Artificial intelligence, including generative AI, is used in advertising today to do everything from generate ad creative and copy to optimize ad budgets and predict advertising campaign performance. You can even use AI to scale up ad creative almost instantaneously or spy on your competition's ad strategy.
In fact, modern advertising runs on AI…
Almost every ad you see online relies on AI to reach your eyes and ears in real-time. Today's leading ad platforms, like Google Ads and Meta Ads, use AI to sell, target, and place ads micro-second by micro-second across vast ad network that span millions of digital destinations, apps, and experiences.
That means AI literally dictates who sees your ads and how much you spend to reach audiences on just about every popular ad platform out there.
(For example, Meta's AI uses ad frequency and relevancy to determine the price and display rate of your ads on Facebook and Instagram.)
So, AI literally determines if your ads succeed or fail.
This creates a huge challenge—and a big opportunity—for advertisers.
First, the challenge…
Today's AI-powered ad platforms give you the ability to run thousands of ad variations to micro-segmented audiences at scale. But human ad professionals aren't equipped to take advantage of these superpowers.
We can't keep up with all the data generated by these platforms or process it fast and well enough to move the needle in our campaigns. And we simply don't have the resources and bandwidth to create thousands of ad variations on the fly to test each and every moment.
And it shows…
Instead of unlocking our true potential in digital advertising, we launch a handful of simple campaigns with some basic optimization. These campaigns usually underperform.
Now, here's where the opportunity comes in:
You don't have to try (and fail) to keep up with AI-powered ad platforms on your own. You can actually use AI to help you…keep up with AI.
Today, advertisers have access to powerful, off-the-shelf AI tools that can do things like: generate nearly unlimited creative assets, micro-target audiences, scale up campaigns and budgets, conduct thousands of tests, and even run campaigns autonomously.
So, let's take a look at how to actually understand and adopt these tools in your own advertising.
You don't need to know everything about AI to use it in your advertising—you just need to know these basics.
The best definition of AI comes from Demis Hassabis, founder of AI company DeepMind, which was acquired by Google. He says:
AI is the “science of making machines smart.”
That means making machines that can do intellectual tasks that humans can do. Tasks like: read, write, and understand text; see and identify objects; move around obstacles; hear and understand language; and sense the external environment.
Machines are able to do all of these things thanks to AI.
That's because AI allows machines to learn. Unlike traditional technology, AI can actually detect patterns in data, then learn to make predictions from those patterns. It can then learn from its outcomes to make better and better predictions over time.
Once trained by humans, AI can go learn and improve on its own. The more data you give an AI system, the better it can learn and improve.
Whether you know it or not, you use AI dozens or hundreds of times each day.
Gmail and Google Docs use AI to understand what you're typing, then predict what you want to type next. Every time you (and millions of others) use this feature, you train the AI to get better and better at predictive text.
Self-driving cars use AI to detect obstacles and drive safely. Every mile they drive gives them more data to improve their driving abilities.
Siri and Alexa use AI to understand voice commands and predict what responses make the most sense. Every time you talk to them, they learn to improve the quality of their responses.
In fact, AI isn't just one technology. It's an umbrella term that encompasses a range of smart technologies like these that can learn and improve on their own. Some AI technologies you might hear about are: machine learning, computer vision, natural language generation (NLG), natural language processing (NLP), deep learning, neural networks, and speech recognition. There are dozens of others, too.
You don't need to know every term to be successful with AI. You just need to understand that AI-powered technology has the revolutionary ability to learn and improve on its own.
The ability to learn and improve on its own is why AI gives you a huge competitive advantage in advertising.
AI is an absolute must if you want to win in the new landscape of modern programmatic advertising.
Thanks to the internet and programmatic advertising, we now have the ability to reach consumers across hundreds of digital platforms. We also have the ability to target them based on hundreds and thousands of demographic and behavioral data points. We can even test hundreds or thousands of different ads to see what they respond to best.
Unfortunately, humans aren't good at managing any of this.
Make no mistake, we're great at being strategic and creative. This served us well in the Mad Men days of advertising, when a smart idea and clever slogan meant your ad campaign would succeed. Today, we are still integral to strategizing and creating unforgettable ads.
But we're not good at the rest of it. We can't analyze all the data we now have quickly enough to take action to improve campaigns. We can't manage hundreds or thousands of ad, targeting, and budget variations to get the best results. And we certainly can't find new customer opportunities in a sea of data.
AI can do all of these things and more. That's why forward-thinking companies are using AI to:
There are dozens of use cases for AI in advertising—here are some of the most powerful ones.
There are literally hundreds of use cases for AI in advertising. Here are a handful of the most valuable ones that forward-thinking players in the advertising industry are using today.
Today's advertising relies on programmatic to target and deliver ads in real-time across the internet. AI is critical to the infrastructure that underlies advertising products on many platforms, though you may not always see it. Modern programmatic platforms often use AI to manage real-time ad buying, selling, and ad placement.
In fact, all digital advertising exchanges and platforms use artificial intelligence to regulate the purchase and sale of advertising in real-time. That includes programmatic exchanges, third-party networks, and advertising on platforms like Facebook, Instagram, and Snapchat.
You won't find these exchanges, services, and platforms revealing how their AI algorithms work anytime soon though. But that's the point: Even behind the scenes, artificial intelligence dictates how your ad spend gets used, who sees your ads, and how effective your overall campaigns are. That means if you run paid advertising, you need to understand the terminology around artificial intelligence and ask the right questions about how the AI used by ad platforms may be affecting your spend.
A very basic example of this is:
Facebook advertising, specifically ad frequency and relevance score. These two numbers are key pieces of data that Facebook's algorithms use-without human involvement-to dictate how much you pay and how your ads are displayed.
You might think showing your ad more frequently is good. But it's not. As Social Media Examiner puts it:
Traditional advertising research has shown that optimal ad frequency is at least three exposures within a brand purchase cycle. Traditional advertising schools say that you need to "hit" your audience with the same ad as many times as possible. However, repeat exposure on Facebook might actually hurt your campaign.
That's because Facebook's algorithms take into account user feedback. If you show your ad too often, and it's rated poorly by users, your relevance score may go down. "In most cases," says Social Media Examiner, “the higher the frequency, the lower the relevance score.”
A high relevance score means your ad is more likely to be shown to a target audience than the other ads you're competing with. That translates into better performance and lower costs.
In modern advertising, you need to try to understand the algorithm as much as you understand your audience.
Performance optimization is one of the key use cases for AI in advertising. Machine learning algorithms are used by commercially available solutions to analyze how your ads perform across specific platforms, then offer recommendations on how to improve performance.
In some cases, these platforms may use AI to intelligently automate actions that you know you should be taking based on best practices, saving you significant time. In other cases, they may highlight performance issues you didn't even know you had.
In the most advanced cases, AI can automatically manage ad performance and spend optimization, making decisions entirely on its own about how best to reach your advertising KPIs and recommending a fully optimized budget.
In another case, there exists at least one platform that allocates ad dollars automatically across all channels and audiences, so human beings can focus on higher-value strategic tasks, rather than manual guesswork about what works and what doesn't.
Your ad targeting matters just as much as, if not more than, your ad copy and creative.
Thanks to platforms like Facebook, LinkedIn, Amazon, and Google, you have a seriously robust set of consumer data with which to target audiences, both through desktop and mobile advertising. But manually doing so isn't always efficient.
AI can help here. We know of at least a few AI systems that look at your past audiences and ad performance, weigh this against your KPIs and real-time performance data coming in, then identify new audiences likely to buy from you.
AI-powered systems exist that will actually partially or fully create ads for you, based on what works best for your goals. This functionality is already present in some of the social media ad platforms, which use some intelligent automation to suggest ads you should run based on the links you're promoting.
AI tools today excel at generating all different types of marketing language, and that includes the short, punchy copywriting that often succeeds in digital advertising. These systems leverage natural language processing (NLP) and natural language generation (NLG), two AI-powered technologies, to write ad copy that performs as well or better than human-written copy—in a fraction of the time and at scale.
We often see brands have great success having their human copywriters work hand-in-hand with AI counterparts, with each refining the other's copy and giving each other ideas. The result is something that’s better than human or machine ad copywriters can produce on their own.
Using AI, you can generate ad variations automatically. That means you can take a single ad, give it to an AI tool, and it will spin that ad off into a number of different variations. Those variations could include different ad sizes and formats to adhere to different platforms. Or, they may include different designs and creative based on all the various campaign ideas you and your team have come up with.
No matter what variations you produce, one thing is constant:
You no longer need to do this type of work manually.
AI is getting increasingly good at generating images and videos for your ads.
Popular image and video generation tools are wowing audiences online as people share stunningly creative, artistic, and photo-realistic results using off-the-shelf technology. In just a year or two, these tools have grown in sophistication by leaps and bounds. We’re quickly approaching a world where you no longer have to spend a huge amount of time, money, and energy creating breathtaking visuals that capture an audience’s attention.
With AI, you can actually highly personalize your advertisements based on what motivates consumers. AI solutions exist today that can understand the language and content that motivates different types of people, then automatically adjust your ad content to reflect those motivations.
For instance, User A may respond better to language that emphasizes discounts and value, while User B may respond better to language that gets them excited and joyful. AI can actually tell the difference, then tailor your generic advertising message in different ways to appeal to each of these users.
AI’s predictive capabilities unlock a number of superpowers, including in advertising. Using AI trained on vast amounts of proprietary ad data, we can begin to predict how effective our ads will be before they even launch.
That’s because AI can extract signals from millions of successful campaigns, then apply these to new ones. In the past, we’d simply guess at what ad elements would appeal most to our target audience. Now, we have the ability to get far more predictive using AI.
It’s likely you’ve run some type simple A/B test at some point in your advertising career. But with AI, we can do far more robust testing of ad creative and messaging—and we can do it at scale.
AI tools today allow us to test hundreds or thousands of ad copy and creative variations quickly and automatically. AI’s ability to handle data-intensive tasks at scale makes it a perfect complement to human advertisers who aren’t very good at this task.
The result?
AI can do testing at scale for us, then we can focus on using the insights from those tests to create better campaigns that resonate with more humans.
As an advertiser, you don’t operate in a vacuum. Even with a winning campaign, you still face stiff competition from the other advertisers trying to either reach your audience with unrelated offers or actively competing in your market. AI can give you a leg up when it comes to the competition.
AI tools exist today that allow you to essentially spy on your competitor’s ad strategy. These tools use AI to develop a full picture of which ads your competitors are running on which platforms, as well as how much they’re spending and what offers they’re promoting.
Analyzed in aggregate, this information can reveal exactly what your competitor is up to—and give you the insights you need to outmaneuver them.
AI advertising is reshaping how brands do business.
But AI's potential in advertising isn't just theoretical…
Forward-thinking brands are using the technology today to increase advertising productivity and performance.
HOLT CAT is a heavy equipment company that was interested in attracting talent across a specific line of business. Limited talent was delaying work for customers and slowing down new sales. HOLT CAT turned to AI to create an ad campaign that could attract talent quickly and effectively.
Using employee data and AI-powered ad platform AiAdvertising, HOLT CAT was able to personalize ad messages to appeal to top candidates for open positions. Using the tool, they were also able to get clarity on exact ROAS, and lower their cost per hire by 20%. Not to mention, the company hired 270 new people since the start of the campagin—and, on average, 40% of those hires report being influenced to join the company by the advertising.
Vanguard, one of the world's largest investment firms ($7 trillion in assets under management), turned to AI language platform Persado to conduct highly personalized advertising.
The company's Vanguard Institutional business faces a heavily regulated advertising environment, and was only able to run ads on LinkedIn. Due to regulations of what companies could and couldn't say in ads, the financial services ad landscape lacked easy ways to stand out.
Using AI from Persado, Vanguard was able to hyper-personalize its ads and test them at scale to see exactly what approaches resonated with consumers—a level of personalization and testing impossible without AI. As a result, the company saw conversion rates go up by 15%.
In one high profile example we covered, an AI advertising system helped an ecommerce company achieve a 3,000% return on ad spend—while reducing costs.
Entrepreneur Naomi Simson, a host on Shark Tank Australia, owns a company called RedBalloon, which sells gifts and experiences online (think: an experience-focused Groupon). She was spending $45,000 per month on ad agencies alone to run digital advertising for the brand. She was paying over $50 to acquire a single customer at the time.
Desperation drove her to investigate every possibility. She found an AI tool for advertising called Albert. The tool uses sophisticated AI to analyze ad campaigns, then manage targeting, testing, and budgets.
The tool was able to do things humans couldn't. In one day alone, it tested 6,500 variations of a Google text ad and learned from the experiment. Over time, the tool was so effective at learning from data to improve performance that it skyrocketed RedBalloon's return on ad spend. At one time, the company was getting a whopping 3,000% return on ad spend. They also cut marketing costs by 25% thanks to improved efficiency.
Here are some of the top AI advertising tools to look into for smarter, scalable ad campaigns.
So, which AI tools do you actually use to get real-world results?
There are literally thousands of them to explore. Here are just a few AI advertising tools and solutions you can start testing in your own ad campaigns.
Persado uses hyper-personalized AI generated content in ads to boost conversion rates across LinkedIn ads, Facebook ads, and other types of advertising and content creation.
Thanks to applying machine learning to their vast proprietary database, Persado understands what language resonates most with different types of consumers. Their solution then automatically personalizes your standard marketing and ad copy to tailor it to the language that motivates each user most.
The result?
Highly personalized ads that create significant uplift in performance (and revenue), because you’re speaking to consumers in the language they prefer—their own.
What if you could use artificial intelligence to measure someone's attention and response to ads—just by analyzing their facial expression?
Emotiva uses proprietary machine learning to accurately measure emotions and attention levels. That means you can use AI to determine which ads are most effective based on how people actually feel about them and how they actually pay attention to them. It’s like cracking a secret code that tells you precisely what works and what doesn’t.
Pathmatics uses AI to bring transparency and insight to advertising.
The tool shows you exactly how your ads perform across channels and gives you competitive intelligence about how your competitors' ads perform, fueling ideas for effective creative and placement.
Using the Pathmatics' AI technology, you can literally see exactly what ads your competitors are running in real time and get a complete picture of their ad strategy.
Omneky is an AI ad platform that generates personalized ad content at scale.
Using this generative AI tool, you can generate thousands of optimized ads quickly, then precisely target each one to different audiences. Omneky can even determine which creative resonates most, so you can improve your ad content moving forward. The tool works with platforms like LinkedIn, Reddit, TikTok, Youtube, Facebook, Snapchat, and Instagram.
Celtra automatically uses AI to generate variations of your ad creative at scale.
Celtra will take a single piece of creative you’ve produced, then spin off countless variations for different platforms, formats, and styles. This makes it easy to literally generate thousands of assets automatically.
(Seriously, if you’re creating variations of ads manually, you shouldn’t be.)
OneScreen uses AI for out-of-home ad delivery, targeting, and measurement. The company's machine learning algorithm automatically optimizes which content and ads get shown to audiences, taking the guesswork out of out-of-home advertising.
GumGum uses computer vision technology to learn from images and videos across the web, then help you place ads in the exact spots consumers will see them.
AiAdvertising is an AI-powered ad agency that takes the guesswork out of getting ROI from your ads. The company uses proven tools and strategies to help you maximize both budget and performance across your ad campaigns.
In turn, marketers and advertisers get more predictable, scalable, and effective campaigns, thanks to the power of human experts combined with intelligent machines.