Empowering Leaders with Generative AI: A Framework for Navigating the Future

By Dr. Shane Snipes

Ever tried explaining artificial intelligence to someone who’s still figuring out how to mute themselves on Zoom? It’s a bit like trying to teach a dog to send an email—both fun to watch and equally frustrating. But here’s the thing: AI isn’t just the latest tech buzzword. It’s shaping industries, transforming education, and rewiring how we approach business strategy. If you’re not paying attention, you’ll end up as that metaphorical dog, watching the digital transformation unfold while struggling to keep up.

But don’t worry—I’ve got your back. Let’s talk about the Generative AI Literacy Framework, a tool designed to help educators, business owners, and leaders like you make sense of this new landscape. It’s not just about understanding AI; it’s about using it responsibly, effectively, and, dare I say, a little bit humorously.

The Problem: Why AI Literacy Matters

Right now, AI is creeping into almost every part of our lives—your business, your classroom, even your Netflix recommendations. But let’s be honest: most of us aren’t AI experts, and that’s okay. The problem isn’t that you don’t know how AI works; it’s that without some basic understanding, you might miss out on huge opportunities—or worse, make a costly mistake. Remember when someone said, “Hey, let’s invest in Blockbuster”? Yeah, that kind of mistake.

AI Literacy is about more than just knowing the jargon; it’s about mastering the fundamentals so you can use AI to your advantage rather than fear it like it’s the next Terminator movie. You don’t need to be an engineer to get it, but you do need a framework to help you understand how to work with AI tools, trust their outputs, and know when to call them out on their nonsense.

The Framework: Breaking It Down

So, what’s in this Generative AI Literacy Framework I’m talking about? It’s a roadmap for getting you from "AI rookie" to "AI-savvy leader." It’s not magic, but it’ll sure feel like it when you start seeing the results.

1. Input Understanding and Contextualization

Here’s the thing with AI: what you get out of it depends on what you put into it. Think of it like asking for directions. If you say, “Take me somewhere,” AI’s going to spit out a hundred options, none of which are helpful. But if you say, “Take me to the coffee shop at 7th and Broadway,” you’ll get exactly what you need.

For leaders and educators: This is where crafting specific prompts comes into play. Whether it’s AI generating ideas for a new marketing campaign or assisting students in their research, the clearer your input, the better the output. If you can’t explain what you want, AI can’t give it to you.

2. Verification of AI Outputs

Now, here’s the dirty little secret: AI isn’t always right. In fact, sometimes it’s completely wrong—like, "flat-earth conspiracy" wrong. That’s where verification comes in. You can’t take AI’s word as gospel; you’ve got to fact-check it. Cross-reference its suggestions, compare its findings, and make sure it’s not just making stuff up (it happens more than you’d think).

In business and education: This step is crucial. Whether you’re using AI to analyze customer data or generate content, don’t just accept what it gives you. Verify the facts. Remember, AI is only as smart as the data it’s been trained on.

3. Bias Detection and Evaluation

AI isn’t neutral. It’s trained on data—data that’s full of human bias. That means it can, and often does, make recommendations or assumptions that are skewed. Your job is to spot these biases before they affect your decisions.

For business owners: Imagine you’re using AI to help with hiring, and it consistently recommends candidates who fit a specific demographic profile. That’s a red flag. You need to understand the biases AI might have inherited from its training data and address them.

For educators: This is a great opportunity to teach students about bias in technology. It’s not just about teaching them to use AI but also helping them think critically about the results they get.

4. Structured Evaluation with the C.R.I.T.I.C. Model

Here’s where we bring in some structure. The C.R.I.T.I.C. Model gives you a framework for evaluating AI outputs systematically. It stands for:

• Clarity: Is the information understandable, or is it buried under jargon?
• Relevance: Does it actually answer the question, or did it take a detour?
• Integrity: Is it truthful? Did you verify the facts?
• Thoroughness: Does it cover all the bases, or are there gaps?
• Impartiality: Is there bias you need to be aware of?
• Coherence: Does it make sense, or does it sound like a robot had a meltdown?

Use case: Whether you’re evaluating an AI-generated customer report or a student’s AI-assisted research paper, apply the C.R.I.T.I.C. model to make sure it’s as solid as it should be.

5. Application of Knowledge

This is where the magic happens. AI can spit out data, ideas, or strategies, but it’s still your job to apply that knowledge in a way that makes sense for your situation. AI isn’t the end-all solution; it’s a tool in your toolbox. Combine its insights with your experience and expertise to make informed decisions.

For business owners: If AI tells you that customer demand is shifting, it’s up to you to decide how to pivot your strategy. AI can guide you, but it can’t replace your leadership.

For educators: Help students synthesize AI-generated information with their own research. Encourage them to blend machine insights with their personal understanding of the subject.

6. Ethical Use of AI

AI comes with ethical responsibilities. Just because you can automate something doesn’t mean you should. We need to think about privacy, fairness, and transparency. As leaders, it’s our job to ensure we’re using AI in ways that are responsible and aligned with our values.

In practice: Make sure your use of AI aligns with ethical guidelines. Whether you’re automating marketing emails or using AI to grade papers, transparency and fairness are non-negotiable.

Why This Framework Works

What makes this framework powerful is that it’s not about making you an AI expert; it’s about making you AI-literate. You’ll understand how to use the tools, how to verify their outputs, and how to spot biases. More importantly, you’ll have a framework to think critically about AI and its role in your business or classroom.

The Generative AI Literacy Framework equips you to lead with confidence in a rapidly evolving tech landscape. It’s not about replacing human insight with machine intelligence—it’s about combining the two to get the best of both worlds

What’s Next?

If you’re ready to dive into AI and explore how this framework can work for you, start by assessing where AI fits into your current strategy. Whether you're an educator looking to integrate AI tools into your curriculum or a business leader seeking to optimize operations, this framework will guide you toward making smart, ethical decisions in an AI-driven world.

Let’s make sure we’re not just keeping up with the changes but leading them.

About Dr. Shane Snipes

Dr. Shane Snipes is an educator, researcher, and advocate for responsible technology use. He helps leaders and organizations navigate the intersection of AI, education, and business, ensuring they stay ahead of the curve while maintaining ethical integrity.