IBM Bought a ‘Nervous System’ for $11 Billion

IBM’s decision to buy real-time data streaming company Confluent for $11 billion signals a shift in the AI race. Tech giants believe that controlling real-time data is as important as building powerful models. 

This acquisition comes in a year marked by similar moves. Salesforce purchased Informatica, while services firm Genpact acquired XponentL Data to expand its data and AI capabilities. These deals indicate that enterprise vendors want greater control over data feeding AI systems. 

IBM said its acquisition will combine its AI and automation software with Confluent’s real-time data streaming capabilities, helping enterprises to connect, process, and govern data across environments. The companies said this will support AI agents and applications that require access to trusted, real-time data.

Confluent, built on the open source platform Apache Kafka, offers data streaming, connectors, governance, stream processing, and deployment options across Confluent Cloud, Confluent Platform, WarpStream, and Confluent Private Cloud. It claims to work with more than 6,500 clients, including over 40% of the Fortune 500.

IBM said the deal aligns with its hybrid cloud and open-source strategy, following earlier acquisitions such as Red Hat and HashiCorp. 

Andrew Humphreys, senior director analyst at Gartner, told AIM that IBM wants to position itself to become the platform through which enterprises move, process and govern data for emerging AI workloads. He said Salesforce signalled a similar intent with its Informatica acquisition, placing IBM in direct competition with Salesforce and Oracle as companies seek to own the data infrastructure that feeds AI.

Humphreys said the acquisition gives IBM more than 50% share in the event broker market. He noted that alternatives such as Redpanda, AWS MSK, Google MSK and Azure Event Hub remain strong competitors as cloud providers bundle these services directly into their platforms.“Clients who do not have a multi-cloud strategy are more likely to choose IBM Confluent than they were likely to do so prior to the acquisition,” he said. 

Michael Ni, VP and principal analyst at Constellation Research, told AIM that Confluent fills a structural gap for IBM by providing the “nervous system” needed for its AI and hybrid-cloud strategy. He said IBM already had strong capabilities in metadata, governance and AI lifecycle management, but lacked a unified streaming backbone. 

“Confluent fills that gap with portable, governed data-in-motion infrastructure that complements IBM’s hybrid-first strategy, making it an alternative to hyperscalers for enterprises seeking vendor-neutral streaming and enterprise AI governance,” Ni said.

Humphreys added that IBM has long competed with Confluent through its IBM MQ product, which is central to many event-driven architectures. He said, “IBM MQ and Kafka solve different problems,” giving IBM a chance to offer a broader portfolio. 

How does it help IBM?

In a blog post, IBM CEO Arvind Krishna wrote that companies increasingly want to run operations in real time as transactions, supply chains and fraud detection happen within milliseconds. He said AI models are “only as strong as the signals feeding them,” while digital workers and autonomous workflows require continuous, reliable data streams.

Ni said the deal helps IBM compete more directly with leading cloud companies. “You can’t compete with AWS, Google, or Databricks without a real-time nervous system that provides the streaming context that AI, agents, and automated decisions require to support autonomous workflows and agentic architectures,” he said.

Humphreys said both companies are positioning the deal as a step towards enabling more real-time data access for AI agents. But he warned that claims that everything will become event-driven should be treated cautiously, noting that “most AI agents still rely on static data snapshots” and that adoption will take time.

Salesforce is making a similar push

Salesforce recently expanded its Data 360 portfolio by adding Informatica to address one of the main challenges in enterprise AI adoption, which is unreliable results stemming from inconsistent, siloed, or low-quality data.

The company said the combination of Data 360, MuleSoft, and now Informatica creates a unified data foundation that provides AI systems with the context they need to operate accurately across enterprise applications.

Informatica brings deeper metadata intelligence, data lineage, governance, and quality controls into Salesforce’s data stack. The latter said the platform helps establish shared meaning for business entities across ERP, finance, supply chain, HR, and commerce systems, thereby reducing ambiguity for AI models.

“AI is only as good as the understanding behind it, and that understanding comes from context,” said Rahul Auradkar, EVP and general manager for Data 360 and AI Foundations at Salesforce. He said integrating Informatica with MuleSoft’s real-time connectivity gives customers a foundation of trusted enterprise context that strengthens every AI, automation, and analytics outcome.

Salesforce said these capabilities will help reduce hallucinations, support safer execution, and strengthen applications across Agentforce, Tableau, and the broader Salesforce platform.