AI production

The Enterprise AI Governance Gap Is a Data Problem First

The Enterprise AI Governance Gap Is a Data Problem First

AI, AI Governance, Application Development, Data Management /

Most enterprises are running AI on ungoverned data foundations, and the gap between ambition and operational reality is widening. Quest Software’s Global Field CTO Sue Lane joins ECI Research’s Paul Nashawaty to explain why data quality, semantic layers, and portable governance frameworks determine whether AI investments deliver in production. The governance gap isn’t a maturity problem waiting to close — it’s an active risk posture demanding immediate structural attention.

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Why Enterprise AI Fails Without an Orchestration Layer

Why Enterprise AI Fails Without an Orchestration Layer

Agentic AI, AI, Application Development, Enterprise IT Strategy /

Enterprise AI pilots are failing not because the models are inadequate, but because organizations lack a unified orchestration and governance layer. Druid AI CEO Joe Kim argues that without a single control plane measuring every agent’s actions and defining human handoff points, AI accountability is effectively impossible. ECI Research data on multi-agent adoption and autonomous agent confidence gaps support the case.

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