What Exactly Is AI?

AI Is Everywhere, But What Does It Mean?

Ever since OpenAI released ChatGPT in 2022 as their free public research preview, Artificial Intelligence has absolutely exploded into our professional and personal lives. It seems like we can't go a day without hearing more news about the latest models, doomsday predictions about AI taking our jobs, or the obscene amount of money being spent on data centers and the impact it has on our environment.

The biggest question out of all of this should be: "What does all of this mean?" I've met a lot of people who honestly don't really care if AI makes operations or work more efficient. They liked their lives better before the risk of AI taking their jobs was added on to their already growing list of concerns. I can't say that I blame them. Who cares if large corporations can boost their bottom line with more efficient and effective operations? Why would it matter to me if the latest model from Anthropic or OpenAI can do better work than a software engineer? I'm not even a computer science major!

What does all of this mean is exactly the question we should be asking ourselves with all of this AI craze. I believe that the best way to increase standard of living, life expectancy, and overall enjoyment is with technology and innovation. Artificial Intelligence is promising rapid growth with both of these in mind, decreasing the cost and the time for new inventions and processes to take precedence in the market.

In today's article, we are going to be discussing the rapid rise of Artificial Intelligence, what exactly AI is, and the benefits of learning as much as possible about AI for your personal and professional life.

What Is Artificial Intelligence?

Whenever I get into a conversation with someone about AI, I tend to use almost personal pronouns to describe it such as "it is learning". I think most of us have fallen into this trap of personifying Artificial Intelligence as almost a sentient being, rather than the formula that it actually is. We need to remember: It's just math.

According to NIST, the formula for the ChatGPT GPT 3.5 model was "a combination of basic mathematical formulas such as (y=mx+b) scaled to trillions of parameters." (NIST, 2024) AI is simply a mathematical formula developed in computer software and hardware to complete tasks like a human. That's the important part: LIKE A HUMAN. AI developers are trying to mimic human behavior and decision making with formulas in order to reduce labor cost, increase efficiency/effectiveness, and expand the capabilities for corporations and individuals alike.

New AI models are trained on something called a Transformer. More accurately, many of the AI models we use today are built using a Transformer architecture. The Transformer was introduced by Google researchers in 2017 and changed the way computers could process language. Instead of reading every word only one at a time, the Transformer uses a process called "attention" to determine which words and pieces of information are most important in relation to one another. This architecture eventually became the foundation for models like GPT, which literally stands for Generative Pre-trained Transformer.

This is where the word "training" starts to make a little more sense. During training, enormous amounts of information are broken down into smaller pieces called tokens. The model repeatedly tries to predict what should come next, compares its prediction to the correct answer, and mathematically adjusts itself when it gets something wrong. Do that over and over again across an enormous amount of data and you eventually develop a model containing billions, and in some cases far more, mathematical parameters that represent patterns it discovered during training.

That doesn't mean the model has read a book and "understood" it the same way that you or I would. It means the model has become incredibly good at recognizing patterns and relationships in information. When you ask ChatGPT a question, there isn't a tiny person inside of your computer looking through the internet for an answer. Your words are converted into numbers, those numbers pass through the model, and the model mathematically determines what response is most likely to satisfy your request.

It sounds a lot less like science fiction when you describe it that way.

Why Has AI Become So Popular So Quickly?

Artificial Intelligence itself isn't new. Researchers have been working on AI for decades. What has changed is how capable, affordable, and accessible it has become.

Stanford's 2025 AI Index found that the cost of using a model with roughly GPT-3.5-level performance fell from about $20 per million tokens in November 2022 to only $0.07 by October 2024. That's more than a 280-times decrease in roughly two years. At the same time, computer hardware has continued becoming more efficient and smaller AI models have become significantly more capable.

That matters because technology that once required enormous budgets, specialized engineers, and massive amounts of computing power can increasingly be accessed by almost anyone with a computer and an internet connection.

And this is where I think the conversation around AI becomes much more interesting.

AI Isn't Just for Large Corporations

When we talk about Artificial Intelligence, the conversation usually focuses on companies like OpenAI, Microsoft, Google, Amazon, and Meta. But I think some of the biggest long-term benefits of AI could actually come from organizations that don't have billions of dollars to spend.

Think about a small business with five employees. They probably can't afford to have a full-time data analyst, marketing department, research team, administrative assistant, software engineer, and customer service department. A nonprofit may have ten people trying to manage fundraising, donors, programs, grants, volunteers, marketing, reporting, and everything else that comes with fulfilling their mission.

AI doesn't magically replace all of those people, nor should that be the goal. What it can do is give smaller organizations access to capabilities that historically required much larger teams.

That is already beginning to happen. The U.S. Chamber of Commerce reported in 2025 that 58% of surveyed small businesses were using generative AI, up from 23% in 2023. Interestingly, 82% of the small businesses using AI reported that they had increased their workforce over the previous year. That doesn't prove AI caused those businesses to hire more people, but it does challenge the idea that adopting AI automatically means eliminating employees.

The same opportunity exists for nonprofits. TechSoup's 2025 research, based on more than 1,000 nonprofit organizations, found nonprofits already experimenting with AI for grant writing, fundraising, marketing, administrative work, and data analysis. Smaller nonprofits still face more barriers to adoption, particularly around cost, expertise, security, and knowing where to start, but more than 60% of nonprofits with budgets below $1 million were already exploring AI for areas such as donor outreach, grant writing, and administrative automation.

Churches aren't excluded from this transition either. Barna's 2026 research found that only 13% of surveyed Protestant pastors said they did not use AI at all. Most of the adoption is happening behind the scenes in areas like brainstorming, research, graphic design, communications, and administrative work - not replacing the relationships and spiritual leadership that actually make a church a church.

I think that distinction is incredibly important.

The Goal Shouldn't Be to Replace People

If the only reason we develop Artificial Intelligence is to figure out how many employees a corporation can eliminate, then I understand why so many people want absolutely nothing to do with it. But that is an incredibly narrow way of looking at the technology.

What happens when the director of a small nonprofit can spend less time manually organizing spreadsheets and more time meeting the people their organization serves? What happens when a church administrator can immediately find which volunteers are available instead of spending an afternoon calling people? What happens when a small business owner who can't afford a data analyst can finally understand the information their business already generates?

That is the side of AI that I believe deserves significantly more attention.

AI isn't important simply because it can generate an email faster than we can type one. It's important because the cost of accessing advanced technological capabilities is dropping dramatically. Smaller organizations are beginning to gain access to tools and capabilities that historically belonged primarily to organizations with significantly larger budgets.

There are absolutely questions we still need to answer about privacy, jobs, misinformation, energy consumption, accountability, and where AI should and should not be used. Those concerns shouldn't be ignored. But neither should the opportunity.

Artificial Intelligence doesn't have to replace the human side of our organizations. Used correctly, it can give people more time and better information to focus on the parts of their work that are uniquely human: relationships, creativity, leadership, judgment, compassion, and ultimately the mission they are trying to accomplish.