When the Coder Is an Unrated Component
AI coding agents now modify production software with no aviation-grade assurance framework, a gap regulated buyers cannot ignore.
Find here all our blog posts tagged with: AI Governance.
When AI Stops Advising and Starts Operating the Grid
As AI shifts from analytics to closed-loop control in energy and industrial systems, validation and human-override design become the real governance test.
Off the Grid, Off the Record: AI's Energy Attribution Problem
As AI data centers bypass public grids with private power, buyers lose built-in metering and now need independent energy attribution to satisfy disclosure obligations.
The Trial Matching Black Box
Agentic AI that extracts and standardizes EHR data for oncology trial matching is becoming clinical trial infrastructure with no validation framework behind it.
The Architecture Question Behind AI Agents in Air Traffic Control
As AI agents are proposed to manage rising air traffic, the unresolved decision is architecture and assurance, not model capability.
The Exemption Your CDS Tool Is Standing On Is Under Review
FDA's Section 3060 review of clinical decision support flexibilities means hospitals should stop assuming their AI-driven CDS tools sit outside device regulation.
Clinical AI's Financial Case Is Made. Its Audit Trail Isn't.
Drug discovery and trial AI are proving their financial return faster than sponsors are building the validation records to defend that work at inspection.
Plant-Floor AI Agents Are Closing the Loop Faster Than Governance Can Follow
Industrial AI agents are moving from advisory copilots to closed-loop actuation, and the audit infrastructure to govern them is still catching up.
The Safety Wearable Is Now a Regulated Decision-Maker
Biometric and proximity safety wearables in energy and industrial plants are starting to meet the legal definition of automated decision-making technology.
The Grid Is Now Trusting AI's Own Numbers
AI vendors claim they can unlock grid capacity and cut power volatility, but utilities are making capital decisions on unaudited performance figures.
The 72/10 Problem: Why Industrial AI Stalls Before It Scales
Most manufacturers have deployed AI, but only a tenth scale it, and the gap is governance, not algorithms.
Insuring the Unflown: Aviation AI Has No Loss History
As AI moves into cockpits, MRO, and eVTOL, insurers are underwriting aviation risk with no actuarial base, forcing buyers to substitute governance evidence for loss data.
The Benchmarking Gap FDA Hasn't Closed
Nature Medicine's new framework for evaluating generalist medical AI outpaces FDA's device-modification tools, leaving capability-tier governance to buyers.
The Physical AI Business Case Has a Regulatory Hole
Industrial buyers are being pitched humanoid and physical AI capability faster than the safety classification and liability frameworks needed to deploy it responsibly.
The Governance Gap FDA's Rulemaking Won't Reach
FDA is still asking questions about generative AI in medicine while health systems already run it inside clinical workflows unmonitored.
In Physical AI Deals, Telemetry Rights Are the Real Asset
Energy and industrial AI transactions increasingly hinge on whether sensor and telemetry data remain usable after closing, not on the model itself.
The Money Is Ahead of the Rulebook in Trial AI
Capital is flooding into AI for clinical trial conduct while regulators have yet to define what governs it, leaving sponsors exposed.
Two Safety Layers, One Machine: The Governance Gap in Physical AI
Vendor-native AI safety standards and established machine-safety codes are emerging in parallel, and industrial buyers must decide which one actually carries liability.
