AI Governance

Welcome and Introductions

Ken Feehan | 00:00–03:40 Okay, terrific. Dean, back to you — you were doing introductions.

Dean Peters
Yes, before we got unceremoniously dumped! Thanks, folks, for coming back. I’ve spent 20 years in product and 10 years before that in engineering — lots of work with data, AI, and natural language processing. I’ll hand this off to Dan.

Dan Torres
Hi there, folks. I’m Dan Torres, product manager for many years, from companies A to Y — Apple, Yahoo, and recently left Google to start my own project. I’ve delivered a range of products, most recently in search and AI. Glad to be here!

Jason Hare
Hey everyone, I’m Jason Hare. I’ve been doing data governance since before it was cool. I was formerly at ThoughtWorks as Subject Area Lead for Data Governance in North America. I now focus on governance frameworks and AI ethics, and I’m thrilled to be here today.

Ken Feehan
Thanks, Jason. I’m Ken Feehan, VP of Product at Productside. I’ve been here seven years, but my whole career has been product management. Dan and I worked together at Apple back in the ’90s. Productside, if you’re new here, is the rebranded 280 Group — same team, new mission to help product managers transform their impact.

This webinar is part of our Productside Expert Series — designed for the product management community. Please post your questions in the chat and connect with us on LinkedIn.

What Is AI Governance and Why It Matters

Ken Feehan | 03:41–05:30 AI governance is often defined as a collection of policies, laws, and regulations governing the use and deployment of artificial intelligence — addressing fairness, security, privacy, accountability, and transparency. Panelists, does that definition hold up?

Dan Torres | 05:31–06:00
It’s a good start, but governance is really about people — not just policies. Jason, you said something similar on a podcast recently.

Jason Hare | 06:01–08:54
Exactly. Governance refers to the people part of data management — the processes, policies, and oversight. Ethical frameworks and social norms come from people. If you stay aligned with societal norms, you’re usually on the right side of history.

Dean Peters | 08:55–09:40
I once worked in a highly regulated space and pushed back when asked to deliver faster by cutting corners. I told leadership, “I’m not willing to endanger customers or risk a free vacation from the federal government.” Governance is about protecting people and brand trust.

The Role of Product Managers in Governance

Dan Torres | 09:41–12:45 AI is an ingredient, not the final product. PMs sit at the intersection of business, users, and technology. That makes us responsible for balancing innovation with ethics. When something goes wrong — it’s not just an engineering issue, it’s a trust issue.

Dean Peters | 12:46–13:40
Exactly. Product managers should talk first to legal, compliance, and finance before speaking with engineering. Governance starts with people and perspective, not just technology.

Jason Hare | 13:41–15:11
The “people part” is vital — especially transparency and fairness. When algorithms operate like black boxes, vulnerable populations are at risk. Transparency is a moral and regulatory obligation.

Governance: Time Saver or Time Sink?

Ken Feehan | 16:44–17:38 So, is governance a time saver or a time sink for PMs?

Dean Peters
It’s a trap if you ignore it! Pay now or pay later. Governance prevents disasters before they happen.

Dan Torres
It might feel like a necessary evil, but it’s part of creating a trustworthy experience. Governance isn’t bureaucracy — it’s brand protection.

Jason Hare
Exactly. Trust is a differentiator. Governance builds credibility with users who are skeptical of AI.

Poll #1 – How Deep Is Your Company Diving into AI?

Ken Feehan | 19:09–21:02 We asked attendees: How deep is your company diving into AI? – 40% are exploring opportunities. – 21% use AI in key areas. – 13% call it a core part of their business. – 10% say it’s a primary focus.

Dean and Dan agreed these results show a typical distribution — interest growing fast, but many still hesitant.

Resources and Best Practices for PMs

Jason Hare | 22:00–25:00 At ThoughtWorks, we built an entire governance library — collateral, templates, and case studies. Product managers need accessible frameworks and language to embed governance early in design, not as an afterthought.

Dean Peters | 25:11–26:00
Regulated industries like healthcare and finance often have full compliance teams. Startups, not so much. PMs in smaller orgs must champion governance themselves — it’s part of being a responsible leader.

The Evolution of AI Governance

Dan Torres | 26:04–28:00 Governance isn’t new — it’s just evolved. Think back to Johnson & Johnson’s Tylenol recall: it forced companies to formalize crisis and ethics policies. With AI, the stakes are higher, and the pace is faster.

Jason Hare | 28:01–29:08
Right. AI governance sits on top of corporate, IT, and data governance. The hierarchy keeps expanding as risks grow. Expect the rise of the Chief AI Officer soon — with mandates around safety, compliance, and fairness.

Regional Governance and Global Impact

Dean Peters | 29:09–31:30 Regional differences shape AI policy. The **EU AI Act** emphasizes transparency; the U.S. has a patchwork of state laws like California’s CCPA. Product teams must balance innovation with compliance across markets.

Jason Hare | 31:31–33:45
Exactly. GDPR and state laws all trace back to the same eight OECD privacy principles. The U.S. enforces reactively; the EU enforces proactively — with funding tied to fines. PMs can’t wait for regulation — proactive governance is a competitive advantage.

Dan Torres | 33:46–35:24
Products live everywhere — online borders don’t exist. Whether you sell in Illinois or Italy, you need to account for privacy and fairness in your design and deployment.

Proactive Governance Using Frameworks

Dean Peters | 35:25–37:36 In our Productside AI course, we teach frameworks like **PESTEL** — Political, Economic, Social, Technological, Environmental, and Legal. It helps PMs anticipate risks instead of react to them.

We’ve also discussed creating AI nutrition labels — summarizing an AI product’s “ingredients” like bias mitigation, privacy practices, and data integrity. Transparency builds trust.

Successes and Failures in AI Products

Dan Torres | 39:05–41:33 A great example of AI done right: **Khan Academy**. They built tutoring models with transparency and guardrails, explaining mistakes and data sources. They didn’t just add AI — they designed it responsibly.

Dean Peters | 41:34–43:20
Contrast that with Air Canada’s chatbot, which gave false information about bereavement fares and caused lawsuits. Governance failed because policy didn’t keep up with the product.

Ken Feehan | 43:21–44:15
Exactly. It’s not just about what goes wrong — it’s how you respond. Governance prepares you to handle mistakes with integrity.

Poll #2 – Biggest AI Governance Challenges

Dan Torres | 44:16–45:00 We asked: What’s your biggest AI governance challenge? Most respondents said **“leadership support.”**

Dean Peters | 45:01–46:00
That’s where PMs can lead from the middle — using evidence and advocacy to influence change.

Practical Steps and Frameworks

Dean Peters | 49:02–52:00 Practical steps for PMs:
1️⃣ Read frameworks like **NIST** and **IEEE** guidelines.

2️⃣ Document model decisions and rationale.

3️⃣ Treat transparency as a product feature, not a checkbox.

Governance isn’t a roadblock — it’s insurance for innovation.

Q&A and Closing Remarks

Ken Feehan | 52:01–End We’re out of time, but thank you to our panel — **Dean Peters, Dan Torres, Jason Hare** — for your insights.

Governance is not bureaucracy; it’s responsible innovation. Be the PM who spends a few extra minutes preventing a crisis instead of cleaning up one.

Visit Productside.com/AI-Governance for resources and sign up for our AI Innovation for Product Managers course to learn more.