AI Success Depends on Trusted Real-Time Data, Says Confluent's Rubal Sahni
Artificial intelligence has moved well beyond experimentation. Enterprises have invested heavily in large language models, copilots, and agentic AI, but many continue to struggle when it comes to deploying these technologies at scale.
Confluent's 2026 Data Streaming Report, based on responses from 4,625 IT leaders across 14 countries, including 650 from India, suggests the bottleneck is no longer AI investment. Instead, organisations are finding that fragmented data, legacy architectures, and the lack of real-time data infrastructure are slowing AI adoption.
The study found that 79% of Indian IT leaders believe inadequate real-time data infrastructure is delaying AI growth, while 78% cite insufficient infrastructure for real-time data processing as a major challenge. Only 37% of organisations have successfully deployed agentic AI into production.
In an interaction with CIOL, Rubal Sahni, AVP – India and Emerging Markets, Confluent, discusses why AI success increasingly depends on trusted, real-time enterprise data; how organisations...
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