He added, “IBM already has the pieces of the puzzle required to build and train AI models; Confluent provides the connective tissue to saturate those models with continuous live data from across an organization’s entire operation, regardless of the source. This capability should pave the road ahead for more complex AI agents and applications that will be able to react to data in real time.”
He also pointed out that the company is playing the long game with this acquisition, which is its largest in recent history. “IBM effectively positions itself proactively to compete against the AI-native big data companies like Snowflake and Databricks, who are all racing towards the same ‘holy grail’ of realizing AI agents that can consume, process, and react to real-time data within the context of their clients’ trained models and operating parameters,” he said, adding that IBM is betting that a full-stack vertical AI platform, watsonx, will be more appealing to enterprise buyers than a composable solution comprised of various independent components.
The move, he noted, also complements previous acquisitions such as the $34.5 billion acquisition of Red Hat and the more recent $6.4 billion acquisition of Hashicorp, all of which are built upon dominant open source standards including Linux, Terraform/Vault, and Kafka. This allows IBM to offer a stand-alone vertical, hybrid cloud strategy with full-stack AI capabilities apart from the ERP vendor space and the point solutions currently available.
