Articles on governed AI
Thinking on AI governance, department ownership, and keeping enterprise AI auditable. New here? Start with the overview: AI Governance for Regulated Industries.
The Doorman Fallacy Is Coming for AI Governance
AI makes the visible work cheaper. The governance problem is everything around that work: judgment, ownership, review, and the record that proves a decision was made responsibly.
Read postAI governance in life science companies
The fastest AI adoption in pharma and biotech is internal, not in the product. It runs regulated records, trade secrets, and personal data through tools nobody is tracking.
Read postAI Governance in the Back Office of Banks and Broker-Dealers
Financial firms are adopting AI fastest inside compliance, risk, finance, and HR, where the records and controls are already regulated. This is how to put that internal AI use under governance before an examiner asks for the evidence.
Read postAI Governance in the Aerospace Back Office: Where the Audit Trail Goes Missing
Aerospace and aviation companies are pulling AI into their engineering, quality, and compliance back office. The governance gap shows up in the records those teams produce, well before it would ever show up in the avionics they ship.
Read postWhy AI in the Utility Back Office Needs the Same Audit Trail as Everything Else
Nuclear and electric utilities run on documented quality programs and audit evidence. Putting AI under governance means every internal action stays attributable, policy-controlled, and recorded.
Read postAI Governance for the Defense Contractor Back Office
Defense and government contractors are adopting AI faster than they can govern it, and the riskiest exposure is internal. This is a look at how administrative AI use collides with CUI rules, export control, and CMMC.
Read postThe danger of LLMs
Our foot is on the gas but we can't see over the steering wheel.
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