Why Is AI So Confusing?

When you think about humanity’s biggest accomplishments, you probably think of the Moon landing, or splitting the atom. You probably don’t think of AI.

I get why. Technology has moved so fast over the last few decades that every new thing just feels like the next software update. But zoom out over the last 500 years and the pace is wild. So it makes sense that AI doesn’t feel like a big moment. But what if it’s the step that changes everything after it? How we write, code, cook, look things up, build things, and maybe even how we finally cure diseases we’ve never been able to touch. That’s a lot of power, and it’s scary for the average person. Of course it is. It’s confusing as hell.

What is AI governance? What’s an LLM? What on earth is an agent? I’ve been asked these questions by entry-level marketing interns and by CEOs of billion-dollar companies. Plenty of companies try to explain this stuff. Very few explain it in a way a normal person can actually use.

So let’s try.

The part nobody thinks about

Most of us type into a chatbot, get an answer back, and have no idea what happened in between. We upload our financial documents and ask it to “build me a budget.” We upload a photo of our kid at Disneyland and ask it to fix the squinting. And we assume all of that is private and safe.

News flash: nothing online is ever completely secure, and that includes AI chatbots. Would you post your bank statements on social media? Ask the internet at large to edit pictures of your kids? Of course not. But plenty of people do the equivalent with AI every day without thinking twice. It’s even more true at work, where people paste customer data and contracts into whatever AI tool is open in the next tab.

What is AI governance?

That last problem is exactly what AI governance is for. The textbook version: AI governance is the set of policies, standards, processes, and guardrails that make sure AI systems are built, used, and monitored responsibly and legally. (Salesforce)

In plain English, it’s the AI police. It’s how a company keeps AI from going rogue. You can see everything the AI is doing and catch it when it wanders off and does its own thing, ideally before it causes a problem. Think of it saying, “Hey, that file has customer Social Security numbers in it. That’s not going into the chatbot.” Guardrails are just the rules the AI has to follow, and thank goodness for them.

And policies? We all know what those are. They’re the things we break every time we paste confidential company info into a chatbot.

What is an LLM?

LLM stands for large language model. Sounds boring. Stick with me.

The textbook version: an LLM is a type of AI model trained on enormous amounts of text so it can understand, summarize, translate, and write language that sounds human.

What does that actually mean? Imagine sitting someone in front of the National Geographic channel for ten years straight. They don’t memorize every episode, but they pick up how nature documentaries sound. Then you ask them about lions, and they give you a confident, narrator-voice answer about lions eating everything in the jungle. (Lions don’t live in the jungle, by the way. Confident and wrong, which is also very LLM.) That’s basically what’s going on. It’s very good at predicting what a good answer looks like, which is not always the same thing as being right.

One thing people mix up: the chatbot isn’t learning from you in real time while you talk to it. Its knowledge comes from training that happened before you ever opened it. But depending on the tool and your settings, your conversations can be saved and used to train future versions. Which is one more reason to think twice about what you upload.

What is an agent?

Now the fun one. You hear this every day. “I built an agent that sends my emails.” “I built an agent that writes my social posts.” Okay… but what does that actually mean?

The textbook version: an AI agent is software that uses AI to take a goal, break it into steps, and then carry out those steps on its own, like calling APIs, running code, or searching the web. (IBM, Meta)

In plain English, a regular chatbot answers your question and stops there. An agent takes the next step and actually does the work for you, like sending the email or posting the post. That’s it.

How do you build one? Whole other story. We’re keeping it simple today. But did you notice the big, scary term API in there?

What is an API?

An API (application programming interface) is a set of rules that lets different pieces of software talk to each other and swap information.

I know, that one sounds intense. In practice, it’s how one app you use teams up with another app you use.

Picture yourself at a restaurant. The waiter takes your order back to the kitchen and comes back with your food. You never walk into the kitchen, and the chef never comes out to your table. The waiter is the API. It carries your request to the system that can handle it and brings back the result. Simple.

Where that leaves you

We covered a lot, and if your head hurts a little, that’s normal. Technology is confusing, and AI is a whole other ball game. Nobody has it all figured out, partly because it changes every week.

That’s what we’re here for. Some days we’ll be blunt with you, and some days we’ll walk you through it slowly. Either way, the more you understand how AI works, the better your decisions about how to use it.

And if your company is trying to figure out how to let people use AI without the bank statements ending up somewhere they shouldn’t, that’s literally what we do at SUPERWISE.