Indian IT Firms Face Data Governance Constraints
Indian IT firms are rapidly adopting enterprise AI but face widespread data readiness and governance shortfalls, industry practitioners and analysts said in 2025. Experts cite fragmented architectures, inconsistent data quality and immature lineage as primary reasons many pilots fail to reach production; McKinsey finds only 1% of companies at AI maturity and MIT estimates a 95% generative-AI pilot failure rate. Tier-1 firms fare better due to cloud-native platforms and targeted acquisitions like TCS's $700-million Coastal Cloud deal.
Key Points
- 1Highlight data readiness as the primary bottleneck, with fragmented architectures and inconsistent data quality across firms.
- 2Explain governance immaturity and unclear ownership prevent pilots scaling, causing most AI initiatives to stall before production.
- 3Advise building internal data platforms, stronger governance and hiring senior architects to enable production-grade enterprise AI.
Scoring Rationale
Strong industry relevance and credible sources drive score, limited novelty and moderate direct actionability cap impact.
Sources
Public references used for this report.
Practice interview problems based on real data
1,625 SQL & Python problems across 15 industry datasets — the exact type of data you work with.
Try 250 free problems