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Artificial intelligence (AI) is no longer an emerging technology. This technology, able to mimic human-like responses and tasks, has been around for decades. The debut of Open AI’s ChatGPT has made it prevalent and raised continuous conversations as to whether AI is really here to take our jobs.
But without context about what AI is and how businesses can use it effectively, it’s easy to miss the ways it can benefit us too.
In this guide, we’ll cover the basics of what AI is and how it works from a technical aspect. While AI may be part of our present and our future state for work and living, there are different types of the technology that get us there—and we have a few tips to make the most out of integrating AI into any workflow so you can focus on the tasks you enjoy.
What is artificial intelligence?
Artificial intelligence (AI) is an advanced computer science, which uses technologies and machines such as computers, robots, and algorithms, to simulate human-like engagement and interactions.
Some real-life examples of AI used in day-to-day life already include:
Maps and navigation: Directions to and from a place on your favorite app are generated through processed data fed to AI, while using algorithms to predict and understand the best routes.
Chatbots: Customer support teams have adopted AI to help with easy customer requests, such as understanding a return policy, tracking an order, or finding a business’s contact information.
Payments: Companies and banks have been using AI to process and deposit payments. Businesses even use AI technology in the background to look for breaches in security and identity management.
Facial detection: Unlocking your phone with your face wouldn’t exist without AI.
The different types of AI
AI can be a catch-all term, but not all AI is built the same or can do the same things. There are four main types of AI, two of which we haven’t quite achieved yet in everyday life.
1. Reactive machine
Reactive machine AI is precisely how it sounds: This type of AI responds and reacts to real-time data but it doesn’t have the capabilities of storing said data or having a memory bank. Reactive machine AI is often programmed to analyze specific behaviors and data rather than rely on understanding and responding to them with past information, like other types of AI.
This type of AI is useful for repetitive or laborious tasks such as uploading and transcribing audio.
2. Limited memory
Limited memory AI has the ability to store and remember certain types of information or new tasks. But like its name suggests, its capabilities are restricted. For example, this type of AI is used in self-driving vehicles. It can process what’s happening based on the information it has been served to drive in the first place.
A chatbot is another example of limited memory AI. While often scripted, a chatbot reacts to and understands prompts provided by customers to find answers from a specific pool of data programmed into the tool.
3. Theory of mind
The following two types of AI get into the realm of sentience and self-awareness many believe is typical of the AI experience and aren’t quite consumer-ready.
The first is theory of mind, which is a type of AI that builds upon limited memory—able to store information and react with past experience—with an understanding of human emotion. AI can’t respond to or generate authentic emotional experiences.
4. Self-aware
The final type of AI is one that we’re furthest away from: self-aware. With self-aware AI, a robot or computer is most human-like—able to process information, respond to it, and react with emotion and self-awareness. That means it understands when it’s being angry and adjusts accordingly, similar to how we manage our own emotions.
How AI works
Now that we’ve gone through the different types of AI, let’s unpack the processes, data sets, and different fields of AI. The technology needs to, more broadly, consume a wide swath of data from all different avenues to be able to respond to and react effectively to a prompt.
For example, if you wanted to know how to write a brief introduction email to any customer who signs up for your newsletter, you could ask an AI tool how to do it and get a complete outline with tips as a response. Without a generous amount of information pulled from a variety of sources, that response wouldn’t be possible.
The major fields and techniques of AI include:
Neural networks: This technique mimics what the brain does in humans, creating neural pathways for information to travel, and is a component of deep learning. This allows us to classify and group information very quickly. Search algorithms are an example of a neural network.
Machine learning: While a lot of AI does need some human intervention, the goal is to not really have it. That happens with machine learning (ML), which means AI can learn, process data, and improve over time. Think of any algorithm serving up content you like based on past behaviors. That’s thanks to ML.
Deep learning: A subset of ML, deep learning offers more complexity and can perform more intricate tasks. Need to generate art for a social media post? This happens because of deep learning.
Large language models: A key way text gets generated is via large language models (LLMs). Information is provided to a computer program so it can recognize and interpret language and other types of data. It uses that data to predict language patterns and generate text, like when you ask an AI to draft an email.
Natural language processing: Similar to LLMs, natural language processing (NLP) recognizes and understands human language and responds in kind, sounding human rather than cold and robotic. Think of any digital assistant that responds to your request with a similar tone and language.
What to consider when using AI
AI is an amazing partner for business owners from small to enterprise. Yet, it’s important to understand it precisely as that: a partner. While AI is buzzy and flashy in the news cycle, it is, like any other tool, not without its limitations and considerations.
To understand AI fully and incorporate it into your business’s workflow, consider the following ethical and logistical concerns beforehand.
Accuracy: Whatever the AI produces from a prompt is only as useful as the directive it’s been given and the data it’s been served and trained on. What information is fed to the AI isn’t always clear. That can mean biased or factually inaccurate data. It’s important to always check for inconsistencies or misrepresentation in anything an AI tool generates for you.
Privacy: AI relies on a consistent flow of data to process, analyze, and serve back to its users. That means if it gets access to your private data, depending on the AI type, it may not fully “understand” it shouldn’t be used or accessed.
Copyright: Authorship is a massive concern with AI. It's a fantastic tool to help generate text or visuals, but it’s important to understand that, because it’s pulling from so many different sources, there could be a risk of copyright infringement if the content isn’t edited or adjusted.
Cost: Depending on the size of your business, getting and using AI may be expensive. Do you build your own or get a third-party provider? Will AI be integral to your day-to-day operations or a useful tool to help with brainstorming? Cost can be little to a lot depending on what you need AI for.
Uniqueness: A unique, human element is essential for any successful business, brand, or audience connection. By design, the responses AI tools generate are like an average of the information they’ve been fed. That’s why it’s important to use AI tools in a way that supports your ideas and output, but doesn’t replace them.
How to incorporate AI into your workflow
Getting started with AI is generally very easy. Put in any search engine what you need from an AI tool and one will pop-up. Squarespace AI is useful for small businesses and entrepreneurs looking to help build their website, generate website copy, send out emails to their customer base, and even write product descriptions.
But incorporating it into any business’s workflow needs some consideration. Here are our tips for bringing AI into your work in a way that fits your business.
1. Understand your business’ goals
Start here and continuously go back to these goals over time to see if they’re still what you need for your business. Are you looking to build a website? Do you need assistance generating copy to attract new customers? Create a set of goals to work off of and consider how AI can make them more achievable.
2. Keep tasks and expectations realistic
As we’ve seen, AI has its limitations. It’s important that, when bringing AI into your business’s workflow, that you use it within its parameters. If you’re using Squarespace AI to help build out your website, the AI will provide insights into design choices and copy to help you optimize it more quickly. Keep the tasks within the framework of what the AI can do.
3. Monitor performance
Your goals will determine how you monitor AI’s performance but, in general, it’s key to keep an eye on how the AI is performing to understand if your business or workflow is benefiting from it. For example, after implementing an email marketing AI workflow, are conversions up? Has the content marketing and strategy outline provided by an AI tool actually helped you generate more traffic or brand awareness?