AI momentum is growing. No surprise there, given AI’s role in driving tangible business outcomes, from improving productivity to creating new revenue streams. And businesses that recognize data as the linchpin of their AI strategies are on the path to unlocking success.
As easy access to reliable, real-time data takes center stage—especially in the world of GenAI—a whopping majority of IT leaders see data streaming platforms as key to translating the potential of AI into measurable business value.
of IT leaders say data streaming platforms will be increasingly used to feed AI systems with real-time, contextual, and trustworthy data.
A closer look into AI momentum reveals widespread adoption and experimentation across multiple domains—but varying levels of maturity. With technologies like GenAI driving a surge in demand for continuous data access across businesses, our survey findings reinforce how data is the foundation of AI success.
This strong recognition of enterprise data's importance highlights a critical connection: AI systems in a business context are only as good as the data that powers them and how quickly and reliably data can be delivered.
of IT leaders emphasize the use of enterprise data as a business imperative.
of IT leaders agree that AI systems must leverage enterprise data to realize their true potential.
of IT leaders cite DSPs enabling use of enterprise data to drive AI-based systems.
While AI offers tremendous opportunities for businesses, enterprises are too often held back by disconnected systems that fail to deliver the right data, in the right format, at the exact moment it’s needed.
Our survey findings show that every organization faces its own mix of challenges—with the majority of IT leaders highlighting three or more challenges.
Failure to address these challenges will result in operational bottlenecks and increased complexity, undermining the potential benefits of AI.
The good news? Data streaming platforms are accelerating AI adoption by allowing businesses to tap into continuously enriched, trustworthy data streams—enabling them to quickly build and scale AI applications.
Organizations clearly recognize that DSPs help them directly tackle the data challenges that constrain AI operationalization, particularly in areas related to data access, data quality, and data governance.
Notably, the specific benefits attributed to DSPs correspond directly with the core requirements for building trustworthy AI systems that deliver consistent business value.
