← Atlas Theme · spans 2 topics

Defective data and weak security trap AI pilots in perpetual pre-production.

The vast majority of generative AI and agent initiatives remain trapped in pre-production experiments due to poor data quality, security compliance failures, and growing corporate disillusionment.

2
Topics it spans
4
Findings citing it
Evidence window
The convergence

The same conclusion keeps arriving from across the workspace's research — 2 topics independently instantiate this theme. Filter the evidence by where it came from:

How companies are using autonomous AI agents
Enterprise AI Agent Security: The "Agentic Identity Crisis" and the Governance Vacuum of 2026

This highlights how systemic governance and security failures ultimately force organizations to pull agents out of active production.

How companies are using autonomous AI agents
SMB AI Agent Adoption: Racing Forward but Stuck in Experimentation

Without clean, unified database architectures, small and medium businesses find their agent pilots locked in perpetual experimentation.

B2B Buyer Criteria Shift for AI
Beyond the Hype: The 2026 Shift to Semantic Foundations, Explainable AI, and LLM Observability

Defective and fragmented data structures prevent models from generating reliable outputs, trapping AI initiatives in a trough of disillusionment.

How companies are using autonomous AI agents
The Enterprise AI Agent Production Gap: The "80/31" Divergence and the 88% Pilot Bottleneck in 2026

Unresolved security, data quality, and integration bottlenecks leave nearly ninety percent of enterprise AI agent pilots unable to launch into production.