Responsible AI Governance — for people accountable for what happens next.
Walk in with a problem. Walk out with a decision framework aligned with NIST AI RMF, EU AI Act transparency requirements, and ISO 42001 monitoring principles — plus a bias checklist and one specific move on your calendar. Not a lecture. Not a policy template. A working session for the people actually responsible for AI inside real organizations.
What is AI governance, actually?
Not the policy binder that lives in a SharePoint folder nobody opens. Not the compliance checkbox your legal team sends around once a year.
AI governance is the living system of decisions, accountability, and oversight that keeps AI from quietly going wrong — after it's deployed, when nobody's watching, when the edge cases start showing up in the data.
Three frameworks define how serious organizations govern AI right now. NIST AI RMF gives you the lifecycle structure: Govern, Map, Measure, Manage. ISO 42001 gives you the management system: policy, roles, monitoring, continual improvement. The EU AI Act gives you the legal floor: risk tiers, transparency obligations, bias audits, and human oversight for high-risk systems.
Most organizations know these frameworks exist. Almost none have translated them into something their actual teams can use on a Tuesday. That's the gap this session fills.
It's the answer to: Who owns this output? What gets logged? What happens when it's wrong? And who's accountable when it affects a real person?
Governance is not:
- ✕ A 200-page AI policy document
- ✕ A one-time ethics training
- ✕ Blocking AI until someone figures it out
- ✕ A technology problem
- ✕ Someone else's job
Governance is:
- ✓ A short, usable decision filter your team can apply today
- ✓ Clear accountability before something goes wrong
- ✓ A logging and monitoring habit, not a project
- ✓ The language to talk to legal, security, and the C-suite
- ✓ A practice — not a policy
Six modules. One spine.
A working session, not a tour of frameworks. We move fast, apply everything live, and you leave with something in your hand.
Open — The shadow AI problem
Why governance keeps failing. What's already happening in your org right now. The gap between strategy and Sharon.
Module 1 — What IS governance, actually
Not the policy binder. The living system of decisions, accountability, and oversight. How NIST AI RMF, ISO 42001, and the EU AI Act fit together — and what they actually require of your team in plain language.
Module 2 — Where bias actually lives
Spoiler: almost never in the model. What "fairness" means when there are six definitions — and they conflict mathematically. How to audit for what actually matters.
Module 3 — The three-question frame
Test any AI project in under five minutes. Aligned with NIST AI RMF GOVERN 1.1 — what data goes in, who owns the output, what gets logged. The filter your team can apply to actual decisions without calling a meeting.
Breakout + debrief — Apply it live
Small groups. Real scenario from your industry. You apply the three-question frame and the bias checklist to something that actually keeps someone in the room up at night.
Module 4 — Your Monday move
One specific action on your calendar before we close. The 30/60/90 framework for what governance actually looks like over time. What to say to legal, security, and the C-suite — and what to write down.
Close + Q&A
Open questions. What comes next. How to bring this to your team.
Not a certificate. A plan.
Everything below is filled out for your context, not handed to you as a blank template.
The Decision Framework
A short, usable filter aligned with NIST AI RMF GOVERN and MANAGE functions. What data goes in, who owns the output, what gets logged, what doesn't.
The Bias Audit Checklist
Aligned with EU AI Act Article 10 data governance requirements. Where bias actually lives in your systems — and how to check for it without a data science degree.
The Three-Question Frame
Aligned with NIST AI RMF GOVERN 1.1. Test any AI project in under five minutes — tools already deployed and ones being evaluated right now.
Governance Language for the C-Suite
What to ask, what to require, what to write down. Including how to position ISO 42001 and NIST AI RMF to legal, security, and the board — without sounding like you're stalling.
The 30/60/90 Implementation Frame
Aligned with ISO 42001 continual improvement requirements. What governance actually looks like over time, sized to your org, resources, and current risk surface.
One Monday Move
One specific action on your calendar before you leave the session. Not homework. A commitment made in the room, aligned with the NIST AI RMF MAP function.
If your job description includes the word responsible — you're in the right room.
- ✓ Leaders and senior ICs in regulated environments — healthcare, energy, public sector, financial services
- ✓ Project managers, BAs, and product owners who keep getting pulled into AI conversations
- ✓ HR, legal, and security partners who need to know what to ask — and what to require
- ✓ Compliance professionals tired of "AI ethics" being abstract
- ✓ Policymakers and program leads responsible for AI inside public systems
You do not need a technical background. You need to care about what happens when AI makes a bad decision inside your organization.
Format & logistics
Built from inside the systems we're talking about.
Karin Collinsworth spent 28 years inside some of the most complex regulated systems in the country — healthcare, public health, county government, energy — learning one pattern that repeats at every scale: organizations fail for the same reasons. Misaligned foundations. Ungoverned complexity. People running on cortisol instead of capacity.
She was among the first to bring practical AI into King County's business analysis practice and the PMI community. She has led enterprise Agile transformation, Epic EHR implementations, application portfolio rationalization across 1,250+ systems, and AI governance work in environments where bad systems have real consequences — audits, investigations, and the people the systems are supposed to serve.
Trained in HIPAA compliance, CJIS, and network security across regulated government and healthcare environments. Deep practitioner fluency in NIST AI RMF, ISO 42001, and EU AI Act requirements — and how to translate all three into something operational teams can actually use. Currently pursuing IAPP AI Governance Professional (AIGP) certification.
She teaches this material because she has spent three decades living the problem — not studying it from the outside.
More about Karin →Private sessions for groups of ten or more.
Open enrollment works for individuals. For teams, a private session is the better fit — industry-specific examples, your actual AI tools and workflows in the room, custom dates, and net-30 invoicing or PO accepted.
Private sessions aren't run through the LinkedIn event. Start with a 30-minute discovery call to scope the engagement.
Book a discovery call
30 minutes. We'll figure out whether a private session makes sense and what it would look like for your team.
Meet with Karin →The work happens in the room.
No replay. 20 seats. The next session fills faster than you'd expect — mostly because someone forwarded this to someone who forwarded it to someone who is tired of "AI ethics" being theoretical.