Last week, I watched a buddy of mine (a fellow small business owner) demo her tech stack. Eleven AI tools on regular rotation and about 1,000 more she’s dabbling with or considering. Her monthly spend is over $400.
But, and this is a big but, she felt “kinda bad” about using any of them. There was a lot of “should I?” and “I wouldn’t want to be seen using them.” When I asked about her AI principles, she looked at me like I’d asked for her blood type.
She’s in good company (or maybe better to say she has a LOT of it).
I’ve had the same conversation with C-suite executives running companies with thousands of employees and with realtors running solo. They gave me the same blank stare. The same awkward pause. The same sudden interest in checking their phones.
88% of companies now use AI in at least one business function. But only one-third have begun scaling it across the enterprise, and just 6% qualify as “high performers” seeing significant business impact.
That’s a lot of money spent on tools that aren’t delivering, and I’d argue it’s because most organizations skipped a step. They bought the tools before they figured out what they actually believed about AI.
The problem isn't that companies aren't using AI. It's that they skipped the part where they decided what they believe about it.
Cards on the Table: How My Principles Play Out
I use AI to help write this blog, my newsletters and other content. I use it to create images, too. (Never the ones of my dogs, though, because they simply cannot be improved!)
But the ideas, frameworks, examples, and point of view? That’s me. That’s the first 20%.
AI helps me challenge my thinking, draft sections and frame ideas. Nothing goes out the door without serious review and editing from me or my team. That’s the final 20%. (Not sure what I mean by 20%? I’m shocked…lol. Read about that HERE.)
I also work with AI using projects trained on my thinking, my tone, my perspectives. So even when AI suggests ways to frame something, it sounds like me. Think of it less like hiring a ghostwriter and more like having a thought partner who’s read everything I’ve ever written and somehow still wants to work with me.
I don’t say this defensively or with embarrassment. My principles make it clear: AI is a thinking partner for me, not a ghostwriter. I’m transparent about how I use it because hiding it would conflict with what I believe…with my AI principles.
And that’s what principles actually do. They turn “should I?” into “here’s how I do.”
What Are AI Principles, Anyway?
AI principles are your foundational beliefs about AI’s role in your work or organization. They answer questions like: What is AI actually for here? How should humans and AI work together? What’s off-limits?
They’re part of what I call the 3 Ps:
❤️ Principles are what you believe.
🚓 Policy is what’s allowed and what isn’t.
📙 Playbook is how you actually do the work.
Most organizations start with tools and hope strategy catches up. (It doesn’t catch up. It just creates confusion that compounds quarterly.)
Why This Matters for Everyone
AI principles matter at every level, but for different reasons.
If you lead a large organization, you’re probably already seeing the chaos. 78% of employees are using AI tools you haven’t approved, and 51% report conflicting guidance on when and how to use AI. That’s hardly “adoption.”
That’s everyone doing their own thing and hoping nobody asks too many questions.
If you run a small business or work solo, nobody’s making you do this work. No compliance department. No governance committee scheduling meetings about meetings. No accountant giving you disapproving looks when the credit card bill comes (let me know if you want to borrow my hubby/accountant – he’s an expert in this area).
Which means every tool that promises to “save you 10 hours a week” gets a yes, and before long you’re spending more time managing AI tools than they’re saving you. (Ask me how I know.)
If you’re one person inside a bigger organization, your company may not have articulated its AI principles. Or they exist in a policy document nobody reads, nested three levels deep in SharePoint, last updated in 2023.
Knowing your own principles helps you navigate when the official guidance is vague, outdated, or silent.
Without that framework, you get AI guilt. That nagging feeling every time you use ChatGPT to draft an email: Should I be doing this? Does this make me lazy? What if someone finds out?
Here’s some more – personally heartbreaking – food for thought: that guilt also isn’t distributed equally.
Research from Harvard Business School found that women are more likely to avoid AI tools because they’re worried about the potential costs of relying on computer-generated information, particularly if it’s perceived as unethical or “cheating.”
When organizations stay silent on principles, they’re not being neutral. They’re creating an environment where some people charge ahead like a bull in a china shop while others hold back, second-guessing every use.
Principles replace that guilt with intention. They give people permission to use AI well instead of wondering if they’re doing something wrong.
The data backs this up: companies without a formal AI strategy report a 37% success rate with AI initiatives. Those with one? 80%.
"AI guilt is a symptom of missing principles. Define what AI is for in your work, and the 'should I?' questions answer themselves."
The Three Areas Your AI Principles Need to Cover
Strong principles cover three areas. Miss one and you’ve got gaps, and people will fill those gaps with their own assumptions. (Usually the worst-case-scenario kind.)
1. Strategic Principles: What is AI actually for here?
These define purpose. Before you can write principles about how to use AI, you need clarity on why you’re using it at all.
- For organizations, this might sound like: “AI serves our client promise” or “We automate the mechanical to make room for the meaningful.“
- For individuals, it’s more personal: “I use AI to think bigger, not to think less” or “AI handles the parts of my job I’ve outgrown.”
2. Cultural Principles: What does this mean for our people?
This is where you address the thing everyone’s thinking but nobody wants to say out loud. Whether it’s your team wondering if AI is coming for their jobs, or you personally trying to figure out where AI fits in your professional identity.
This is also where AI guilt lives. Without cultural principles, people feel like they’re cheating when they use AI. They hesitate to mention it because they’re not sure if it undermines their credibility.
- For organizations: “AI won’t be our edge. Our people will.” or “We invest in capability, not just software.”
- For individuals: “AI literacy is part of my professional development.” or “Using AI well is a skill, not a shortcut.”
It’s worth noting, by the way, that only 7.5% of employees receive substantial AI training. The people winning with AI aren’t just using the tools; they’re investing in building real capability.
3. Operational Principles: How do we do this responsibly?
These cover accountability, transparency, and ethics. Not as afterthoughts, but as core operating beliefs. This is the category that lets you talk openly about AI use without feeling like you’re confessing something.
- For organizations: “AI gets responsibility. Humans own accountability.” and “Transparency. Always.”
- For individuals: “I review everything AI produces before it goes anywhere.” and “I’m honest about when and how I use AI.”
How to Write Your AI Principles
You don’t need a committee or a six-month process. (Though I know that’s how most organizations approach anything with the word “principles” in it.)
Start with four questions:
- What is AI actually for in my work?
- What do I believe about AI’s relationship to my expertise?
- How do I want to handle transparency?
- Where are the lines I won’t cross?
Write three to five statements that capture your answers. Then test them.
Pick a recent AI decision you made or avoided. Does your principle tell you anything about whether it was the right call?
One warning: if your principle could apply to any business anywhere, it’s not specific enough.
- “We use AI responsibly” means nothing. (It’s the corporate equivalent of “thoughts and prayers.”)
- “AI gets responsibility, humans own accountability” means something
Want to see where you stand?
I’ve built an assessment that gauges your alignment across all three Ps: principles, policy and playbook. Takes five minutes and gives you a clear picture of what to work on first.
If you want to go deeper, there’s a coaching chatbot that walks you through developing your own 3 Ps step by step.
This is the foundation of my keynote Aligning for AI. The organizations and individuals who win with AI won’t necessarily be the ones who adopted fastest or spent the most. They’ll be the ones who got clear on what they believed first.
About Julie: A Hall of Fame AI keynote speaker, tech founder, and innovation strategist, Julie works with associations, real estate professionals, and corporate sales teams to help them lead smarter, sell more, serve better, and save time with AI. She delivers highly actionable and engaging keynotes on becoming AI-empowered, leading in an AI-driven world, and transforming work and customer relationships.
AI Principles FAQ: Common Questions About AI Guilt, Policy and Use
Principles are beliefs. Policy is rules. You need principles first because they're what make the rules make sense. Without them, policies feel arbitrary and people work around them.
The 20-60-20 rule is a framework for collaborating with AI effectively. You invest the first 20% setting direction (defining goals, audience, and context). AI handles the middle 60% (drafting, outlining, and generating options). You return for the final 20% to edit, validate, and personalize the output. This ensures AI amplifies your thinking rather than replacing it.
Maybe. Check whether your company's principles actually guide decisions or just sit in a document somewhere. If they're vague or you can't recall them without looking, developing your own personal principles helps you navigate day-to-day choices. Your principles should align with your organization's, but they can be more specific to your role.
Define your own. You'll be making AI decisions regardless of whether official guidance exists. Personal principles give you a framework when the company line is vague, outdated, or silent. They also position you well if leadership eventually asks someone to help shape organizational principles. (Might as well be you.)
Rarely. Good principles outlast specific tools. ChatGPT, Copilot, whatever comes next: your principles should still apply. If you're rewriting them every time a new tool launches, they're not principles. They're reactions.
Because you don't have a clear framework for when it's appropriate. Guilt thrives in ambiguity. Define what AI is for in your work, and the guilt starts to fade.
