Artificial intelligence (AI) has been a mainstay of science fiction for many years. As long ago as 1872, science fiction writers depicted computers that controlled the earth — robots that challenged or aided humanity or human battlesagainst AI machines. Think “2001: A Space Odyssey,” “Blade Runner” or “The Matrix.”

However, while science fiction writers played with artificial intelligence, AI marketing has become an increasingly important tool for companies in the real world.

In 2021, the global AI market was valued at $93.53 billion — a number expected to reach $997.77 billion by 2028,according to Grand View Research.

In 2022, Statista published a report that said, "AI is expected to have wideadoption in and implications for every industry vertical and is likely to be one of the next great technological shifts, like the advent of the computer age or the smartphone revolution."

How Does Artificial Intelligence Work in Marketing?

AI marketing typically fits into two categories: task automation and intelligent/machine learning. And these two use categories can operate either as standalone or integrated programs.

Task Automation vs. Intelligent AI

Task automation is pretty straightforward — AI programs carry out structured, repetitive tasks. They operate according to a pre-determined set of rules or programmed sequence of events. This use of AI is not, and need not be,intelligent.

Intelligent AI marketing, however, takes advantage of machine learning — a type of AI that can become more accurate over time, learning as it goes, essentially. Intelligent AI runs large quantities of data through its pre-programmedalgorithms to make complex predictions and decisions.

Intelligent AI places customers in verticals that best reflect their interests and anticipates how they will respond to promotions, discounts or seeing a product or service that corresponds to their customer preference profile.

However, these programs aren't perfect. Most applications can only perform in narrow areas, and each use case needs direction on how to compute large amounts of data.

Standalone vs. Integrated AI Programs

Standalone programs are isolated AI programs with no connection to a company's primary product information channels. They allow for the creation of websites that perform specialized tasks. For example, think of a clothing company that lets you design a custom shirt. Or a paint company that recommends colors based on the emotions it detects in your texts.

The benefit of a standalone program is that you can construct it for a specific task quickly. The downside is that it's not integrated into other essential channels, meaning the customer must take an additional step before purchasing, which can be discouraging.

Integrated AI programs, in contrast, are embedded in your existing framework. They allow companies to serve up ads or promotions to customers in seconds — customized to each user — without adding an extra step to the customer journey.

For example, think about when you look at a product on eBay. The site then uses integrated AI to offer other product recommendations based on your browsing history.

Integrated AI can provide important information about customers, such as:

  • How likely are they to make a purchase?
  • How did they navigate through each touchpoint in the customer journey?
  • What kind of information helped propel them towards a purchase?

These insights are gathered behind the scenes using large volumes of quality data.

Companies can benefit from many AI use cases, whether simple standalone programs or intelligent integrated ones. Learning to recognize where each works best is the key to successful outcomes.

Related Article: Artificial Intelligence Takes Off in the Enterprise

AI Components Used in Marketing

Several components go into a successful AI marketing campaign.

Machine Learning

As we discussed above, machine learning is essential for intelligent AI marketing systems. Machine learning uses a series of algorithms that analyze the large amounts of data available to your company, building on that analysis witheach new input gained from customers' experiences.

These algorithms, which use historical and current data, allow AI applications to deliver split-second, relevant information to the customer, increasing the likelihood of a purchase.

Many brands build their own machine learning applications. Even teams with no coding knowledge can develop these applications withAI tools like SageMaker Canvas.


The internet and social media deliver enormous amounts of digital data to companies. These companies also have access to how individual customers travel through their journeys: what they like, what they don't like and what encourages ordiscourages them from making a purchase.

While this information offers invaluable insights into customers, it can also oversaturate organizations if they’re not prepared. It’s critical to know which data sets to use in AI marketing applications.

Successful AI marketing requires quality, current data. Old or incorrect information can result in customers seeing the wrong recommendations or receiving inaccurately addressed or irrelevant messages — which can drive shoppers to acompetitor.

Employee Talent

A brand won’t see results with AI marketing if its employees don’t have the right experience.

When seeking to bring on internal talent, look for the following skills:

  • Data literacy: AI marketers should know how the organization captures data, what they can get out of it, how to interpret it, etc.
  • Ethics: Biases can be programmed into an AI program by those who create it. AI engineers and marketers need to have a solid ethical basis.
  • Adaptability: AI’s abilities — and the legislation surrounding it — is in constant flux. A strong AI marketer should be able to react and adapt quickly.
  • Coding: Not a requirement, but a background in coding is always helpful when working with AI.

Some brands also choose to work with expert outside organizations to implement new and maintain already-established AI programs.

Related Article: If You Want to Succeed With Artificial Intelligence in Marketing, Invest in People

The Benefits of AI Marketing

Using AI marketing to tailor your marketing plans and grow your business has become one of the critical business factors in the 2020s.

AI that enhances marketing efforts delivers greater customer satisfaction. It allows companies to deal with customer concerns faster and lightens employee workloads. It also increases revenue and reduces risks.

Let’s take a more in-depth look at AI marketing’s benefits.

Increased Campaign ROI

Launching a marketing campaign used to be like rolling the dice. Sometimes you were lucky — and sometimes you got snake eyes.

The reason was simple: marketers didn't have access to the vast amounts of personalized data currently available.

Today, AI can analyze and interpret large quantities of data in microseconds and offer up hyper-personalized insights. As a result, marketers can craft campaigns that are highly relevant to each customer, meaning less wasted money andgreater return on investment.

Better Customer Relationships

Say you’re a customer looking at an online store. You put an item in your virtual cart, but you get distracted and walk away for a couple of hours. Later that day, when you check your email, you see a reminder about the forgotten item.

Most customers find these messages relevant and helpful, increasing their overall satisfaction. And when a customer is satisfied, they’re more likely to return (and sing your praises to friends and family).

With AI, it’s possible to deliver these types of relevant communications in real-time without employee intervention.

Faster Decision-Making

AI marketing applications instantly analyze data from marketing campaign results, making it easier for marketing teams to make quick decisions on effective changes.

If something is working well, AI applications will zero in on it. Marketers can then make that quality more prominent while scaling back on features that aren’t as successful.

Reduced Risk

In past decades, when marketing campaigns took a broad-brush approach, brands were never sure they were targeting the correct marketing segment. A marketing team might have spent $10 to make $1. While most campaigns were more successfulthan that, there was always a risk.

Using an AI marketing application reduces that risk and better targets the correct marketing segment. The broad-brush approach? No longer needed.

Related Article: 6 Ways AI-Based Personalization Is Improving the Customer Experience

Learning Opportunities

How Companies Are Using AI Marketing Now

Many private industries, such as financial services, government agencies, healthcare organizations and entertainment outlets, use artificial intelligence in various ways, and each use creates different results.

Some of those uses include:

Programmatic Media Buys

Marketing teams often disagree about where best to run advertisements. While they can plan around preference-based user data, in most cases, they cannot alter or change the plan in real-time based on current customer inputs. AImarketing eliminates this problem.

When AI applications analyze up-to-the-minute data, they can be programmed to bid on ad space most targeted to the preferred customer demographic. Your marketing team can select appropriate channels at the right time and find the bestprice available.

Delivering the Right Message

AI marketing applications allow your company to create more targeted messages based on how customers responded to previous messages. Netflix, for example, uses AI marketing and intelligent learning to depict artwork that more closelymatches an individual user's interests.

"Let us consider trying to personalize the image we used to depict the movie ‘Good Will Hunting,’”Netflix explained on its technology blog. “Here we might personalize this decision basedon how much a member prefers different genres and themes.

“Someone who has watched many romantic movies may be interested in ‘Good Will Hunting’ if we show the artwork containing Matt Damon and Minnie Driver, whereas, a member who has watched many comedies might be drawn to the movie if we usethe artwork containing Robin Williams, a well-known comedian."

Deeper Personalization

Today’s customers expect deeper personalization throughout their shopping experiences. AI marketing's use of quality data allows your company to learn more about consumers' preferences on a deeper level.

For instance, Amazon Music can create a customized playlist for users based on their music choices. If you're a Miles Davis fan, it can create an entire Miles Davis channel for you. You don't have to listen to it, but it's there if youwant it.


Natural language processing (NLP) is a component of AI that allows computer programs to understand human language. Marketers can use NLP to create chatbots that answer frequently asked customer questions.

This technology not only allows customers to get answers faster — and at any time of day — it also lightens the burden of human customer service agents, allowing them to focus on more complex issues.

Dynamic Pricing

Every customer likes a bargain. With AI, brands can use the information they have on a customer to offer up a reasonable product or service price.

For example, if a customer has shown hesitation to purchase in the past, AI-powered dynamic pricing can use a lower price point that’s more likely to encourage a sale.

While you might lose a small profit from a price drop, you’ll gain it back — and then some — by acquiring a returning customer.

Related Article: The Case for Artificial Intelligence in Content Marketing Use Cases

The Challenges of AI Marketing

Marketing teams are still experimenting with how to use AI most effectively. Companies looking to benefit from the tech should do their homework on the best tools for their operations.

Let’s consider some of the challenges that come with using AI marketing.


It's crucial to keep customers consistently front-of-mind when using AI marketing. Your team must comply with all legal standards on collecting personal data, such as theGeneral Data Protection Regulation (GDPR) andCalifornia Consumer Privacy Act (CCPA). AI may soon face government regulation, too, under theEU’s proposed AI Act.

Your teams will need to program AI marketing tools to follow these compliance demands. Otherwise, you might find yourself in hot water legally, facing mounting fines or dealing with unhappy customers.


An AI marketing tool is like a new employee. It takes time to learn the ropes. You'll need to train your AI program with high-quality data that accurately reflects organizational goals, customer preferences, trends and context.

If you don't prepare your application using high-quality data, it won't do what you want it to do, and its value will plummet.

Market Adaptation

Implementing AI technology includes evaluating what jobs you will replace and what new jobs you will create.

As AI becomes more intelligent and better able to deliver personalized content, you may not need such a big marketing team. Or, as mentioned above, you may need to seek out talent with AI-specific skills.

Related Article: AI in Marketing: Top 5 Mistakes Marketers Make

Getting Started With Your AI Marketing Efforts

If your company has limited experience with AI marketing, you should start by building a rules-based simple standalone application.

The best formula is "crawl, walk and then run." Don’t try to do more than is possible in the beginning — be realistic. For example, you can create a behind-the-scenes AI application that assists service representatives in accessingcustomer information more quickly.

As you gain experience and add more complex AI marketing into your operations, always keep your customers at the forefront of your thoughts. That means paying attention to data accuracy, privacy and security.

Your goal is to use automated decision-making driven by AI to provide more value to customers, employees and the organization as a whole.