Solving tech debt unlocks 3x digital revenue boost for Australia’s AI leaders
An Artificial Intelligence (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 who fail to address tech 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 who are generating nearly three times more digital revenue (68%) than their mainstream peers (24%) by successfully investing in strategic modernisation programmes 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 For Australian businesses the top challenge in software development identified in the research was outdated database technology that does not support the demands of AI workloads.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’ treat 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. The leaders across the region are showing what’s possible when organisations ditch rigid, siloed legacy systems and move to AI-ready data platforms like MongoDB.”
One example of an organisation demonstrating how to become a leader in AI and modernisation is Australia’s Bendigo Bank. In 2025, the bank modernised a mission-critical banking system by moving off rigid legacy technology onto MongoDB, using AI-assisted tooling to break work into smaller, safer releases without outages. The bank reduced the development time required to migrate a core banking application off of a legacy relational database to MongoDB Atlas by up to 90%, at one-tenth of the cost of a traditional migration.
Lendi Group is another Australian organisation demonstrating how to become a leader in AI, as the company aims to become one of Australia’s first fully AI-native businesses by June 2026.
In order to modernise its legacy data architecture which it inherited from a previous merger, Lendi Group worked with MongoDB to build an operational data layer (ODL), creating the foundation for the next generation of Lendi Group’s AI-powered services. It has already improved time to market for AI features by approximately 40%.
“Legacy is a massive and expensive hurdle for organisations in Australia. But we’ve seen first hand how outstanding businesses, from scale-ups like Heidi to large enterprise organisations like Lendi Group and Bendigo Bank, can make strategic modernisation an engine for growth and success in the AI era,” said Simon Eid, Senior Vice President APAC, MongoDB.
IDC: How to Bridge the AI Readiness Gap
To pay down data debt and improve AI readiness, IDC recommends that Asia Pacific organizations:
- 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.
Find out more about how Asia Pacific organisations can replicate the success of the Leaders and close the AI readiness gap in this IDC InfoBrief.
