Why enterprise AI keeps stalling — and how data streaming could unlock it
A New Stack article argues that enterprise AI adoption is stalling not because of model quality but due to data infrastructure problems. The piece highlights that many organizations struggle to get AI models into production because they lack real-time, reliable data pipelines. Data streaming, particularly through platforms like Confluent, is presented as a solution to provide the continuous, high-quality data feeds that AI agents need to function effectively. The article suggests that without addressing data infrastructure, even the best models will fail to deliver business value. It emphasizes that streaming data can enable AI agents to react to events in real time, improve decision-making, and scale across the enterprise. The post is sponsored by Confluent, but the core argument—that data infrastructure is the bottleneck for enterprise AI—is supported by industry trends.
Developers must prioritize data infrastructure to make AI agents production-ready.