Agentic AI marks a shift in how AI is used: it no longer just supports decisions - it acts inside live business operations.
This report, from Arlington Research, quantifies the trust gap between what organizations need for production AI and what most can deliver today.
Trustworthy agentic AI depends on three foundations:
- Live data that reflects what’s happening now, not as of your last copy
- The right data, enriched with shared business meaning and context
- Guardrails built into access and tools, so actions remain governed and explainable
Without these foundations, AI action becomes fragile: hard to scale, hard to govern, and hard to defend.
In this report, you’ll learn:
- Where production AI trust breaks first (live data, right data, guardrails)
- Why semantics and provenance become gating factors when AI moves into execution
- What changes architecturally to support agentic AI across distributed enterprise environments
Download the AI Trust Gap Report
