Artificial Intelligence (AI) for Brands: Terms Explained Simply

Here is a list of AI term explanations in a simplified, conversational style for brands and brand managers:

Artificial Intelligence (AI)

AI is when machines or computers can think and act like humans. It’s basically trying to make computers smart so they can understand stuff, talk to us, learn on their own, and make decisions without needing a human to program every little thing. AI is blowing up these days.

Machine Learning

Machine learning is a type of AI that allows computers to learn and improve on their own without being explicitly programmed. The computer looks at tons of data, finds patterns in that data, and uses those patterns to make predictions or complete tasks. It’s like if you showed a friend a bunch of games of chess and they figured out the strategies and rules on their own just by seeing the data. The more data the computer has access to, the more it can learn and optimize its performance. Machine learning powers many modern AI applications, from product recommendations to self-driving cars.

Deep Learning

Deep learning is a subset of machine learning that uses multi-layered neural networks to learn from large amounts of unstructured data like images, video, and audio. The more layers in the neural network, the more complex concepts it can learn. Deep learning algorithms perform very well at things like image and speech recognition.

Neural Networks

These are a big deal in AI. They’re designed to imitate how the human brain works. They have layers that can learn from lots of unstructured data, like photos or videos. The more data they get, the better they get at things like recognizing speech or images. It’s kind of like how our brains can easily recognize a dog or a cat after seeing lots of photos and real life examples.

Natural Language Processing (NLP)

NLP allows computers to understand and generate human language, either written or spoken. This powers AI features like text messaging bots, voice assistants, and automatically generated text summaries. NLP uses machine learning to analyze massive amounts of natural language data to detect patterns and meaning that teach computers to communicate more like humans.

Computer Vision

This is the tech that lets computers “see” by understanding what’s in images and videos. It allows AI systems to make sense of the visual world like humans can. For example, computer vision powers features like face recognition in photos or self-driving cars that can “see” stop signs. It’s a huge area in AI.


Chatbots are computer programs that can chat or text with humans. They’re designed to have conversations with us by understanding what we say and responding. Think Siri or Alexa – you can ask them something in normal language and they’ll respond based on their programming. It’s not exactly like chatting with a human yet, but it’s getting better all the time as AI improves.

Reinforcement Learning

Reinforcement learning is a type of machine learning where algorithms learn through trial and error interactions with their environment. The algorithm gets either rewarded or penalized for its actions, like training a dog with treats and scolding. This technique allows AIs to learn skills like game strategy purely through experience.