunman47 is licensed under CC BY-NC-ND 2.0.)

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