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Artificial intelligence. Most marketers know about it. Some embrace it, while others fear it. The reality is that almost all of us are using it every day, though we may not always know it. AI is predicted to have trillions of dollars of annual impact, yet most marketers don’t understand it. In most cases it won’t replace human work, but it can give marketers and brands superpowers beyond their current marketing efforts. Implementing AI strategies can lead to increased productivity and efficiency, increased revenue growth and a greater ROI on marketing spend.
As the technological pace of change and the challenge of reaching customers and prospects through the glut of online “noise” increases, AI will continue to provide more effective and increasingly customized solutions. But AI is confusing for many marketers. So, in this series of posts, we’d like to define what it is and share some of the basic terms associated with it as a starting point for learning about its marketing potential. Then we’ll touch on some of the ways AI is making marketing more effective and efficient. Finally, we’ll look at some of the limitations of AI including the question of its impact on us as humans.
11 AI Terms You Should Know
If you are unfamiliar with AI terminology, the following short glossary will be a great place to start. It will also help to clarify any misconceptions you might have about certain terms.
This term refers to machines that can learn, reason and act for themselves in the same way that humans can. In simplest terms, it is “making machines smart.”
These are simply math formulas or programming commands that define a series of steps used to solve a problem. Many algorithms are a set of rules built to tell machines what to do, but with advanced AI, machines can create their own algorithms that can open new paths and create new opportunities.
The process of replacing either part or all of an activity previously performed by a human with a machine. A simple example would be the ability to automatically send emails based on predetermined user interactions. AI will enable machines to perform higher level cognitive tasks than was before possible.
Extremely large data sets that can be analyzed to reveal trends and patterns relating to human behavior. Machine learning uses big data.
An AI function that mimics how the human brain processes data and makes decisions. An example would be the ability of self-driving cars to automatically detect objects like stop signs, traffic lights and pedestrians.
A series of algorithms that find patterns in huge amounts of data. These patterns are then used to make predictions. Examples would be speaking to Alexa, recommendations of shows or products on Netflix or Amazon, songs on Spotify, your Facebook or Twitter feed and your Google searches. Each of these platforms is collecting as much data about you as possible and then making an educated “guess” about what else you would like.
Natural Language Generation
An AI technology that takes structured data and turns it into a written or spoken narrative.
Natural Language Processing
A technology that interprets human language with an acceptable level of accuracy. Google Translate, Apple’s Siri and Amazon’s Alexa are examples.
Robotics are not artificial intelligence. Rather, this field uses artificial intelligence in its creation of physical automatons.
Ordered data that is displayed in columns and rows
Any data not structured in a particular way. Examples: Word documents, social media posts and email.
Digital marketing is now a game of quick changes and out of the box ideas. Everyone is going to have to learn to think differently if they want to remain competitive. We’d love to help you do that thinking. We’re experts in finding the right hack that creates a breakthrough. We’d love to start a conversation about we could help you as you adapt to this ever-changing world. Just click the button below.