The deployment of agentic AI in enterprises is revealing significant challenges related to data infrastructure, with many organizations facing stalled projects and abandonment due to issues like skills gaps and poor data governance. As organizations push for production, the need for improved real-time data access and data quality becomes critical to ensure the reliability and effectiveness of AI systems.
The most valuable insight for you is that the primary barrier to successfully deploying agentic AI in production isn't just about model quality or costs, but rather about addressing data infrastructure issues. Specifically, improving data quality, governance, and ensuring real-time access are crucial, as 66% of surveyed organizations cite these as significant challenges. Prioritizing investment in data streaming platforms over AI and ML solutions indicates a strategic shift towards strengthening the underlying data foundation for reliable AI operations.