AI vs. Automation: How They’re Different & How They Connect

We talk about AI and automation every week in this newsletter, and sometimes it might even seem like we use these terms interchangeably. And it just occurred to us: we’ve never defined our terms.

If you’re interested in these topics, you might already have a sense of the differences between AI and automation. But it’s important to know how these concepts differ — and how they work together to push us forward.

So that’s what we’re covering this week: how AI and automation are different and how they connect to each other.

What Is AI?

AI, or artificial intelligence, is a handful of computing approaches that try to emulate human behavior and thinking, solving problems in human-like ways.

Artificial intelligence systems can “listen” to our speech and determine what we’re asking about, then supply an answer. (Or at least they can attempt to: looking at you, Siri.)

Other AI systems can scan huge repositories of data looking for entries that appear to match certain criteria, things that humans can do easily (albeit slowly) but that traditional computing cannot do well.

The latest iteration of generative AI uses natural language processing and something called large language models both to understand what we’re asking and to provide human-like answers, synthesizing information from multiple sources in ways similar to how humans operate.

What Is Automation?

Automation is something entirely different: it’s using technology to perform tasks with little human input. Automation can be quite “dumb” compared to AI: for example, a computer can be trained to find every instance of a specific word in a data set. This doesn’t require thought or decision-making; it’s a straightforward task.

As another example: an industrial robot can be programmed to follow the same sequence of steps to assemble a car part, and even to take branching paths based on various parameters.

In both of these examples, automation enables technology to do something humans would otherwise have to do—usually faster and with more accuracy.

The Difference Between the Two

The difference is in what we’d think of as thought or intelligence: going back to our automation examples, those computers or industrial robots don’t have to “think”— they just have to follow the instructions they’ve been given. (Those instructions are the automation.)

AI systems, on the other hand, do more than follow step-by-step instructions. They don’t really think, of course— but the way they process data, make decisions, and perform their desired functions mimics how humans would do so.

How AI and Automation Fit Together

Though these two technologies are different, they do play well together. An AI system that can make predictions based on a large data set would typically be configured with certain automations: once it makes the predictions (using AI), it has to do something with those predictions. The steps between the prediction happening and it landing in your inbox? Most of those are simple automations.

The same goes for an AI-driven object recognition system: it’s hard for computers to recognize objects, but when an AI does so, the system typically needs to do something with that information. All the steps that happen post-recognition could be handled as automations.

What About Automation Without AI?

There’s plenty of automation happening all around you that doesn’t need AI at all. Industrial automation (robots on assembly lines) has been around for decades without any AI help. Robotic process automation (RPA) uses “dumb” software robots to interact with software and systems in a way that emulates human action—but not human thought.

Of course, these lines get muddier by the day, with businesses like IBM advertising AI-infused RPA, and so on.

As technology keeps moving forward, we expect to see a further blending of AI and automation—but there will still be use cases for either one individually, too.