The accelerated enterprise adoption of AI is transforming how businesses manage infrastructure, data, and governance. As AI moves from pilot to production, organizations are encountering new demands for performance, scalability, and security, often within complex hybrid IT environments. Meanwhile, the pressure to realize measurable outcomes from AI initiatives is forcing a reevaluation of existing architectures and operational frameworks.

Success in enterprise AI requires more than powerful models—it demands intelligent data infrastructure. That means breaking down data silos, integrating AI pipelines with distributed environments, and embedding governance from the start. Leaders are also tackling data gravity, regulatory friction, and architectural sprawl with unified, adaptable platforms that support hybrid AI strategies.

In our latest Market Brief, Enterprise AI Evolution: Maximizing Data Value in a Hybrid World, developed in partnership with NetApp, Futurum Research explores how forward-thinking enterprises are modernizing their infrastructure to support scalable, secure, and high-performance AI operations. Drawing on research and CIO insights, the report examines:

• Why AI infrastructure decisions now involve cross-functional teams and shorter refresh cycles
• How Retrieval-Augmented Generation (RAG) and vector databases are reshaping enterprise data access
• What organizations must do to manage data movement, gravity, and sovereignty across regions
• How unified control planes and intelligent tiering enhance governance, security, and scalability

If you’re working to unlock real AI value across hybrid environments, download your copy of Enterprise AI Evolution: Maximizing Data Value in a Hybrid World today.