Is Everything AI Now?
It’s 2026. Do you know what your AI is doing?
It’s a bird…it’s a plane…yes, it’s Super Intelligence! Is there anything more hazy today than AI? You hear about it everywhere. And it seems to be everywhere. But finding out what it is can be daunting. Even so, about two-thirds (66%) of US adults say they interact with AI at least several times a week, including 7% who say they do so almost constantly. (Pew Research Center, February 2026 survey)
Is Alexa (or Siri) ‘AI’? What about your weather app? Online shopping? Navigation in your car? Streaming service? Google search? Even if you seldom use the internet or your phone, chances are your bank, grocery store, government office, or doctor uses AI. What’s frustrating for some people is that we just don’t know who’s doing what anymore. Did an AI chatbot answer my question? Or was it a real person?
Let’s start with some ‘established’ definitions. One of the most cited comes from the OECD (the Organisation for Economic Co-operation and Development’s AI policy group definition).
AI system: An AI system is a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Different AI systems vary in their levels of autonomy and adaptiveness after deployment.
The US government’s current definition (NOTE: Undergoing updates as of October 2026):
15 U.S.C. 9401(3), from the National Artificial Intelligence Initiative Act of 2020. The term ‘artificial intelligence’ means a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations or decisions influencing real or virtual environments. Artificial intelligence systems use machine and human-based inputs to—
- perceive real and virtual environments;
- abstract such perceptions into models through analysis in an automated manner; and
- use model inference to formulate options for information or action.
OK. What exactly does that mean? Over the years, computer systems have been evolving from systems explicitly coded to produce specific outcomes to systems that can produce responses without specific commands telling them exactly how. While the core of these systems is still built using computer code, the difference lies in the ways the AI systems use a process of mathematical weighting to provide predictions and content of all kinds, whether semi- or completely autonomously. These systems are fed immense sets of data, powered by massively powerful processors, ‘trained’ by engineers, taught a mathematical way to analyze content, and then they predict the most likely result. (Note to AI users: this isn’t always the correct result.)
Technology professionals will say that AI has been around for quite some time. The term ‘artificial intelligence’ was coined in the 1950s, and the capabilities have improved significantly since then. Most of the changes to applications were rather invisible to the user. Email systems moved from using explicit rules on which email to put in my spam box and which to leave alone, to systems which were designed to identify spam by matching patterns and probabilities. This new approach to computing was a forerunner to the more complex AI systems of today. As computer capacity and speed increased, coupled with the vast amount of data available across the internet, these capabilities grew dramatically.
Now, AI has moved front and center. Breakthroughs in technology in the 2010s dramatically improved the ability to parse human language and to extend the mathematical capabilities of the programs. When ChatGPT came out in 2022, followed soon by Claude and others, the public got its first real look at what these tools could do. New “generative” AI systems take language-based requests and produce a unique result. You don’t need to know how to write computer code to get results. This means everyone can have a research and writing assistant that can make posters and videos, code websites, create stories, summarize huge volumes of data, transcribe video chats, and a thousand other things on their laptop or phone. The catch? Your laptop or phone has to be connected to one of the large data centers running these systems.
Other AI systems, called “agentic” AI, can take actions towards a goal without the underlying instructions on how to do it. For instance, you can tell an AI agent to reorganize all of the files on your laptop, identifying which to keep and which to delete. And that’s all you have to say. The AI agent figures out how to do that. (Another note to AI users: you may not want to have it delete anything until you check.)
Where does that leave us? AI systems are here now, and there doesn’t seem to be any sign that they are going to go away. And given the widespread nature of AI tools, it is nearly impossible to think that you can avoid using them or being impacted by them. AI isn’t new, and it isn’t just one thing. It is a whole range of computer capabilities, from better code, to enhanced research and medical breakthroughs, to cute pictures and yes, a host of generative AI social media ‘slop.’ What AI produces is often limited only by the things people ask it to do, its programming and training, and the probability that it gets the right answer.
All of this new capability brings with it a host of other issues. The goal of this post is to clear up some of the misconceptions about what AI is, where it is, and what it does. Before you say, “I’m never using AI,” understand that you likely have, and likely will, be interacting with it in the future.
So you decide. What parts of AI do you think are useful?
Dig Deeper:
Pew Research Center — What do Americans think AI is?
Stanford HAI — 2026 AI Index Report
Policies, data and analysis for trustworthy artificial intelligence