India’s digital economy aims for one trillion dollars. AI is key, but data issues hinder progress. Poor data quality and governance are major obstacles. Open data architectures like lakehouse models offer solutions. Companies are adopting technologies like Apache Iceberg. Strong data foundations are crucial for AI success. This enables innovations and reduces risks.
India’s digital economy is projected to hit $1 trillion in the coming years, powered by platforms such as UPI, Aadhaar, and the Open Network for Digital Commerce (ONDC). Artificial intelligence is expected to accelerate that growth reshaping finance, healthcare, retail, and logistics. But here’s the hard truth: AI cannot deliver without fixing India’s data foundations. Scattered, poor-quality and siloed information continues to hobble enterprises. Unless this gap is bridged, much of the nation’s AI ambition risks being reduced to pilot projects and press releases.
The Data Dilemma
A recent IDC report projects that AI spending in India will grow 35 percent annually, reaching $9.2 billion by 2028. Yet the barriers remain steep: more than half of enterprises cite weak data quality, and nearly two-thirds identify poor governance as the biggest obstacle. This is not just a technology issue it’s a business risk. CIOs and CDOs know that fragmented systems drive up costs, slow decision-making and leave organizations vulnerable in a regulatory environment shaped by the new Digital Personal Data Protection Act.
