Holding Space for Your AI Principles: Why This Conversation Can’t Be Rushed
A practical guide to moving from corporate theater to genuine co-creation.
Before we even begin, I want to invite you to arrive in this moment. Take a deep breath. Notice your body, the screen in front of you, these words.
Now I have a question for you: How do you feel about AI right now?
There’s no right answer. Maybe you’re curious. Excited. Anxious. Overwhelmed. Hopeful. Skeptical. All of the above.
Just notice. And name it.
The Tension Is Everywhere
If you’re feeling multiple, contradictory things about AI, you’re not alone.
And if you’re leading a team or organization? That complexity multiplies exponentially.
Your engineering team might be thrilled about the capabilities. Your legal team might be terrified about the risks. Your customers might be asking questions you don’t have answers to yet. Your board might be pressuring you to “do something with AI” without clarity on what that means.
Take another breath. Feel that tension.
Here’s what I need you to understand: These tensions are not problems to solve. They are creative tensions to hold.
The dilemmas are real:
Fairness vs. Accuracy
Efficiency vs. Equity
Innovation vs. Safety
Freedom vs. Control
…
There’s rarely a clean answer. There’s usually a third way—a path that honors both sides of the tension.
And in a landscape where the technology is evolving daily, where regulations are still taking shape, where no one has all the answers yet, your values and principles become your compass.
Good principles don’t give you a rulebook. They give you a way to navigate when the rules don’t exist yet.
Why This Matters More Than You Think
I know “defining our AI principles” can sound like corporate theater. Another document no one will read. Another initiative that goes nowhere.
But done right, this work is actually an invitation to something profound:
To bring meaning and connection back to how we build and use technology.
To redefine what work means for humans in an AI-augmented world.
To create an alternative to the extractive, profit-maximizing-at-all-costs playbook that’s broken so much of what we value.
To discover new kinds of creativity—new ways of measuring what matters, new purposes, new ways of being.
When I frame it that way, the whole process shifts. It becomes about being guardians of what we believe in.
And honestly? That’s beautiful work.
You Don’t Have to Start from Scratch
Here’s the good news: you’re not the first organization to wrestle with this.
For years, a global community of researchers, ethicists, technologists, and policymakers has been doing the hard work of anticipating AI’s harms and articulating ethical guidelines.
Organizations like the European Commission, the OECD, and NIST have created robust frameworks.
Companies like Google, Microsoft, and Akbank, alongside mission-driven organizations like Khan Academy and Common Sense Media, have publicly shared their principles.
You can learn from all of them.
Through this collective work, a set of common principles has emerged:
Human Agency & Oversight – Humans should remain in control; AI should augment, not replace human decision-making
Privacy & Data Governance – Personal data should be protected and used responsibly
Data Quality & Integrity – AI systems should be built on accurate, complete, and reliable data
Technical Robustness & Safety – AI systems should be secure, reliable, and resilient
Transparency – People should understand how AI systems work and how decisions are made
Diversity, Non-discrimination & Fairness – AI should not perpetuate bias or create unjust outcomes
Accountability – There should be clear responsibility when things go wrong
Contestability & Redress – People should be able to challenge AI decisions and seek remedies when harmed
Societal & Environmental Wellbeing – AI should benefit society and minimize environmental harm
Informed Participation & Literacy – Stakeholders should understand AI systems and participate meaningfully in decisions about their use
Multi-stakeholder & Adaptive Governance – Diverse voices should be involved in AI governance, with approaches that evolve as the technology changes
These aren’t just abstract ideals. They’re practical guideposts that organizations around the world are using to make real decisions.
→ [See how leading organizations define these principles (Benchmarks slide deck)]
The question isn’t whether these principles matter. The question is: Which ones matter most to you? And what do they actually mean in your context?
The Problem Most Organizations Face
Most organizations approach this as a compliance exercise.
They schedule a one-hour meeting. Someone presents a slide deck of “industry best practices.” The team picks five principles from a list. Maybe they wordsmith a bit. Then they move on.
Three months later, no one remembers what the principles were. Six months later, when a contentious decision comes up, no one thinks to reference them. A year later, they’re buried in a SharePoint folder no one can find.
This is what happens when you treat principles as a checklist instead of a conversation.
Here’s the truth that most organizations don’t want to hear:
Defining your AI principles is not a task you complete. It’s a creative process you facilitate.
And like all creative processes, it requires two things most organizations are reluctant to give:
Time. And space.
What “Holding Space” Actually Looks Like
This phrase—”holding space”—might sound soft or fuzzy. But it’s actually quite specific.
Holding space means:
Creating a container where people can be honest. Where the product manager can say “I’m worried we’re moving too fast” without being labeled a blocker. Where the data scientist can say “I don’t actually know if this model is fair” without fear of judgment.
Facilitating, not dictating. This isn’t about the CEO announcing what the principles are. It’s about drawing out the wisdom that already exists in your organization—across functions, across levels, across perspectives.
Listening deeply. Not just hearing words, but understanding what people actually care about. What they’re afraid of. What they hope for.
Allowing for iteration. Recognizing that your first draft won’t be perfect. That you’ll learn as you go. That principles should evolve as your understanding deepens.
Making it real, not performative. Connecting these principles to actual decisions, actual trade-offs, actual moments where you have to choose what matters most.
This kind of work can’t happen in a rushed hour-long meeting.
It needs psychological safety. It needs skilled facilitation.
And honestly? It might need multiple sessions.
A Simple Way to Begin: 5 Questions
If you’re ready to start this conversation with your team, here’s a simple framework.
Block 90 minutes on the calendar. Get the right people in the room—not just leadership, but people from across your organization who will actually be building, deploying, and being affected by AI.
And work through these five questions together:
1. Our Relationship with AI
As a team, what emotions come up when we think about AI?
Don’t skip this step. Don’t go straight to “the business case.” Start with the human reality.
Are people excited? Anxious? Curious? Overwhelmed? Skeptical? Hopeful?
Name the feelings. Write them down. Let them be complex and contradictory.
This isn’t therapy. It’s context. You can’t have a meaningful conversation about principles if you don’t understand the emotional landscape you’re operating in.
2. Our Hopes
What is the most positive outcome we hope to achieve with AI?
What becomes possible that wasn’t possible before?
What problems could we solve? What value could we create? What could we do better, faster, or more effectively?
Let people dream a little here. This is the “north star” energy—the pull toward what we want to build.
3. Our Fears
What is the harm we are most committed to preventing?
If everything went wrong, what would that look like?
What’s the outcome that would make us say, “We should never have done this”?
What’s our red line—the boundary we absolutely will not cross?
This is the “guard rail” energy—the recognition of what we need to protect against.
4. Our Non-Negotiables
Looking at our existing organizational values, which one is most critical to uphold as we adopt AI?
Most organizations already have stated values. (If you don’t, that’s a different conversation.)
Which of those values feels most at risk in an AI context? Which one has to guide everything else?
This connects your AI principles to your organizational identity. It prevents the AI conversation from feeling disconnected from who you already are.
5. Our North Star Principles
If we could choose only 3-5 principles to guide our AI work, which would they be and why?
Go back to that common list:
Human Agency & Oversight
Privacy & Data Governance
Data Quality & Integrity
Technical Robustness & Safety
Transparency
Diversity, Non-discrimination & Fairness
Accountability
Contestability & Redress
Societal & Environmental Wellbeing
Informed Participation & Literacy
Multi-stakeholder & Adaptive Governance
You can’t prioritize everything equally. So what rises to the top for your organization, in your context?
And more importantly: Why? What makes fairness more critical than transparency for you? Or vice versa?
The “why” is where the real work happens.
→ [Download the Identify & Define Worksheet to capture your team’s responses]
What You’ll Walk Away With
After this 90-minute conversation, you won’t have a finished document.
But you’ll have something more valuable:
A shared understanding of where your team is emotionally and intellectually around AI.
Language for what you’re trying to achieve and what you’re trying to prevent.
A shortlist of principles that actually resonate with your people—not because they came from a consultant’s slide deck, but because they emerged from your conversation.
Momentum toward making this real.
What Comes Next
This first conversation is just the beginning. Here’s what I recommend:
1. Document what emerged.
Write it up. Share it back to the team. Ask: “Did I capture this right? What’s missing?”
2. Define your terms.
“Fairness” means different things to different people. So does “transparency.” So does “accountability.”
What do these words actually mean in your context? Get specific.
3. Test them against real decisions.
Don’t let your principles live in a document. The next time you’re making a decision about an AI project, explicitly ask: “Based on our commitment to [principle], what should we do?”
4. Create accountability mechanisms.
Who is responsible for ensuring these principles are upheld? How will you know if you’re living up to them? What happens when you’re not?
5. Revisit regularly.
Set a reminder for six months from now. Gather the team again. Ask: Are these still the right principles? What have we learned? What needs to evolve?
This Is the Real Work
I know this might feel slow in a world that’s moving impossibly fast.
Every day there’s a new model, a new capability, a new competitor doing something with AI that makes you feel like you’re falling behind.
The pressure to move quickly is real.
But here’s what I’ve seen again and again: Organizations that rush this part end up having to redo it later—usually after something goes wrong.
A model that produces biased outcomes. A product that erodes customer trust. A PR crisis that could have been avoided. A regulatory penalty that blindsides leadership.
The organizations that take time to do this work right—to hold space for genuine conversation, to honor the creative tensions, to let principles emerge from dialogue rather than be imposed from above—those are the ones building AI that actually reflects their values.
And when things get hard (because they will get hard), those principles become the anchor that keeps them grounded.
You Don’t Need to Be Perfect. You Just Need to Start.
You don’t have to solve everything today.
You don’t need the perfect framework or the perfect facilitator or the perfect conditions.
You just need to gather your team, block 90 minutes, and ask these five questions.
Create space for people to be honest. Listen deeply. Write down what matters.
The rest will unfold from there.
Take one more breath.
The conversation begins now.
Ready to take the next step?
If you’re a leader who wants support facilitating this conversation—or if you’re looking for a more structured framework to guide the deeper work of defining and operationalizing your principles—I’d love to help.
→ Book a 15-minute conversation to explore what this could look like for your organization.
→ Explore workshops designed to guide teams through this process.
→ Connect with me to discuss how your organization is navigating these questions.
What tensions are you holding right now? I genuinely want to know. Reach out—let’s talk.