About

Why This Exists

As a practicing COO in a regulated healthcare organization, I've led AI deployments in production environments where compliance, risk, and real financial outcomes are non-negotiable. Like many of you, I've seen too many AI initiatives stall in endless pilots, drained by vendor hype, insufficient governance, or unclear paths to measurable P&L impact.

COOs in midsize regulated companies – healthcare, financial services, insurance, and similar sectors – are under pressure to deliver workflow improvements without exposing the organization to brand, operational, or regulatory risks. Yet reliable, vendor-neutral guidance is scarce: most resources are either too theoretical, heavily sponsored, or focused on technology rather than operations.

COO AI Playbook exists to close that gap. It is a standards-driven, operator-focused resource library of practical playbooks, evaluation frameworks, ROI models, and anonymized field reports designed specifically for COOs who want to operationalize AI safely and see results traceable to their profit and loss statement.

This is independent and operator-led: I curate and validate the content, informed by peer feedback, but retain editorial judgment. It is sponsor-free, with no hidden agendas. Tools or approaches are mentioned only if they have proven effective in production settings.

Core Principles

Independence and Integrity.
- No sponsors, no affiliate deals, no pay-to-play placements.
- No sales funnels, urgency tactics, or scarcity gimmicks.
- No consulting pitches or disguised monetization – this is not a pipeline for services.
- Content is published to serve the operator community, not to drive revenue.
Evidence and Safety First.
- Recommendations are anchored in real outcomes (anonymized where needed) or clearly tagged for confidence level.
- Human-in-the-loop controls, observability, rollback plans, and compliance considerations are foundational.
Plain, Practical Focus.
- Written from one COO to another: direct, practical, and focused on workflows, metrics, and risk management.
Community-Informed, Editorially Curated.
- Feedback, counter-examples, and stories from fellow operators are welcomed and often incorporated (anonymously by default).
- I lead the curation to maintain quality, consistency, and independence..

About the Author

Michael Moshiri is a practicing COO who co-founded and leads a national healthcare organization since 2018. He has deployed AI systems in regulated production environments, navigating compliance, risk, and scaling challenges firsthand.

This playbook shares those hard-won standards to benefit the broader operator community. Views expressed are personal.

Contact me here.

License Summary

Content is free for internal company use: adapt checklists, run models, or incorporate into documents.

Commercial republication or derivative products require written permission (almost always granted for legitimate operator needs – just ask).

Refer to the License page for more details.