Enterprises migrate to real-time data processing, analytics to support decision-making by AI agents, new research says
STAMFORD, Conn.–(BUSINESS WIRE)–Enterprises increasingly are adopting real-time data processing as a foundational tool for AI-enabled automation, according to new research from global AI-centered technology research and advisory firm Information Services Group (ISG).
For enterprises to stay competitive, the technology they deploy must operate at the speed of business, understanding and acting on events as they occur. Real-time data is essential for generating maximum value from AI agents.
The 2026 ISG Buyers Guides for Real-Time Data provide the rankings and ratings of 58 software providers and their products for streaming and analysis of real-time data and events. The series includes Buyers Guides covering real-time data processing, streaming data and analytics, plus application integration for real-time interoperability. The research finds that real-time data processing has evolved from a niche capability to a core component of enterprise operations as companies adopt AI agents for immediate, automated decision-making.
“For enterprises to stay competitive, the technology they deploy must operate at the speed of business, understanding and acting on events as they occur,” said Kathy Rudy, ISG partner and head of the Data, Analytics & Technology Office. “Real-time data is essential for generating maximum value from AI agents.”
Enterprises are migrating from traditional batch-oriented data processing to real-time approaches so they can respond to events as they happen. While real-time data systems have been used for years in industries with high-performance requirements, such as financial services and telecommunications, they are now becoming essential in mainstream use cases to process, analyze and share messages generated by applications, devices and agents. As AI, streaming platforms and event-driven architectures converge, real-time data processing creates new possibilities for operational responsiveness, AI-driven decision-making and more intelligent applications.
For AI agents to autonomously carry out business processes, they need to act on the latest business events and data, which requires agentic systems to be integrated with data streaming and event processing. The combination of AI with real-time data processing is only beginning, but ISG expects more than one-third of enterprises to integrate data streaming and processing with AI and generative AI inferencing by 2028 to enable real-time agentic applications.
Real-time data is made up of events, or changes of state, such as a sensor identifying a new temperature reading. Once used for point-to-point communication between applications, it is now at the heart of business processes that involve multiple applications. Application integration, which increasingly relies on APIs and agent-driven automation, is essential to carrying out these processes.
Stream processing enables applications to ingest, filter, aggregate and transform large volumes of data in motion using stream analytics, which can create visualizations and support machine learning and GenAI. This capability is becoming so central to enterprise operations that traditional data processing providers are adding support for processing of real-time data streams, while streaming and event specialists are improving their support for event data stored in data warehouses.
“To make the best use of streaming data, enterprises need to holistically manage data both in motion and at rest,” said Matt Aslett, ISG director of research, analytics and data, and author of the report. “By 2028, we expect more than three-quarters of enterprises to adopt standard information architectures that include streaming data and event processing.”
