https://vert-ai.com/insights Production-grade AI, data platforms, and decision science. Field notes from Vert AI. en-CA Mon, 20 Apr 2026 18:26:09 GMT https://vert-ai.com/insights/enterprise-ai-fails-in-production https://vert-ai.com/insights/enterprise-ai-fails-in-production Gartner, MIT, and every enterprise survey confirm it. The bottleneck is engineering, data architecture, and operational readiness, not model selection. What implementation-led teams do differently. Sun, 01 Mar 2026 12:00:00 GMT https://vert-ai.com/insights/semantic-layer-undervalued-asset https://vert-ai.com/insights/semantic-layer-undervalued-asset Only 7% of enterprises operate a governed semantic foundation. Without one, every model and dashboard trains on a different version of the truth. Why the semantic layer is the highest-ROI infrastructure investment most data teams skip. Sun, 01 Feb 2026 12:00:00 GMT https://vert-ai.com/insights/growth-metrics-are-lying https://vert-ai.com/insights/growth-metrics-are-lying Revenue is vanity. ROAS is a platform fiction. CAC ignores cohort decay. Most growth measurement frameworks quietly reward capital destruction. A decision-science approach to measuring what actually compounds. Thu, 01 Jan 2026 12:00:00 GMT https://vert-ai.com/insights/agentic-ai-production-failures https://vert-ai.com/insights/agentic-ai-production-failures Gartner predicts 40% of enterprise apps will use agentic AI by end of 2026. Most will not survive contact with production data. The governance, evaluation, and operational gaps that separate demos from deployed systems. Mon, 01 Dec 2025 12:00:00 GMT https://vert-ai.com/insights/data-not-ready-for-ai https://vert-ai.com/insights/data-not-ready-for-ai Before investing in models, run this diagnostic. Five structural signals, from pipeline fragility to semantic drift, that predict whether your data layer will enable AI or undermine it. Sat, 01 Nov 2025 12:00:00 GMT https://vert-ai.com/insights/hidden-cost-layer-ai-roi https://vert-ai.com/insights/hidden-cost-layer-ai-roi Change management, data preparation, integration work, and operational overhead account for up to 60% of total AI investment. Almost none of it appears in the business case. How to build an honest cost model. Wed, 01 Oct 2025 12:00:00 GMT https://vert-ai.com/insights/model-to-production-engineering-gap https://vert-ai.com/insights/model-to-production-engineering-gap A model in a notebook is not a system. Monitoring, versioning, fallback logic, and operational scaffolding separate a demo from a deployed capability, and most ML teams are not equipped to close that gap. Mon, 01 Sep 2025 12:00:00 GMT https://vert-ai.com/insights/decision-layers-missing-architecture https://vert-ai.com/insights/decision-layers-missing-architecture Most companies have dashboards. Very few have decision systems. The architectural pattern that connects predictive models, business rules, and operational workflows into systems that generate action, not reports. Fri, 01 Aug 2025 12:00:00 GMT https://vert-ai.com/insights/etl-to-ai-native-data-stack https://vert-ai.com/insights/etl-to-ai-native-data-stack The modern data stack is dead. The AI-native data stack, real-time, context-rich, and semantically governed, is what production AI requires. An architectural blueprint for data teams building for agentic systems. Tue, 01 Jul 2025 12:00:00 GMT https://vert-ai.com/insights/capital-allocation-data-problem https://vert-ai.com/insights/capital-allocation-data-problem Where to spend, where to cut, where to scale. These are measurement questions, not strategy questions. Companies that treat capital allocation as a data engineering problem outperform those that do not. Sun, 01 Jun 2025 12:00:00 GMT