Plug and Play’s new pulse survey finds three-quarters of large enterprises have AI in production, but half aren’t consistently measuring its value. ECI Research analysis identifies the data, governance, and capacity constraints that separate AI deployment from AI return. The real competition is now over measurement infrastructure, not model capability.
Enterprise AI Is in Production But Half Can’t Measure ROI Read More »
The EU AI Act’s binding rules for AI in consumer finance set an accountability standard that will inevitably reach capital markets. Firms relying on fragmented documents and manual approval chains can’t produce the audit trail regulators will require. Tokenization offers one structural path forward — but the window to build proactively is closing.
EU AI Act: What Capital Markets Firms Must Do Now Read More »
Accountability consultant Linda Galindo is calling out the growing use of AI to write performance reviews, warnings, and termination notices. With 26% of employees suspecting AI-authored feedback, the credibility of these communications is collapsing. ECI Research data shows organizations are investing in AI governance, but the harder question is where AI should not speak on behalf of a person.
The Accountability Gap Leaders Can’t Ignore Read More »
The Linux Foundation has launched the Tokenomics Foundation, backed by 30 founding members, to establish vendor-neutral standards for measuring AI costs and ROI. The foundation’s roadmap includes token cost telemetry, cost-to-serve frameworks, and practitioner certification. For enterprises scaling AI spend without clear attribution, this initiative arrives at a critical moment.
Linux Foundation Launches Tokenomics Foundation to Standardize AI ROI Read More »
Enterprise AI governance has advanced on access logging and provenance tracking, but most programs still lack enforcement at the content output layer. Markup AI calls this “compliance theater.” ECI Research data shows nearly two-thirds of practitioners already see elevated risk from AI-assisted development, making the case for output-layer controls more urgent.
Why the Output Layer Is the Real Risk in AI Content Governance Read More »
The EU AI Act’s transparency requirements are now enforceable, and most enterprises are not structurally ready. Kore.ai’s CSO warns of “governance debt” — AI initiatives that stall not because the technology fails, but because the oversight infrastructure was never built. ECI Research breaks down what this means for ITDMs and engineering teams.
EU AI Act Transparency Rules: The Governance Debt Risk for Enterprises Read More »
Acceldata has launched AI Observability as a native capability of its xLake Data & AI Platform, connecting agent traces directly to data quality, lineage, and pipeline health across hybrid environments. The announcement targets a gap no existing AI observability tool fully closes: tracing an agent failure back to the data that caused it. For enterprises running workloads across both cloud and on-premises infrastructure, this positions data governance as an enabler of AI deployment rather than a constraint on it.
Governing Agents Across Hybrid Data Read More »
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.
The Enterprise AI Governance Gap Is a Data Problem First Read More »
Meta’s content licensing deal with Newsmax is a preview of a two-tier AI training data market. Large publishers can negotiate; most independent creators cannot. ECI Research examines what this means for enterprise risk, developer supply chains, and the future of AI content rights.
Meta-Newsmax Deal Exposes AI Content Licensing Gap Read More »
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.
Cequence Brings Agentic AI Governance Across MCP, API, and LLM Read More »