IBM’s recent acquisitions of Red Hat, HashiCorp, and its planned purchase of Confluent reflect a deliberate strategy to build the infrastructure required for enterprise AI. According to IBM’s Sanil Nambiar, AI depends on consistent hybrid cloud runtimes (Red Hat), programmable and automated infrastructure (HashiCorp), and real-time, trustworthy data (Confluent). Without these foundations, AI cannot function effectively.

Nambiar argues that modern, software-defined networks have become too complex for humans to manage alone, overwhelmed by fragmented data, escalating tool sophistication, and a widening skills gap that makes veteran “tribal knowledge” hard to transfer. Trust, he says, is the biggest barrier to AI adoption in networking, since errors can cause costly outages. To address this, IBM launched IBM Network Intelligence, a “network-native” AI solution that combines time-series foundation models with reasoning large language models. This architecture enables AI agents to detect subtle warning patterns, collapse incident response times, and deliver accurate, trustworthy insights for real-world network operations.

Learn more from The New Stack about AI infrastructure and IBM’s approach:

IBM’s Confluent Acquisition Is About Event-Driven AI

Project infragraph: IBM’s Real-Time Model for Infrastructure Assets

IBM’s Mellea Tackles Open Source AI’s Hidden Weakness

Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Human Cognition Can’t Keep Up with Modern Networks. What’s Next?

The New Stack Podcast