Agentic AI Needs a New Data Foundation
Access the Gartner® report on why context-aware data management is critical to enabling scalable, accurate, and governed AI agents.
Agentic AI is reshaping how organizations build and deploy intelligent systems, moving from static models to autonomous agents that continuously reason, act, and adapt.
But most data platforms weren’t designed for this shift.
In this Gartner® report, Emerging Tech: AI Vendor Race: Agentic AI Needs Context-Aware Data Management, you’ll learn why traditional data architectures fall short and what leading organizations are doing instead.
“Agentic systems must scale with data growth, context-aware platforms use automated governance and progressive discovery to keep AI agents accurate, efficient, safe, and compliant.”
Source: Gartner, Emerging Tech: AI Vendor Race: Agentic AI Needs Context-Aware Data Management, 2026
What You’ll Learn
- Why traditional databases and data platforms are insufficient for agentic AI use cases
- How context-aware data platforms unify structured, unstructured, and multimodal data
- The role of semantic layers and knowledge graphs in enabling AI reasoning
- Why progressive data discovery is essential for accuracy and efficiency
- How embedded governance and policy enforcement reduce AI risk and ensure compliance
Why This Matters Now
AI agents don’t just retrieve data. They interpret, reason, and act on it. Without the right data foundation, organizations face:
- Incomplete or inaccurate AI outputs
- Increased compliance and security risks
- Slower time to value from AI investments
Context-aware data platforms are emerging as the critical layer to bridge this gap, enabling AI systems to operate with the context, trust, and control required at scale.
Who Should Read This Report
- Chief Data Officers (CDOs)
- Chief Information Officers (CIOs)
- Chief Technology Officers (CTOs)
- Data and AI Platform Leaders
- Product and Engineering Leaders building AI-powered applications
