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EAI Reliability: Why Quiet Failures Need Runtime Supervision, Not Better Dashboards

Mon., 13. April 2026 | 7 min read

Overview

A key strategic issue about Enterprise Artificial Intelligence (EAI) is whether it can keep behaving correctly once it is embedded in live workflows, exposed to new data, changing users, shifting policies, and real operational pressure. A recent article in IEEE Spectrum on EAI’s “quiet failures” captures this core risk. Systems can remain available and appear healthy while gradually becoming wrong, brittle, or misaligned. OECD’s recent work strengthens this point. There has been an increase in structured incident-reporting and a material rise in media-reported EAI incidents and hazards between 2022 and 2025; an increase from 92/month to 324/month on average.1,2,3

For CIOs and other C-level leaders, this shifts the question of EAI’s reliability from a narrow engineering concern to a governance, assurance, and operating-model issue. Our recommended posture for the next 12–24 months is to prepare and selectively invest. That is, …

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