IBM acquires Confluent in $11 billion all-cash deal to power real-time AI data pipelines

IBM is making one of its largest software bets in years. The company confirmed Monday that it is acquiring data-streaming platform Confluent in an all-cash deal valued at $11 billion, a move that places real-time data infrastructure at the center of IBM’s AI ambitions.

The transaction values Confluent at $31 per share, a 33% premium to Friday’s close. Investors reacted quickly. Confluent shares jumped 26% in premarket trading. IBM stock slid about 1%, reflecting near-term concerns around deal size and dilution rather than strategic intent.

“IBM and Confluent, Inc., the data streaming pioneer, today announced they have entered into a definitive agreement under which IBM will acquire all of the issued and outstanding common shares of Confluent for $31 per share, representing an enterprise value of $11 billion,” IBM said in a news release.

Confluent sits at the heart of modern data flows. Built by the original creators of Apache Kafka, the platform moves event data across enterprises in real time, covering everything from bank transactions and online shopping activity to factory sensors and application logs. These streams feed analytics systems, automation software, and machine-learning models that rely on fresh data to make decisions.

From Red Hat to Kafka: IBM’s $11B Confluent Deal Targets the Heart of AI Data Flow

IBM sees that capability as a missing piece. The company has spent years reshaping itself around hybrid cloud and AI, most visibly through its $34 billion acquisition of Red Hat in 2019. Chief executive Arvind Krishna framed the Confluent deal as the next logical step.

“With the acquisition of Confluent, IBM will provide the smart data platform for enterprise IT, purpose-built for AI,” Krishna said in a statement.

The timing reflects a broader shift inside large companies. Global data volumes continue to surge, and IBM projects total data generation will more than double by 2028. AI systems no longer rely on static datasets pulled once a day. They need continuous streams that can support live inference, fraud detection, predictive maintenance, and autonomous workflows.

“This is about owning the data layer AI depends on,” one analyst said shortly after the announcement.

Confluent brings scale to that vision. The company counts more than 6,500 customers across finance, retail, manufacturing, and tech. Many already run Kafka as the connective tissue between on-prem systems, cloud infrastructure, and analytics tools. Folding that capability into IBM’s WatsonX AI platform and Red Hat OpenShift gives IBM deeper reach into production data pipelines that competitors often access only at the application layer.

The deal follows a pattern under Krishna’s leadership. IBM has focused less on splashy consumer technology and more on infrastructure that large enterprises already trust. Recent moves include the $6.4 billion HashiCorp acquisition earlier this year and prior purchases such as DataStax, all pointing toward control over how data moves, gets secured, and feeds AI workloads.

Confluent’s public-market journey made it a natural target. The company went public in 2021, steadily grew its customer base, and expanded its view of the total addressable market to $100 billion as AI adoption accelerated. Market conditions put pressure on its valuation, even as demand for real-time data continued to rise across industries.

Competition in this layer of the stack has intensified. Salesforce announced its intent to acquire Informatica for $8 billion earlier this year. Hyperscalers continue to pour money into native streaming tools. Snowflake and Databricks have circled similar capabilities to strengthen their own platforms. IBM’s hybrid focus stands apart, especially for banks, governments, and regulated businesses that hesitate to place all critical data inside a single public cloud.

Regulatory review still lies ahead. The companies expect the transaction to close by the middle of 2026, subject to approvals in the U.S. and abroad. Antitrust agencies have shown growing interest in AI-adjacent consolidation, and infrastructure deals tend to draw close inspection.

Market reaction reflects the tradeoff. Confluent shareholders lock in a significant premium. IBM investors weigh near-term costs against long-term control of a foundational AI layer.

This acquisition sends a clear signal. AI leadership no longer hinges solely on models. Control over live data flows increasingly defines who wins enterprise deals. IBM is betting that owning the pipes matters as much as building the engines that run on top of them.