AI Governance & Ethics Consulting
Look, AI governance is a mess right now. Everyone knows they need it, but most companies are winging it.
We keep seeing the same pattern. Companies rush to deploy AI tools because their competitors are doing it, then six months later they’re panicking about compliance, bias issues, or data privacy problems they never saw coming. The EU’s new AI Act isn’t helping anyone sleep better—fines can hit 6% of global revenue if you get it wrong.
The thing is, only about 25% of organizations actually have governance frameworks that do anything useful. The rest are either flying blind or drowning in consultants’ PowerPoints that look impressive but don’t translate to real operations.
What’s Actually Happening Out There
Here’s what we’re hearing from executives: AI is everywhere in their organizations now, but nobody really knows what it’s doing or whether it’s creating problems. Legal teams are freaking out about liability. IT is worried about security. HR is dealing with employees who think AI is going to replace them.
Meanwhile, the board is asking questions that nobody knows how to answer.
We’ve worked with enough companies now to see what works and what definitely doesn’t. The organizations that figure this out early get a real advantage. They can move faster on AI initiatives because they have confidence in their guardrails. The ones that don’t… well, some of them end up in regulatory hot water, and others just miss opportunities because they’re too scared to move.
How We Think About This Problem
Most consulting firms want to sell you a comprehensive framework that covers everything. That sounds great in theory, but it usually means you get something so complex that nobody uses it, or so generic that it doesn’t address your actual risks.
We start with a different question: what could go wrong in your specific business, and what would that actually cost you?
Maybe you’re in healthcare and algorithmic bias in patient care is your nightmare scenario. Or you’re in financial services and you’re worried about AI making lending decisions that violate fair lending laws. Maybe you’re a manufacturer and your concern is AI systems making operational decisions without proper oversight.
Once we understand what keeps your executives up at night, we can build something that actually addresses those concerns.
Getting Started (The Right Way, with Nantucket AI)
We spend time understanding how your company really works, not just what the org chart says. Because AI governance has to fit into your existing culture and processes, or it’ll get ignored.
Your current risk management approach matters a lot here. If you already have solid risk frameworks, we build on those instead of creating something parallel that competes for attention. If your risk management is more… aspirational… then we have bigger conversations to have.
Data is usually where things get interesting. AI needs data, but most companies have data governance that evolved organically over years. Sometimes that works fine for AI, sometimes it creates massive blind spots. We need to figure out which situation you’re in.
And honestly, we need to understand what your organization can realistically handle. There’s no point designing an elegant governance framework if your people don’t have bandwidth to implement it or your culture will reject it.
The Actual Work
Building Something That Works in Practice
Good AI governance isn’t about creating perfect policies. It’s about giving your people tools to make better decisions about AI while managing the risks that could actually hurt your business.
We’ve seen too many governance frameworks that look great on paper but fall apart when people try to use them. Usually because they’re too complex, too divorced from how work actually gets done, or they slow everything down so much that people find workarounds.
Figuring Out What Could Actually Go Wrong
Traditional risk management assumes you know what you’re dealing with. AI creates new kinds of problems that don’t fit into existing risk categories very well.
Some risks are obvious—data breaches, privacy violations, discriminatory outcomes. Others are subtler but potentially more damaging. Like AI systems that gradually drift away from their intended behavior. Or vendor relationships that create dependencies you don’t fully understand. Or organizational changes that happen faster than your governance can adapt.
We help you map out what could realistically go wrong in your environment, not just theoretical risks from white papers.
Making Sense of Regulation (Without Going Crazy)
The regulatory environment is evolving fast and it’s not getting simpler. The EU AI Act is comprehensive but complex. The US is taking a different approach. Industry-specific regulations are getting updated to address AI.
Trying to comply with everything perfectly will paralyze you. We help you figure out what actually applies to your business and build approaches that can adapt as new requirements emerge.
More importantly, we help you think about regulation as a floor, not a ceiling. Good governance often goes beyond minimum compliance because it makes your AI initiatives more effective.
Getting Your Board the Right Level of Involved
Board oversight of AI is becoming a big deal, but most boards don’t know what they should be looking at. They know they’re supposed to be asking questions about AI risk, but they’re not sure what the right questions are.
We work with boards to figure out what they should actually be overseeing versus what management should handle. Too much board involvement slows everything down. Too little creates governance gaps that regulators notice.
The Specific Stuff We Help With
- Data Strategy That Makes Sense: If your data governance is a mess, your AI governance will be too. We help you figure out whether your current data practices can support responsible AI, and what needs to change.
- Technology Choices and Vendor Decisions: Build versus buy gets complicated when AI is involved. Vendors make claims that are hard to evaluate. We provide independent analysis to help you make smart choices while managing the unique risks that come with AI partnerships.
- Making It Work With Your Organization: AI governance has to fit your company culture or it won’t stick. We design approaches that work with how your people actually make decisions, not against it.
- Ethics That Actually Matter: Responsible AI isn’t just about avoiding bad publicity, though that matters. We help you develop ethical frameworks that are specific enough to guide decisions but flexible enough to adapt as AI capabilities evolve.
How We Actually Work
We don’t show up with a predetermined solution. Every organization is different, and AI governance has to reflect that.
Usually we start by working with your leadership team to understand priorities and constraints. Then we bring together people from different parts of your organization because AI touches everything—IT, legal, operations, customer service, HR.
We create documentation that people can actually use. Not binders that sit on shelves, but tools that help your teams make better decisions about AI.
And we stick around during implementation because that’s where you discover what actually works and what needs adjustment.
The goal isn’t perfect governance from day one. It’s building something that works for your organization right now and can evolve as your AI use matures.
Smart governance doesn’t slow down innovation. It creates the confidence your organization needs to move forward on AI without creating unnecessary risks.