IBM is making one of its biggest moves in years with an $11 billion agreement to acquire Confluent, a Mountain View–based company known for building the leading real-time data streaming platform. As enterprises scramble to deploy AI applications and autonomous agents, the biggest bottleneck isn’t the models; it’s feeding them fresh, trustworthy data fast enough.
“IBM and Confluent together will enable enterprises to deploy generative and agentic AI better and faster by providing trusted communication and data flow between environments, applications and APIs,” said Arvind Krishna, chairman, president and chief executive officer, IBM. “Data is spread across public and private clouds, datacenters and countless technology providers. With the acquisition of Confluent, IBM will provide the smart data platform for enterprise IT, purpose-built for AI.”
With data scattered chaotically across clouds, datacenters and countless providers, IBM sees Confluent as the connective layer AI systems have been missing.
How Confluent fits into IBM’s AI play
Confluent’s entire value prop is “data in motion,” which means continuous streams of events and updates moving across systems in real time. Its products, including Confluent Cloud, Confluent Platform and the newer Confluent Intelligence features, are built on Apache Kafka and designed to clean, connect and govern data as it moves.
That real-time piece is becoming non-negotiable as companies move from traditional dashboards to AI agents that require constant awareness of what’s happening “right now.” IBM even pointed to IDC’s estimate that we’ll see more than a billion new logical apps by 2028. All of those apps, and the AI agents working alongside them, only function well if they’re getting clean, connected, up-to-the-second data. That’s the exact problem Confluent was built for.
Confluent has also broadened its platform beyond streaming. It now covers governance, processing, connectors and hybrid deployment options, so IBM isn’t just picking up a fast data pipeline; it’s getting a complete system for moving and managing data across environments.
As the companies described it, Confluent “excels at preparing data for AI, keeping it clean and connected across systems and applications.”
Partners, customers and market reach
Confluent brings more than 6,500 customers (including 40% of the Fortune 500) and a quickly-growing partner ecosystem across ISVs, integrators, MSPs and OEMs. IBM specifically noted that Confluent’s partner strategy mirrors its own “broad and open technology ecosystem,” making the integration feel more like a continuation than a reset.
Co-founder and CEO Jay Kreps echoed that alignment, saying, “Since its founding, Confluent has helped organizations unlock the full potential of their data… We are excited by the potential to join IBM and to accelerate our strategy with IBM’s go-to-market expertise, global scale and extensive portfolio.”
What happens next
The deal, approved by both companies’ boards and major shareholders representing about 62% of Confluent’s stock, is expected to close by mid-2026 pending regulatory review. It’s another step in IBM’s string of data- and AI-focused acquisitions, including DataStax earlier this year.
At a high level, IBM isn’t just buying a data tool; it’s buying the underlying infrastructure layer that modern AI depends on. As one Forbes analysis put it, in the world of intelligent systems, real-time data isn’t a feature. It’s the foundation everything else stands on.
Confluent’s recent leadership hires (Kamal Brar for global partners and Greg Taylor for APAC) highlight the same trend driving IBM’s acquisition. Both leaders emphasized that AI-driven businesses depend on fast, clean, real-time data. Paired with IBM’s $11 billion move, it’s clear the industry is rallying around one idea: real-time data isn’t optional anymore. It’s the backbone of modern AI.