Research reveals technical debt is blocking AI success in Australia

An AI readiness gap is emerging in Australia, with legacy architecture cited as the primary barrier to AI success, according to new IDC research commissioned by MongoDB.

IDC has predicted that organisations that fail to address technical debt will face 50% higher failure rates and rising costs for their AI initiatives by 2027.

The research paper, Modernising Legacy: Winning in the Age of AI, found that more than half of Australian organisations (58%) say their existing architecture makes it impossible to build new applications without extensive modernisation because it is too rigid, costly, and slow for today’s requirements.

However, there is a cohort of Australian leaders that are generating nearly three times more digital revenue (68%) than their mainstream peers (24%) by successfully investing in strategic modernisation programs to escape their legacy architecture.

“The stakes for modernisation are now critical. High-quality, integrated data is the essential fuel that determines the accuracy and performance of an AI application, making modern data architecture a foundational element of any AI strategy,” said Dr William Lee, Senior Research Director, Service Provider and Core Infrastructure Research, IDC Asia Pacific. “But research shows that many organisations are being held back by their existing rigid legacy architectures that do not have the flexibility and scalability to handle the high volume of unstructured data required for AI.”

The gap between AI ambition and reality is most visible at the data layer. For Australian businesses, the top challenge in software development identified in the research was outdated database technology that does not support the demands of AI workloads.

Support for new AI initiatives was the number one driver for modernising databases and applications in Australia, cited by 45% of organisations. However, almost all organisations (96%) have experienced failed modernisation initiatives, with siloed and poor-quality data cited as the major obstacle.

By contrast, the cohort of companies the research identified as ‘Leaders’ treats modernisation as an ongoing discipline and long-term investment, with 59% of Australian leaders running multiple programs to continually address legacy constraints and build cloud-ready foundations that can support production AI.

“AI has made technical debt an urgent board-level priority,” said Thorsten Walther, Managing Director, CXO Advisory at MongoDB. “The research is clear, strategic modernisation unlocks AI opportunities and supports a significant increase in revenue.”

IDC’s advice on how to bridge the AI readiness gap

To pay down data debt and improve AI readiness, IDC recommends that Asia Pacific organisations:

• make data quality and governance non-negotiable, so AI systems are fed consistent, trusted operational and vector data.
• modernise outdated architectures that block change, enabling rapid development of new applications without the risks and costs associated with legacy systems.
• build cloud-ready, hybrid operating models that reduce data sprawl and make data usable across environments.
• invest in skills and change management, so modernisation and AI delivery can move faster without breaking compliance and reliability.

The IDC InfoBrief, Modernising Legacy: Winning in the Age of AI, is based on an online survey of 1400 organisations with software development and delivery capabilities (more than 100 employees) across Australia, China, Hong Kong, India, Indonesia, Singapore, South Korea and Thailand, conducted in late 2025. Respondents were developers and IT decision makers, which included primary decision makers and members of decision-making units.

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