April 14: A widening AI readiness gap is emerging across Indian enterprises, with legacy architecture identified as the primary barrier to successful AI adoption, according to new research by International Data Corporation (IDC), commissioned by MongoDB.
The IDC InfoBrief, “Modernising Legacy: Winning in the Age of AI,” highlights that organisations failing to address technical debt could face up to 50% higher failure rates and increased costs in AI initiatives by 2027. Nearly 46% of Indian organisations reported that their existing architecture is too rigid, costly, and slow to support modern application development without significant upgrades.
However, the study also identifies a leading cohort of Indian enterprises that are successfully overcoming these barriers. These “AI Leaders” are generating more than three times higher digital revenue (73%) compared to their mainstream peers (20%) by investing in strategic modernisation initiatives.
Legacy Systems Hindering AI Progress
The research underscores that outdated systems are a major bottleneck in India’s AI journey. Key challenges identified include:
- Difficulty embedding security into development without compromising speed (35%)
- Poor data quality and data management issues (34%)
- Lack of alignment between business and software teams (28%)
Additionally, while 50% of organisations cited AI initiatives as the top driver for modernisation, nearly 98% reported experiencing failed modernisation efforts, primarily due to siloed and poor-quality data.
Data Modernisation Critical for AI Success
Commenting on the findings, William Lee, Senior Research Director at IDC Asia Pacific, said:
“The stakes for modernisation are now critical. High-quality, integrated data is the essential fuel that determines the accuracy and performance of AI applications. However, many organisations remain constrained by rigid legacy architectures that cannot handle the scale and complexity of AI-driven workloads.”
Leaders Driving AI-Led Growth
The research highlights that leading organisations treat modernisation as a continuous, long-term investment. Around 57% of these leaders run multiple transformation programmes to build cloud-ready, scalable foundations that support production-grade AI.
Thorsten Walther, Managing Director, CXO Advisory at MongoDB, added:
“AI has made technical debt an urgent board-level priority. Strategic modernisation is unlocking new AI opportunities and driving significant revenue growth. Organisations that move away from siloed legacy systems towards AI-ready platforms are gaining a clear competitive advantage.”
Case Study: IntellectAI
One example cited in the research is IntellectAI, which leveraged MongoDB to modernise its data infrastructure. This transformation enabled the company to scale ESG and compliance analysis from 100–150 companies manually to over 8,000 companies globally, achieving over 90% accuracy and significantly improving decision-making speed.
Industry Perspective
Aamir Sait, Vice President – India, MongoDB, said:
“Legacy architecture often acts as a constraint in fast-growing markets like India. However, organisations that address technical debt and adopt modern data platforms are better positioned to unlock AI’s full potential and build long-term competitive advantage.”
The research also highlights companies such as Zepto, SonyLIV, and Cars24 as examples of organisations successfully leveraging modern data strategies to advance AI adoption.
Recommendations to Bridge the AI Gap
IDC recommends that organisations across Asia Pacific take the following steps to improve AI readiness:
- Prioritise data quality and governance
- Modernise legacy architectures to enable agility and scalability
- Build cloud-ready and hybrid operating models
- Invest in skills development and change management
Research Methodology
The IDC InfoBrief is based on a survey of 1,400 organisations across Asia Pacific, including India, conducted in late 2025. Respondents included developers, IT decision-makers, and business leaders from organisations with over 100 employees.
