IBM and Confluent: Designing the Middleware Layer for Agentic AI

The Emerging ‘Nervous System’ Of Agentic Value Streams

IBM’s acquisition of Confluent for about $11 billion, subject to regulatory approvals, represents a strategically important step in the evolution of enterprise AI, data, and cloud platforms. From PAC’s perspective, this deal has the potential to position IBM to design a foundational middleware layer for agentic AI, effectively the ‘nervous system’ that connects data, applications, and autonomous AI agents.

Confluent’s core strength lies in real-time data streaming, governance, and intent-driven architectures. When combined with IBM’s existing software, automation, and hybrid cloud capabilities, this creates the basis for a more comprehensive, end-to-end data platform. The objective is not simply better data integration, but continuous, policy-aware data flows that allow AI agents to sense, decide, and act across complex IT environments.

An Intent-Driven Architecture Strategy Reflects Changing Enterprise Demand

Over the past decade, organizations have modernized front-end customer interactions through digital channels, personalization, and AI-enabled engagement. The next wave of transformation will reshape the operational core: back-end systems, logistics networks, manufacturing, and supply chains. As front-end and back-end transformations converge, enterprises are turning to IT providers for help with two critical challenges: accelerating data flows across applications and APIs, and ensuring that data accessed by AI is clean, trusted, and contextually linked in real time.

Agentic AI requires organizations to rethink their respective competitive advantages. As foundation models become more commoditized, sustainable differentiation will no longer come from the LLM or SLM models themselves. Instead, it will depend on how effectively organizations combine agentic AI with proprietary data to redesign products, services, and business processes. This places data in motion at the center of future value propositions.

PAC Expects Significant Implications For Both Software And Data Architecture

Enterprise software will increasingly resemble a real-time operating system in which a middleware layer orchestrates data, events, and processes across systems of record and systems of engagement. In parallel, database architectures must evolve beyond static, siloed data-at-rest models toward continuous data flows across hybrid and cloud-native environments.

PAC views IBM’s acquisition of Confluent as a smart move in the race to address emerging demand for agentic AI. It will strengthen IBM’s ability to manage data in motion, enable end-to-end integration of applications, analytics, and AI agents, and open the door to new, outcome-driven value propositions. As Red Hat did for cloud computing, Confluent, rooted in open source and supported by a large developer community, could play a defining role in making enterprise AI work at scale.

To read more about PAC’s vision for modern software and data architecture, visit our research portal, where you will also find our report regarding the IBM and Confluent deal: IBM and Confluent: Designing a Middleware Layer for Agentic AI.