AI

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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Cequence Brings Agentic AI Governance Across MCP, API, and LLM

Cequence Brings Agentic AI Governance Across MCP, API, and LLM

Agentic AI, AI Governance, Application Development, Application Security, DevSecOps, Security /

Cequence Security has released AI Discovery, API Registry, LLM Registry, and Skill Registry for AI Gateway, alongside upgraded Agent Personas that bind an AI agent’s tools, model, and APIs to a single policy-enforced job description. The approach, which Cequence calls Agentic Zero Trust, is the first to govern MCP, LLM, and API surfaces under a unified agent-bound identity. This research note examines the architectural logic, the competitive stakes, and what it means for enterprise security and development teams.

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AI Feature Adoption Gap: Half of Vertical Software Operators Are Missing the Mark

AI Feature Adoption Gap: Half of Vertical Software Operators Are Missing the Mark

AI, Application Development, Machine Learning /

Banyan Software’s inaugural AI benchmark report finds that 51% of vertical software operators see fewer than one in four customers using the AI they built. The gap between shipping AI and driving customer adoption is the defining competitive variable in vertical software. ECI Research data on engineering time and observability investment adds context to why this problem persists.

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Starburst SEIP: A Governed Data Foundation for Enterprise AI

Starburst SEIP is a Governed Data Foundation for Enterprise AI

Agentic AI, Application Development, Data Management /

Starburst has outlined a four-pillar Enterprise Intelligence Platform designed to deliver federated data access, governed semantics, and agentic AI interfaces without requiring data migration. The strategy positions Starburst against hyperscalers by targeting the governed semantic layer as its primary moat. ECI Research analysts examine what the announcement means for enterprise AI readiness and competitive dynamics in the data platform market.

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Government AI Translation: The Civic Engagement Gap Cities Are Missing

Government AI Translation: The Civic Engagement Gap Cities Are Missing

AI, Application Development, Digital Transformation, Machine Learning /

New York City’s AI agency deployments optimize internal workflows but leave real-time language access for millions of non-English-speaking residents unaddressed. Wordly’s live AI translation platform targets exactly this gap, with implications for how governments measure the true ROI of public-sector AI. ECI Research data shows internal developer tooling dominates AI investment priorities, leaving constituent-facing infrastructure behind.

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Codenotary Uses Claude AI to Secure immudb Development

Codenotary Uses Claude AI to Secure immudb Development

AI, Application Development, DevOps, DevSecOps, Open Source, Programming, Software Development /

Codenotary has been accepted into Anthropic’s Claude for OSS program, deploying AI assistance to accelerate development of immudb, its open source immutable database. The company is using Claude to detect subtle bugs, analyze concurrency issues, and generate regression tests, while maintaining mandatory human review of all code changes. The move positions Codenotary to ship faster at a moment when enterprise demand for software supply chain security infrastructure is near peak.

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Acalvio Deception Guardrails: Securing Agentic AI at Runtime

Acalvio Deception Guardrails are Securing Agentic AI at Runtime

Agentic AI, AI, AI/ML, Application Development, DevSecOps, Security /

Acalvio Technologies has launched Deception Guardrails, a capability that embeds deceptive honeytokens, decoy MCP servers, and fake credentials into AI agent workflows to detect compromise before enterprise systems are impacted. As agentic AI deployments scale, traditional input/output guardrails leave a critical detection gap that deception technology is well positioned to fill. This note examines the product logic, the security risk context, and what it means for ITDMs and developers building production AI agent infrastructure.

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AI Output Governance: The Blind Spot in Enterprise AI Strategy

AI Output Governance: The Blind Spot in Enterprise AI Strategy

AI, Application Development, DevSecOps, Enterprise IT Strategy, Machine Learning /

Enterprise AI governance frameworks have focused on access control and data inputs, leaving output quality and compliance largely unmanaged. Markup AI is making the case for enforceable content standards that apply to what AI produces, not just what goes in. ECI Research data shows governance spending is rising, but organizations need to ensure it’s solving the right problem.

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Europe's Physical AI Advantage: What Industrial Leaders Need to Know

Europe’s Physical AI Advantage & What Industrial Leaders Need to Know

Agentic AI, AI, AI Governance, AI/ML, Application Development /

Europe is leveraging decades of heavy-industry data to build physics-aware AI that American hyperscalers cannot easily replicate. Neural Concept’s $100M Series C and peers like PhysicsX signal a category forming around industrial AI with measurable ROI. ECI Research breaks down what it means for enterprise buyers and engineering teams.

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