Over the course of the last few years, the discussion on artificial intelligence (AI) has shifted from a futuristic concept belonging to the Terminator movie franchise to something that anyone with an internet connection can interact with. You can’t open your phone today without hearing about a company’s new AI feature and all the promises that it makes. Microsoft’s Copilot can create PowerPoint slides for your presentation, Google’s Gemini can summarize a virtual meeting, and OpenAI’s ChatGPT can help you write that email you’ve been putting off for the last two weeks — and read it back to you like a pirate.
AI tools are everywhere, often presented as magical shortcuts designed to streamline our lives, but what is it that they actually do?
Let’s start with some simple definitions of terms that you may have heard being thrown around in AI discussions:
- Artificial Intelligence (AI): A broad term for systems designed to perform tasks that normally require human intelligence.
- Machine Learning (ML): AI systems that learn patterns from data rather than being explicitly programmed.
- Large Language Models (LLMs): AI models trained on massive amounts of text to understand and generate language.
- Prompting: The instructions or questions a user gives an AI system to guide its output.
- Generative AI: AI that creates new content such as text, images, audio, or video rather than just analyzing data.
With these definitions in mind, we’re going to get into how AI works in practice and how people interact with it every day. The following questions address some of the most common topics and considerations for anyone beginning to explore AI.
How does a conversational AI tool like ChatGPT actually work?
At a high level, tools like ChatGPT are built on large language models that have been trained on vast amounts of text. They don’t actually think or understand information the way people do; instead they recognize patterns in language and predict what words are most likely to come next based on the input they receive.
When you ask an AI tool like ChatGPT a question or give it an instruction, it uses those patterns to generate a response that sounds natural and relevant. We are essentially training ChatGPT every time we use it. Similarly, every time you complete a CAPTCHA verification, you are training an AI model on object and text recognition.
What are some of the most common ways that people are using AI today?
The average user of a tool like ChatGPT or Grok (an AI assistant created by xAI) is using it to write and edit email responses, summarize documents, brainstorm ideas, generate first drafts, and answer questions quickly. Many folks treat it like a search engine, which can be great for a number of use cases, but you have to be careful with how you’re prompting it to ensure that you’re receiving an accurate response.
Asking these AI models a question is not like querying a database of information. Instead, the AI uses pattern recognition to predict what words to generate next based on the information that it has been given by you as the prompter. Some tools are more likely to remain more neutral on topics than others, with Grok most notably having an “Unhinged Mode” option for its responses. While this can be an entertaining tool to play with, it’s important to understand that all responses from an AI tool like Grok or ChatGPT come with inherent bias based on how it’s being prompted.
Why is prompting so important with AI?
AI tools rely entirely on the instructions they’re given to generate responses. They aren’t pulling from a stored database of knowledge and don’t have intent, judgement, or context beyond what they’re given by the prompter. When a user types a prompt, the model doesn’t search for a matching answer but rather predicts a response by generating one word at a time based on those learned patterns — much like predictive text on steroids.
A clear, specific prompt gives the AI more framework and direction, which usually results in better and more accurate responses. Vague or poorly worded prompts tend to produce generic or even incorrect responses. Like with all first drafts, the responses are best suited to further editing and refinement with further prompts.
More often than not, the initial response you receive from a tool like ChatGPT will not quite be what you’re looking for and requires further refinement. Using this tool is less about asking a single question and getting a single answer, but more about having a conversation with the tool to help shape the result you want. Even with clear, targeted prompts, all AI responses should be reviewed, especially when being used for decision-making or external communication.
What are some of the limitations or risks that people should be aware of when using AI (i.e. privacy, prompting bias, data accuracy)?
Since AI tools are not inherently intelligent, they can sometimes produce information that sounds confident but is entirely incorrect. You may have encountered this with Google’s AI Overview that frequently provides hilariously off-base answers. There are also privacy considerations with these AI tools. Anything you input into the tool, from a simple prompt to an uploaded medical document, has the potential to be stored or reviewed to further train the AI model.
Tools like ChatGPT and Grok are hosted services, not private journals. What you type or upload into them is sent to a third-party system to generate a response, so you should never upload or input any sensitive or confidential information. Never give it any personal data such as your social security number, financial details, or medical information. Even though these tools feel conversational, it’s important to remember to treat them like any other external software platform.
Why is machine learning important when thinking about the development of AI tools?
Machine learning is what allows AI systems to improve and adapt over time by identifying patterns in data rather than relying on fixed rules. In practical terms, machine learning systems learn patterns from data and use those patterns to make predictions or generate responses. It’s the foundation that allows AI tools to adapt, scale, and handle complex tasks like languages and image generation. Rather than being told every grammar rule or visual detail, the AI learns how language flows or how images are structured by analyzing large volumes of examples.
Machine learning also allows AI models to hand uncertainty. Instead of producing a single “right” answer based on a set of rules, they evaluate probabilities and use the context of the prompt to determine the most likely outcomes. This is how AI can write in different tones, adapt to different prompts, and perform a wide range of tasks — but also why it can occasionally produce errors or unexpected results, such as generating images of people with 10 fingers on each hand.
As AI tools continue to evolve, machine learning plays a central role in refining performance over time. Understanding machine learning helps set a realistic set of expectations — these tools are powerful and adaptable, but they still depend heavily on the data they trained on and the way they are prompted.
Where is the future of AI headed?
AI is likely going to become increasingly integrated into everyday tools rather than existing as something separate or specialized like it is now. We’re already seeing this with highly targeted search engine ads, smart voice assistants such as Amazon’s Alexa, and customer support systems, all of which use AI technology behind the scenes. As this trend continues, we will interact with AI less through standalone platforms like ChatGPT and more through the software and systems that we’re already using daily.
Much like spellcheck or GPS navigation, AI is positioned to become a background capability rather than a headline feature. In many cases, people won’t be using AI in the strictest sense; instead, it will quietly support tasks and workflows in ways that will feel increasingly more normal. As AI becomes imbedded across digital tools, its presence will be less noticeable, even as its influence continues to grow.
As AI continues to evolve, understanding the fundamentals is one of the best ways to set up yourself, and your business, for success. While a world-ending apocalypse at the hands of our AI overlords may be a long way off in a futuristic fever dream, there is a much more immediate need to learn to understand and navigate the AI tools and features already around us.
Whether you’re looking to use AI to help craft and email response or automate your workflow, a foundational understanding of the technology helps ensure it’s used as a tool to support better work, not replace critical thinking entirely.