Advertising can be anything from small-scale pay-per-click (PPC), maximizing reach for every dollar spent—all the way to a more in-your-face orchestra of billboards, TV spots, and targeted ads to push a new product.
No matter the size and scope of your advertising operations, AI is here to disrupt it for the better. It’ll help you in planning stages, with producing creative, and for monitoring and reporting. You’ll have more ideas, data-driven tools to assess if they’re good, and optimization platforms to improve conversion rates as you sleep—literally.
If you’ve used automatic smart bidding in Google Ads and Meta ads, congratulations: you’re already using AI in advertising. But there’s much more to explore here, so let’s get right to it.
Table of contents:
What is AI in advertising?
As a discipline within marketing, advertising is all about getting your product or service in front of your target audience: it can trigger people to work their way through the funnel, going from unengaged strangers to loyal customers. AI can help you research your audience, create content more quickly, use data to make better decisions, and offer a better view of campaign performance as it happens.
Honestly, there aren’t many commercially available platforms that cover all the possibilities quite yet. But with that in mind, here’s how AI can help across the process of creating a new campaign.
Strategy and planning
This phase involves brainstorming and diving into data, as you’ll be setting objectives, choosing target audience segments, and determining the media mix, among many other steps. AI can add more options to the table, find patterns in data, and summarize the research.
More than that, you can get an overview of campaigns you’ve run in the past, check your present ideas against what you’ve already done, and even run the same process for competitor campaigns to find gaps and opportunities.
And if you have previous campaign stats, you can use them to train an AI model to start predicting future campaign performance. When you have enough data, you can submit the best ideas and see how likely they are to be successful.
Creative development
Advertising needs images, audio, text, and video. It’s obvious how AI can help here: over the past year, lots of new generative tools have appeared on the market. You can brainstorm messaging and aesthetics or remix existing assets for optimization or better targeting. And if you’re targeting many channels, you can also use AI to adapt the assets, changing aspect ratios, text sizes, and layouts.
Media planning and buying
Will your campaign work best with the media mix you’ve gone with? If you have access to historical campaign data, you can see which campaigns did best based on the channels you targeted and what the message was, among other data points. And if you’re using Google Ads or Meta ads, these platforms already have smart bidding tools that use AI to give you the maximum exposure for each dollar you spend.
Monitoring and optimization
As the data comes in, you can use an AI model to ask questions about what’s happening and use prompts that correlate different data points together. When you combine this with traditional analytics dashboards, you can get deeper insights into what’s working and what’s not—and then develop some A/B tests or small tactical pivots to steer your campaign to better results.
Reporting and analysis
All wrapped up? Again, you can use AI to ask questions about your data, see what went well and what didn’t, and brainstorm the next steps to take. If your reports always follow the same structure, you can get AI to help you write and format the entire document, as well as generating deeper insights based on campaign data.
How is AI used in advertising?
We’ve gone through each stage of an ad campaign and how you’ll find AI in every step. You’ve got the general overview: now, let’s explore how you can use AI for the core tasks of running a great campaign.
Brainstorming and research
This can be as simple as a prompt in ChatGPT asking for advice on how to run an ad campaign. When you add more data about what you want to achieve and how, it can give more useful answers that can spark ideas on campaign strategy, message angles, and channel mix. Just be careful when entering sensitive data into the chat box: make sure that you’re in a mode where your data won’t be used for model training.
You can also use the summarization and analysis capabilities to help you drive insights from market and audience research, saving you potentially hours of reading through everything yourself. Collect all the data in a set of documents, upload them into an AI tool, and start asking questions.
Optimizing ad spend
Platforms like Google and Facebook already include AI when you’re shopping for keywords and choosing which audiences you want to target. With an enormous amount of historical data on ad performance and user details at their disposal, they offer AI-powered smart bidding tools to optimize your budget.
Taking into account your ad messaging, target audiences, creative, and keywords you pick, these platforms will push your ad to users that are most likely to convert. This doesn’t require manual intervention—although there are manual modes available if you have your data—so it’s an auto-pilot method for increasing your return on ad spend (ROAS).
Audience segmentation
Do you have a lot of detailed customer data? I mean more than just names and emails: if you have purchasing history, website behavior, or demographic signals available, you can use AI to find new patterns, cohorts, and segments within the list. This can be as easy as ingesting the data into a model with a prompt—just be careful to anonymize the data or use an AI model with high privacy standards.
Now that you have new segments, you can dive into their needs and craft messages to target them—higher personalization leads to better results.
Dynamic ad personalization
When you have enough data to know how each member of your audience likes to be addressed, what they want to see, and what resonates the most with them, it’s possible to use generative AI to create variations of your campaign. These can be as simple as changing the layout of the ad—for example, changing the shape or copy of the CTA—or more noticeable, like swapping out images for ones that might appeal more to the current viewer.
As safety and trust in AI models increase—and generation prices decrease—we may even see ads generated on the spot uniquely for each user based on their data, circumstance, and active device.
Content and asset creation
Text, image, audio, and video: whether you need something from scratch or a variation from existing content, AI is the go-to, low-cost speedy solution to create more. You can use it for brainstorming, producing the final assets, or use it programmatically for dynamic ad personalization.
Predictive analysis
By analyzing historical performance and correlating that data with your strategy and creative, you can use predictive AI models as a testing ground for new campaigns before even launching them. And since you can use AI to generate more ideas, you can also remix what you currently have and submit that for predictive appreciation as well.
This is great for testing more ideas in a shorter period and optimizing your original hypothesis before it hits the market. While predictive models need a lot of original data to be really useful, if you commit to that long-term investment, you can get an engine that accurately pinpoints how campaigns will perform.
Competitor analysis
The same way you can use these tools on your marketing and advertising strategies, you can also run them on your competitors. By feeding an AI model with what other businesses are doing—and correlating it with their performance—you can see what is or isn’t working for them.
If you have your data, you can ask AI to compare your strategies and identify gaps and opportunities for differentiation. This can give you useful insights on how to plan your next campaign, either competing directly against or acting on markets or segments that the competition isn’t paying attention to.
Examples of AI in advertising
I’ve read plenty of case studies of AI in advertising—and quite a few in marketing, too, since the line can be blurry. I’ve curated a selection that shows the breadth of what businesses are using to improve conversions, lower costs, and run more successful campaigns across the board. All this with AI involved in any part of the process.
AI optimization features in Google Ads and Meta ads
Google Ads and Meta ads have AI built in to help you find your target audience and serve the message that converts.
Google’s tools are built around its ad distribution channels—Search, YouTube, and the Google Display Network (embedded ad space in websites). Here are the top ones:
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Smart Bidding analyzes billions of data combinations to find the best bidding strategy aligned with your ROI goals. The ultimate goal is to get the right message to the right user for the lowest bid price possible.
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Broad match uses AI to find related keywords that may attract users interested in your offer. This adds flexibility to your campaign, especially if the search terms that you’re targeting are evolving quickly.
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Responsive search ads let you add variations to headline and copy and have Google give feedback based on performance.
Meta has similar features adapted to its distribution channels, Facebook and Instagram. The platform will also help you browse and find target audiences, while optimizing your spend based on objectives. But it goes beyond that:
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The Meta AI Sandbox is a generative AI tool that helps you write copy with AI based on your target audience, create backgrounds for your products, and assist with AI outcropping (super useful to comply to aspect ratios and media formats of each channel).
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Meta Advantage+ adds AI to multiple aspects of your campaign, automating parts of the creation process by using machine learning to predict audience targeting, optimal ad placement, best creative to display, and best budgeting.
Other ad platforms, like Bing Ads and TikTok Ads, may also have a range of AI features present to help their business users reach their intended audiences for less, while delivering the most relevant messages.
Content and product recommendations
Customers who buy socks also buy shoes, right? This is the gist of product recommendations, and the more data you have about past purchases and browsing from your users, the better you can offer them lightbulb add-to-cart moments as they browse your website. If you also have their email, it’s easy to deliver curated product recommendations by using AI to crunch the data and serve a list that’s likely to please.
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SpaceO, an AI software development agency, developed PickyPilot, a tool that integrates with eCommerce shops to recommend the best products based on user behavior. This tool improved the shopping experience for users, reducing the overwhelming aspect of researching the best products.
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The Calm app, a mindfulness and meditation app, uses Amazon Personalize, a machine learning infrastructure, to understand what its users would like next. Users who find personalized content tailored to their needs usually spend more time on the platform, which improves user retention over time.
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Netflix is popular for doing the same with your favorite TV series and films. More than that, they also personalize some trailers and thumbnail images to increase conversion based on what they know about the user.
AI-powered personalized content
Farfetch, a luxury eCommerce fashion company, uses AI to optimize their email ads. Using Phrasee, a generative AI platform, they were able to adapt email subject lines to improve open rates, while still ensuring that the copy remains within the brand voice guidelines.
The result? A 25% average click rate and 7% open rate increases. While these may seem modest numbers, this optimization on top of Farfetch’s large email list yields big results.
Ad optimization to improve conversion
talabat, a delivery app operating in the Middle East, used Meta’s Advantage+ feature set to reduce the cost for acquiring new users. The standard enhancements tool took the company’s original ad and ran several optimizations, including generating multiple versions of creative and messaging, automatically adding filters, cropping, and rearranging text placement, among others.
AI advertising tools: 6 examples
You want to use AI for advertising, but I’m assuming you don’t want to buy your infrastructure and hire machine learning experts to run everything. There are plenty of apps you can use to help you infuse a bit of extra power into your ad campaigns. I haven’t had the opportunity to test these myself, but they come highly recommended.
Adzooma for optimizing PPC campaigns
Are you a pay-per-click power user? If you’re running campaigns across all platforms—Google, Meta, and Bing Ads—it’s hard to keep track of everything. Adzooma is an AI advertising platform that brings all your campaigns in one place, offering advice and insights on how to optimize, as well as making reporting and auditing easier in the long run.
Semrush PLA Research for competitive analysis
When your competition is fighting hard for attention in Google Shopping Ad campaigns—and winning—you can use a Semrush tool to reveal their strategy. The Product Listing Ads Research feature lets you:
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Discover your competitor’s keywords
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Look into the positioning of their listings
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See competitive pricing information
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Analyze the keywords that trigger the listing of their ads
Persado for ad hyper-personalization
If you knew exactly what to say, and where and when to say it, do you wonder how different your life would’ve been? Persado helps you find the perfect message for each member of your audience, drawing from historical data of billions of interactions. As it generates possibilities with AI, it optimizes your ads, so you can get the best results without going bananas with A/B testing rounds.
Emotiva for attention and emotion analysis
The attention economy is real: whoever holds it has power. Emotiva helps you measure signals that show how engaged your audience is across ads. These signals include:
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Dwell time, multi-view, and interactions on your website’s pages
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Attention level, span, and engagement based on a video of your user
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Emotion recognition by analyzing facial movements
Correlate this data with your campaign performance to understand what messages resonate, how much they keep attention, and whether they trigger an emotional response.
SensorTower Pathmatics for channel performance and competitive intelligence
Take a data deep dive across all advertising channels, find new campaign opportunities, and keep up with the competition: SensorTower Pathmatics is a big data platform that helps you strategize and make smarter decisions.
Omneky for iterating ad creative
Would your product have a higher conversion rate with a different font? Perhaps in a different color? Or with a different background? Instead of spending your nights being an A/B DJ in Canva, Omneky can generate these tests with AI, track conversion, and keep optimizing, always staying on brand.
The future of AI in advertising
Time for speculation. Based on the trends I’m seeing and research I’ve done for this article, there are a few ways advertising could evolve based on what AI can do.
First, there’s a huge push toward personalization everywhere. While there was already a lot of data to act on to make it happen, it always depended on human teams creating a campaign and optimizing it as fast as possible to improve performance. With AI, data and decisions are closer and can be completely automated: as soon as a new signal or data point is created, the system can act to generate content, update the retargeting strategy, or change the ad message.
Closely related, tools that use AI to crunch big data into human-friendly insights can help in building smarter campaigns without manual research. At the same time, with predictive models and chat interfaces, you can brainstorm ideas and explore how they would work before you even start putting together the campaign.
The advertising market depends a lot on the distribution channels that hold people’s attention. Depending on their user experience, ads can be anything from text-based to high-quality video. There’s a big question about what AI might do to conventional product and service searches, especially Google Search. There’s a rumor that OpenAI is building a product that would change how people search: if it’s a variation of ChatGPT, how will that channel be monetized? Will there be ads in the generated answers? How can users interact with them? How can businesses leverage this new medium?
Finally, let me ask you a few direct questions: How do you feel about extreme personalization? What do you think about having ads that speak to needs you may not be aware you have? Would you feel completely in control of your shopping decisions knowing that companies have access to this kind of information? Depending on how the world reacts to the expansion of these tools, there may be a push for regulation or legislation, severely limiting or outlawing certain features.
Automate your ads with Zapier
Putting together an ad campaign doesn’t happen only on the advertising platforms: usually there’s Google Docs, Airtable, or ChatGPT involved in the process, as well as a host of collaboration tools to keep your team in sync. If you’re spending a lot of time copying and pasting, forgetting to send assets to your team or extracting the data out of your ads, Zapier can help automate the process. Here are a few resources to help you learn how you can automate your ad workflows:
You can also try Zapier Central as an AI assistant that can help you automate all your advertising workflows using natural language.
Zapier is the leader in workflow automation—integrating with 6,000+ apps from partners like Google, Salesforce, and Microsoft. Use interfaces, data tables, and logic to build secure, automated systems for your business-critical workflows across your organization’s technology stack. Learn more.
Advertise intelligently
AI brings a lot of possibilities to advertising. From simple productivity boosts to more ideation to hyper-personalization, there are a lot of tools you can plug into your campaigns to get better results.
The most exciting part of this combination is how you can build a unique advertising AI tech stack that better matches your business needs and those of your audience. And while it’ll never run on autopilot, it’ll feel a lot like you have more visibility and control over the entire process.
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