The 4 Types of Artificial Intelligence and What Marketers Are Using the Most (Research)

You’ve probably heard how artificial intelligence could revolutionize how marketers work, In fact, you might be using AI-powered tools right now.

But if you’re like me, you haven’t “pulled back the curtain” to see how this technology works until now.

Here, we’ll cover the four main types of artificial intelligence — Reaction Machines, Limited Memory, Theory of Mind, and Self Awareness — and how each type can power your marketing.

How many types of AI are there?

There are four main types of AI: Reactive Machine, Limited Memory, Theory of Mind, and Self Aware.

However, since AI can be classified by function (the types listed above) and abilities, you add three more to the mix: narrow intelligence (ANI), general intelligence (AGI), and superintelligence (SGI).

Below we will explain each type.

4 types of artificial intelligence

reactive machines

As the name suggests, reactive machines react and respond to various signals. It does this without extensive understanding of memory usage or context.

This type of AI is commonly used in game design to create opponents, for example. The opponent will respond to your actions, movements or attacks in real time but is unaware of the overall objective of the game. On top of that, it doesn’t have any stored memories, so it doesn’t learn from past experiences and adjust its gameplay.

Reactive AI Gives Too Much Power marketing tools, notable example chatbot, These programs use reactive AI to respond to messages (or inputs) with the right information.

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Chatbots are a popular tool in customer service, but they can also increase the productivity of marketers. For example, HubSpot chatspot There’s a handy AI-powered assistant that can pull up reports, create contacts and send follow-up emails based on certain commands.

Beyond chatbots, reactive AI can analyze customer behavior, campaign performance, and market trends. With these insights, marketers can instantly optimize their campaigns, improving their effectiveness and ROI.

limited memory

Limited memory AI is capable of learning from a limited amount of data or feedback. However, it does not “bank” any memory for an extended period of time.

A great example of the ‘limited’ aspect of this AI is ChatGPT. It has a limit of 4000 tokens (forms of text such as words) and after that limit cannot remember anything from the current conversation. So, if the conversation has 4097 tokens, ChatGPT responds based on the latest 97 tokens.

This technology can be found in self-driving cars. It can detect lanes and map the road ahead. It can also adjust the car’s speed and brakes in real time based on traffic patterns and road conditions.

In marketing, limited memory AI can be used to analyze large amounts of data, helping marketers make better decisions about their strategies and tactics. It can also make predictions and recommendations based on this data.

While limited memory algorithms are effective, they are not foolproof. They can make mistakes or make wrong predictions, especially when dealing with old data. In other words, the output is only as good as your input. Therefore, it is important to train these algorithms with accurate, relevant and up-to-date information.

Reactive Machines and Limited Memory AI are the most common types today. They are both a form of narrow intelligence (which we will discuss below) because it cannot perform beyond programmed capabilities.

theory of mind

Theory of mind exists only as a concept. It represents an advanced class of technology that can sense the mental states of humans.

For example, if you yell at Google Maps because you missed a turn, it doesn’t get angry or provide emotional support. Instead, it responds by finding another route.

The idea behind theory of mind is to create machines that can interact more effectively with humans because they understand their needs, goals, and motivations. For example, if an AI system can sense the frustration of a disgruntled customer, it can react more intelligently.

In the long term, theory of mind AI could have important implications for marketing. However, it is still in its early stages, which makes it difficult to predict when it will become a reality.

self aware

Self-aware AI is seen as the next step in the development of theory of mind, where machines are able to understand human emotions And They have their own feelings, needs and beliefs. Currently, this type of AI exists only hypothetically.

M3gan, the robot from the film of the same name, is an example of self-aware AI. She is sensitive and aware of who she is and experiences emotions, and can sense the feelings of those around her. He’s awkward like we’d expect from a robot, but he has social interactions.

stages of ai

There are three stages of artificial intelligence, roughly defined by its ability to replicate human capabilities:

1. Narrow Intelligence (ANI): Narrow AI represents the vast majority of AI systems that exist today. At this level, AI is designed to perform a specific task or set of tasks. It does not have the ability to learn or adapt beyond their programming. Examples include chatbots and virtual assistants (such as Siri), and recommendation algorithms.
2. General Intelligence (AGI): This is the next evolution of AI. These systems are designed to have human-like intelligence, allowing them to learn and adapt to new situations, think abstractly, reason and solve problems. At this point, AGI is still largely theoretical.
3. Superintendent (ASI): ASI is an advanced form of AI that is beyond human intelligence, enabling it to solve complex problems, create new technology, and make decisions beyond the scope of human understanding. ASI is a hot topic of debate, and its potential benefits and risks are highly speculative.

While these stages are widely accepted, there is debate about what defines each stage and when we can achieve them – or whether we should be developing AI at all.

Top Types of AI in Marketing

As mentioned, reactive and limited memory AI (both are narrow AI) still exist today. This means that AI tool marketers use strictly reactive, or reactive + limited memory.

We surveyed 1350+ marketers in the US to learn more about their use of AI and automation and the tools they use in their roles. Here are some key takeaways.

First, when asked about the generative AI tools they use in their marketing roles, the majority of marketers using AI are chatbots (66%).

Chatbots can be both reactive and limited memory AI. For example, a rule-based chatbot that follows an if/then model and is programmed with canned responses can be called reactive AI as it follows a set structure and cannot deviate from the structure Is.

Machine learning chatbots, like conversational chatbots, are limited memory AI because they leverage data and past conversations to respond to customers. They become more effective over time, but their memory is limited.

Marketers also said they most commonly use visual AI tools (57%) and text generation tools (56%). Regardless of the tools they use, all generative AI is limited memory AI because the tool can create new content based on the data it is trained on.

All AI/automation users who responded to our survey say that AI and automation tools save an average of 2 hours and 24 minutes per day.

back to you

From reactive machines to limited memory AI, theory of mind and self-awareness, each type of AI has its own strengths and limitations. Knowing these differences is critical to choosing the right tools, leveraging them effectively, and staying ahead of the curve.