As enterprises move agentic AI from experimentation into production, access to timely, reliable data is becoming increasingly important. A new IDC InfoBrief sponsored by Solace suggests that the rise of AI agents is accelerating enterprise demand for real-time data infrastructure.

The 2026 State of Real-Time Data: Agentic Enterprises Are Running on Real-Time Data study surveyed 623 senior technology decision-makers at organizations with $1 billion or more in revenue across eight countries.

Real-Time Data and Agentic AI are Converging

Eighty percent (80%) of respondents said their organizations are investing in or already running AI agents, while 90% said they have increased their focus on real-time data to support their agentic AI initiatives.

Respondents identified advances in agentic AI as the single largest force reshaping their real-time data priorities, ahead of security, cost, and regulatory pressures.

The challenge is not simply developing AI agents. Forty percent (40%) of organizations cited connecting agents in real time to reliable enterprise data as a leading obstacle to putting them into production. Data quality and consistency ranked as the top technical challenge, cited by 46% of respondents.

Data Maturity and AI Outcomes

The study also found a strong association between real-time data maturity and reported AI results. Among organizations classified as emerging, 35% of AI projects delivered measurable outcomes, compared with 67% among organizations classified as leaders. AI agents deployed in production increased from 20% among emerging organizations to 59% among leaders.

Leaders were more than three times as likely to report measurable business results across the majority of their AI projects and reported average annual gains of approximately 23% in areas including speed to market, risk reduction, and the ability to sense and respond to change.

IDC's findings do not establish that real-time data maturity alone causes better AI outcomes; its maturity scoring incorporates real-time deployment, agentic AI adoption, and measurable business results. However, the correlation points to the growing importance of data architecture and operating practices in enterprise AI strategies.

Leaders were also more likely to run real-time data across most or all of their operations—76%, compared with 7% among emerging organizations—and to standardize on unified platforms rather than loosely connected tools.

Investment Continues to Grow

Ninety percent (90%) of respondents said their real-time data investments had met or exceeded expectations. Between 94% and 97% said they plan to increase spending on real-time data and agentic AI.

For industrial and other complex enterprises, the trend suggests that data quality, availability, governance, and latency are becoming increasingly important as AI systems take on more operational responsibilities.

"Organizations are citing agentic AI as the single biggest force driving their need for real-time data," said Carlos M. González, Research Manager, Event-Driven Automation and Analytics, IDC. "That reordering of priorities tells you real-time data is becoming foundational infrastructure for AI, not an analytics feature."

The broader takeaway is that as AI becomes more autonomous, real-time data is moving from a specialized data-management capability toward a foundational component of enterprise AI infrastructure.

Source: IDC InfoBrief, sponsored by Solace, "2026 State of Real-Time Data: Agentic Enterprises Are Running on Real-Time Data," Doc. # US54883526, August 2026.

Survey methodology: IDC conducted a custom survey commissioned by Solace of 623 senior technology decision-makers in June 2026. Respondents represented organizations with $1 billion or more in revenue across eight countries. Seventy-eight percent were primary decision-makers for real-time data and 71% owned their organization's AI or agentic AI initiatives. The reported margin of error was +/-3.9% at a 95% confidence level.

Source: Solace Corporation

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