Demand for real-time AI data processing is surging but infrastructure lags, Confluent survey finds
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Nearly three-quarters (72%) of global IT leaders say a lack of real-time data infrastructure is stalling their efforts to scale artificial intelligence, according to the 2026 Data Streaming Report from Confluent, an IBM affiliate.The report, which surveyed 4,625 IT leaders worldwide, examines the challenges that enterprises are facing when scaling AI, and why they may need to focus more on fixing the infrastructure their AI initiatives rely on rather than simply increasing investment in AI itself.
According to the research, 72% 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 (72%), uncertainty around data lineage, timeliness and quality (66%), and fragmented ownership of data (65%).
These infrastructure challenges are also slowing the deployment of agentic AI. Two-thirds (66%) of IT leaders cite data infrastructure and data quality issues as barriers to agentic adoption, and only 32% report having agentic AI in production, with the majority experiencing delays.
