A Friendly Guide to the AI Terms Everyone Is Talking About

Artificial intelligence has moved rapidly from a niche concept to something shaping how we interact with technology every day. Whether you’re using a voice assistant, exploring new productivity tools, or simply reading the news, chances are you’ve come across a wave of new terminology.

To make things easier, we created a simple, friendly guide to the most common AI terms you’re likely to see. These definitions are drawn from the work of Shelly Palmer, a respected educator and expert in media and technology, and they offer a great foundation for understanding where the world is headed.

Let’s dive in.

Artificial Intelligence (AI): The Big Umbrella

AI refers to computer systems designed to handle tasks that normally require human intelligence — things like recognizing images, analyzing patterns, or answering questions. It’s the broad category that everything else fits under.

Machine Learning (ML): How AI Learns

Machine Learning is a subset of AI focused on enabling computers to learn from data. Instead of being programmed step by step, ML systems detect patterns, adapt, and improve over time. This is why recommendations on apps get better the more you use them.

Large Language Models (LLMs): The Technology Behind AI Assistants

LLMs are the engines behind tools like ChatGPT. They’re trained on massive datasets so they can understand and generate text that reads naturally. They help with writing, explaining concepts, creating content, and answering questions in a conversational way.

AGI: What the Future Might Hold

Artificial General Intelligence (AGI) is the idea of AI that can reason, plan, and think across any topic the way humans do. While it’s often referenced in media, AGI does not exist today — it’s a theoretical future possibility.

ASI: The Sci-Fi Version of AI

Artificial Superintelligence (ASI) is a hypothetical level of AI that would surpass human intelligence in every domain. Like AGI, it’s not real today and lives more in research papers and science fiction than in practical use.

Agents: Small AI Helpers for Everyday Tasks

Agents are focused, automated AI programs that handle specific tasks such as drafting summaries, organizing information, or performing multi-step workflows. Think of them as digital assistants that quietly take care of routine work.

APIs: How Systems Talk to Each Other

API stands for Application Programming Interface. This is the behind-the-scenes technology that lets AI tools connect with software like CRMs, planning tools, or data systems. APIs make it possible for AI to actually do things with your existing tools.

Low-Code AI and No-Code AI: Making AI Accessible

Not everyone needs to be a programmer to use AI effectively.

• Low-Code AI allows users with some technical experience to build AI workflows with minimal hand-written code.

• No-Code AI takes it a step further, allowing non-technical users to build simple AI tools through visual, drag-and-drop interfaces.

Both trends are opening the door for organizations of all sizes to experiment with AI without hiring full development teams.

Guardrails: Ensuring AI Is Used Responsibly

As AI capabilities grow, so does the need for oversight. Guardrails refer to the policies, governance, and monitoring systems that ensure AI is used safely, ethically, and in compliance with regulations. In fields like financial services, guardrails aren’t optional — they’re essential.

Why These Terms Matter

Understanding these concepts helps make the fast-moving world of AI feel a little more grounded. Whether you’re curious about how AI tools work, considering new technology for your business, or simply keeping up with innovation, these foundational terms provide clarity and confidence.

If you ever want to explore how AI intersects with financial planning, investment strategy, or the tools we use at Pathworks Financial, we’re here to help you navigate it thoughtfully.