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Thinking about AI governance

Field notes on where AI governance matters most, what the rules actually say, and what responsible deployment looks like sector by sector. Written by Davor C.

ElorynFederal government7 min read

Eloryn in the federal government: governing AI that acts, not just advises

Ottawa wrote sensible rules for automated decisions years ago. Agentic AI — systems that take actions, not just recommend them — is about to test whether those rules hold in practice.

Davor C. · June 2026

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ElorynProvincial government6 min read

Not just Ottawa: AI governance at the provincial level

Health, education, social services, licensing — most government decisions that touch a Canadian's daily life are provincial. The privacy and human-rights rules there are real, specific, and already in force.

Davor C. · June 2026

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ElorynHealthcare6 min read

AI in healthcare needs more than a model — it needs a record

A model that suggests a diagnosis is impressive. A system you can trust near a patient is a different thing entirely — and the difference is almost all governance.

Davor C. · June 2026

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ElorynFinancial services7 min read

What model risk means for AI in finance

Banks and insurers have governed models they don't fully understand for decades. AI doesn't need a new philosophy of oversight so much as an old one, applied honestly and at speed.

Davor C. · June 2026

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ElorynPrivate sector6 min read

Governance is the on-ramp, not the brake

Outside the heavily regulated industries, no one is forcing the issue — which is exactly why getting AI governance right is a competitive advantage rather than a compliance chore.

Davor C. · June 2026

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More writing

The full collection

These five sector essays are part of a longer collection — including pieces on sovereign AI, adoption principles, and the general case for governing agents — published on the author's professional site.

Read the full collection at davor.cukeric.com