Nearly eight out of 10 (79%) of Indian IT leaders say a lack of real-time data infrastructure is stalling their efforts to scale AI, according to a new 2026 Data Streaming Report from Confluent.
The report, which surveyed 4,625 IT leaders across 14 countries, including 650 respondents from India, examines the challenges that enterprises are facing when scaling AI, and why they may need to focus more on fixing the infrastructure AI initiatives rely on rather than simply increasing investment in AI itself.
According to the research, 79% of IT leaders have encountered at least three challenges when scaling AI initiatives. Among the most common are insufficient infrastructure for real-time data processing (78%), uncertainty around data lineage, timeliness and quality (73%), and fragmented ownership of data (73%).
These infrastructure challenges are also slowing the deployment of agentic AI. Nearly three-quarters (72%) of IT leaders cite data infrastructure and data quality issues as barriers to agentic adoption, and only 37% report having agentic AI in production, with the majority experiencing delays.
“AI adoption has reached a point where success is no longer determined by access to technology alone. As organisations look to scale AI across business functions, the ability to move, govern, and act on data in real time is becoming increasingly important. Our findings show that Indian enterprises recognise this shift, with investments in data streaming rising alongside investments in AI.”
“What’s particularly notable is that organisations are not viewing data infrastructure and AI as separate priorities. The two are becoming closely linked. As AI applications and agentic systems become more deeply embedded into business operations, organisations need data that is continuously available, trusted, and discoverable.” said Rubal Sahni, AVP – India and Emerging Markets, Confluent.
Unlocking AI in real time
As organisations look to move AI from pilot projects into production, attention is increasingly turning to the data that powers it. 86% IT leaders say using enterprise data to drive AI-based systems is a top business priority, highlighting the growing importance of real-time access to trusted information.
The findings suggest many organisations see data streaming as a key part of the solution.
Nearly nine in 10 (91%) say data streaming platforms help unblock agentic AI progress by making data more trustworthy, contextualised and discoverable. Meanwhile, 97% say data streaming increases or is expected to increase the impact of their AI investments, and 94% say it helps ease the path to AI adoption.
Data streaming investment overtakes AI
The report also finds that as AI investments increase, investments into data streaming also increase, with 92% of IT leaders ranking data streaming as a key priority, alongside 91% citing AI and machine learning technologies. The findings suggest IT leaders increasingly recognise that maximising the value of AI depends on access to trusted, real-time data. As organisations move AI initiatives into production, attention is shifting from models alone to the infrastructure needed to deliver the right data at the right time.
Commenting on the findings, Shaun Clowes, Chief Product Officer at Confluent, said: “Most organisations do not have an AI investment problem, they have a data problem. AI systems depend on fresh, accurate and contextual information, but too many are still being built on fragmented data, batch processes, and infrastructure that was not designed for continuous intelligence.
“As organisations move beyond experimentation and start deploying AI across critical business processes, those gaps become harder to ignore. Models need to be connected to the systems, events and signals that reflect what is happening across the business. The companies making the most progress are investing not only in AI itself, but in the data foundations needed to support it. Those foundations will determine which organisations can turn AI investment into business value at scale.”