Nearly three-quarters of IT leaders say a lack of real-time data infrastructure is stalling their efforts to scale AI, and only 32 per cent have agentic AI in production, according to Confluent's 2026 Data Streaming Report.
The fifth annual report, produced with Freeform Dynamics and Radma Research, surveyed 4,625 IT leaders across 14 countries including Australia. Respondents hold strategic and leadership positions in companies with 500 or more employees, with experience of data streaming ranging from little to significant.
The research found 72 per cent of IT leaders have encountered at least three challenges when scaling AI initiatives. The most common are insufficient infrastructure for real-time data processing (72 per cent), uncertainty around data lineage, timeliness and quality (66 per cent), and fragmented ownership of data (65 per cent).
Those problems are slowing agentic AI in particular. Two-thirds cite data infrastructure and data quality issues as barriers to agentic adoption, with the majority of organisations experiencing delays.
"Most organisations do not have an AI investment problem, they have a data problem," said Shaun Clowes, Chief Product Officer at Confluent. "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."
Four in five IT leaders say using enterprise data to drive AI-based systems is a top business priority. Nearly nine in 10 say data streaming platforms help unblock agentic AI progress by making data more trustworthy, contextualised and discoverable, and 94 per cent say data streaming increases, or is expected to increase, the impact of their AI investments.
Investment priorities reflect the shift. Some 88 per cent of IT leaders rank data streaming as a key priority, ahead of the 82 per cent citing AI and machine learning technologies.
"The companies making the most progress are investing not only in AI itself, but in the data foundations needed to support it," Clowes said. "Those foundations will determine which organisations can turn AI investment into business value at scale."