AI Literacy: More Than Just Playing with ChatGPT
And the 5 Focal Points That'll Help You Get There
Artificial intelligence is everywhere. From generating social media captions to analyzing massive data sets, AI has become a tool that professionals across industries rely on.
But knowing how to open ChatGPT and ask a question isn’t the same as having AI literacy. Just like using a calculator doesn’t make you a mathematician, playing around with AI doesn’t mean you truly understand its potential—or its limits.
So, what does AI literacy really mean?
1 and 2. Understanding What’s Under the Hood, and Picking the Right Tool for the Job
The first step in AI literacy isn’t just using AI—it’s understanding how it works.
No, you don’t need to become a machine-learning engineer, but having a basic grasp of how these models are trained, where they get their data, and how different fine-tuning methods affect their capabilities is critical.
For example, many people assume all AI models are the same. But a model fine-tuned for data analysis will handle complex spreadsheets far better than one designed for casual conversation.
Likewise, if you’re writing fiction, you might have better results with a model trained specifically for storytelling rather than a general-purpose chatbot.
AI literacy means knowing these differences and choosing the right tool for the right job.
3. AI Is an Iterative Process, Not a One-and-Done Solution
AI-generated content isn’t perfect. It shouldn’t be treated as a final draft, just as no professional writer submits their first draft without revisions.
AI literacy involves understanding that your role isn’t just to accept what AI generates—it’s to refine, fact-check, and improve it.
If you’re using AI to generate business insights, ask yourself:
Does this analysis actually align with my business goals?
Is the AI making assumptions based on incomplete data?
How can I challenge or refine its conclusions?
The best AI users don’t just take what’s given; they push AI further with follow-up prompts, tweaks, and critical thinking.
4. AI Use Is Personal and Industry-Specific
A marketer, a software engineer, and a police department analyst will all use AI differently. Their AI literacy depends on their existing expertise and how well they integrate AI into their workflow.
Consider this: A journalist might use AI to summarize a breaking news event, while a lawyer might use it to sift through case law.
Their success with AI isn’t just about the tool—it’s about how well they align AI’s capabilities with their industry’s demands and their own critical thinking.
This means that simply "learning AI" in a general sense isn’t enough. True literacy comes from applying AI meaningfully within your field.
5. Knowing AI’s Weaknesses Is as Important as Knowing Its Strengths
One of the biggest mistakes people make with AI is assuming it always gets things right. In reality, AI has plenty of blind spots.
It struggles with real-time events unless connected to a live data source.
It doesn’t "think"—it predicts the most statistically likely response.
It can misinterpret numbers, especially in URLs or non-standard formats.
A great example: If you’re using AI to generate news headlines from existing URLs—as I do for my newsletter on a daily basis—it might read a URL and misinterpret "$1.5 billion" as "$15 billion."
That’s because it doesn’t recognize decimal points in the URL structure. AI literacy means knowing this behavior exists in the algorithm and catching it before it becomes a potentially costly mistake.
The Bottom Line: AI Literacy Is About More Than Just Access
If you sit down and play with ChatGPT for a few minutes, you might feel like you "get it."
True AI literacy, however, is built over time through deeper learning, practical application, and constant iteration.
To recap, AI literacy means:
Understanding how AI is built—the data, the training process, and the fine-tuning that makes one model better than another for a given task.
Knowing AI’s capabilities and choosing the right tool for the job instead of treating all AI models as interchangeable.
Iterating on AI-generated content—not accepting the first output but refining it through critical thinking.
Applying AI within your own industry or expertise, recognizing that AI’s value is directly tied to how well it aligns with your specific needs.
Recognizing AI’s limitations and being vigilant about errors so you’re using it as a tool rather than a crutch.
AI literacy isn’t just about knowing how to prompt ChatGPT—it’s about knowing how to make AI work for you. The better you understand its strengths, weaknesses, and nuances, the more valuable it becomes.