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Real-Time Data Maturity Becomes the Primary Driver of AI Success

Real-Time Data Maturity Becomes the Primary Driver of AI Success

Organizations that integrate real-time data into their core workflows are three times more likely to achieve measurable business results from their AI projects, according to a new IDC study of 623 senior technology decision-makers at billion-dollar enterprises.

The report, sponsored by the Ottawa-based platform Solace, highlights a fundamental shift: agentic AI has evolved from an experimental curiosity into an operational dependency. As AI models become ubiquitous across industries, the competitive advantage is no longer found in the models themselves, but in the speed and reliability of the data feeding them. Leaders in real-time data maturity report 23% average annual gains in speed-to-market and risk reduction.

Despite the clear benefits, implementation remains a significant hurdle. Roughly 40% of organizations identified the connection of AI agents to trusted, real-time enterprise data as their most difficult challenge, often proving more complex than building the agents themselves. Success appears tied to operational discipline rather than sheer budget, with top-tier firms standardizing on unified data platforms rather than relying on fragmented toolsets. As investment in these systems accelerates, 97% of surveyed companies plan to increase spending on real-time data infrastructure over the coming year.

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