AI-Based Email Marketing: What You Need to Know

What is AI in email marketing?

Since technologies involving AI like Midjourney provoke heated discussions, the first thing you’re thinking of is probably machines creating content for you. And, although it’s one of the use cases and we’ll come back to it later, the question is a little more complex. In 2023, if you asked ChatGPT 4.0 about the essence of email marketing, the result was something like this:

In 2025, the updated AI (ChatGPT-4-turbo) got better and suggested a long list of email marketing strategy features you can optimize with it. It was useful, though from a practical standpoint. Here is the gist:

While I can go on a whole technical speech about natural language processing and natural language generation, you are probably here because of the marketing part, so let’s keep the terms simple and quickly discuss three types of algorithms you might encounter.

A lot of artificial intelligence tech relies on neural networks. A neural network is a mathematical function that is designed to recognize patterns in data. What does it do with these patterns later? There are many types of algorithms but if I were explaining it to a preschooler, I’d put it like this:

• “Detectors” simply give you information that the patterns are here. Think of these algorithms as smoke detectors — they only go off when someone lights a cigarette in the room. Solid examples are speech and image recognition algorithms.
• “Predictors” extract patterns from historical data and give you information about the future. For example, Netflix algorithms see that you liked “Black Mirror”, “Stranger Things”, and “Doctor Who” — and recommend more science fiction shows to watch.
• “Creators” use the patterns they recognized earlier and recombine them to create something new. These are called generative algorithms — they generate the output based on the input. ChatGPT and Midjourney are the most popular examples but there are many more.

The thing is, all three types of algorithms can be used in AI-powered email marketing. Now, let’s take a look at some of the use cases.

Ways to use AI in email marketing

I already know that not all neural networks are generative — but there’s a use case for every type of algorithm in email marketing. Buckle up for a ride!

Drafting email copies

Gone are the days we’ve spent crafting perfect copies. Now generative AI-powered technology can do it for you, especially with routine tasks. For example, companies like Sage and Typeface are already using AI to create copies for multiple digital marketing channels. Sage, a global academic publisher known to most college kids across the world, uses Jasper AI for product descriptions, SEO tuning, translation, and more. While not specific to email marketing, the following line (in bold) highlights the systemic shift AI-powered copy has already created. 

“Corwin, our K-12 market, would outsource copywriters to write their back [book] covers. And it would cost around $30,000 dollars a year. And now they’ve been able to bring it back in-house. Jasper can do it for them”, said Shellie Johnson, director of global marketing at Sage in a 2023 interview. 

Still, sending raw AI output to your entire contact list may not be a good idea. However, if you’re uninspired and short on time, drafting a copy with an AI can be a solid starting point. Drafting is a key word though. Here is an example of recent ChatGPT output. I asked him to use a few SEO keys in one paragraph:

Though not for email, this is a perfect example of AI writing as of 2025. Yes, it is still pretty generic and heavy on specific words. Not the ones I needed, though. 

Now, there are algorithms designed specifically for email marketing. With Selzyl, for example, you can build an email template along with a copy in mere minutes. The platform also incorporates AI as an advisor of sorts with different modes, like Copywriter, Psychologist, Marketer, and Proofreader. Depending on the goal, you can use one of them to write a better copy.

Some AI-powered email services, like Hoppy Copy, can create newsletters in different formats or brainstorm topics, subject lines, and A/B tests for you. Here’s what it looks like:

Once you fill in the form, you get five slightly different (and disturbingly good) copies and bonus subject lines for A/B testing in the future. Here’s what I got for the prompt above:

This copy might need some editing like going more specific about the blog content and adding links — but, overall, it’s a pretty decent welcome email for an AI. The takeaway is, that no matter which tool you use, an AI-generated draft will speed up your writing process.

Before you jump from this article to try out what machine learning can do for your next email campaign, here are a few things to know:

• First, generative algorithms can’t write about a new product without any input from your side — that’s because their learning data only has information about stuff that already exists.
• Second, they are only effective if you know your target audience and other crucial aspects any marketing specialist will need. 
• Third, there are a few caveats to consider, like hallucinations, generic tone and wrong lexicon in your copy, and the most basic content forms you can think of. Why is this still a thing? Because natural language generation is about predictability and not about creativity — this one belongs to us, humans!

Will AI tools replace human copywriters? Will content marketing departments cease to exist? Not yet. AI can make pretty good copies, but humans are needed for the strategy, editing, and improving content for it to be really engaging and relevant.

Writing catchy subject lines

As mentioned before, AI drafts several versions of email subject lines. Or just one. Here’s what I got from the algorithm of Copy AI:

I also asked ChatGPT to write email subject lines, here’s what it offered:

Most of these seem generic and a little outdated, but you don’t have to use them as they are! If you’re out of ideas, even underwhelming AI output is a good place to start brainstorming. And drafting is not the only way algorithms can help you with email subject lines.

Jacquard (previously Phrasee) and similar AI-powered tools don’t just write content for you. They learn your brand guidelines and identify if your content fits in the tone of voice, study your subscribers’ behavior, and analyze the subject lines you created. All these features can help you stay on brand and create the most effective subject lines that will get you opens and clicks. 

Don’t know how to ask AI for the right answers and what prompts to give it? Check out our article for the best ChatGPT email marketing prompts, prompts for subject lines included.

Generating visuals and templates

You can use either AI in your email builder to generate templates and visuals or try AI image generators for something specific and unique. The algorithm can help you with email header pictures and illustrations to spice up your copy. Here is a template for a well-being app we’ve generated in Selzy in one minute time with very generic and easy prompt:

Yes, everything you see now — with the subject line, copy, image, buttons, and even the app name — is AI-generated. Yes, it does look just like it, but with a prompt like ours? No wonder!

With more detailed input, you can create more intricate results. These AI-generated templates work especially well for relatively simple cases, like abandoned carts or transactional emails. But you can also generate something longer and more care-demanding — newsletter emails, for example. 

Need to create a very specific image and looking for the best tools on the market? Here is our list of the top AI image generators to choose from, with pricing and adorable pictures for comparison.

Segmentation

List segmentation is dividing the entire subscriber base into groups and sending them different newsletters based on these groups’ characteristics. You can segment the contact list based on location and time zones, gender, age, behavior, and other criteria depending on your goals. It’s possible to do manually but it has certain drawbacks:

• It’s time-consuming, especially with a large subscriber base and convoluted behavioral criteria.
• It’s prone to the human factor — you can send the wrong emails to the wrong people.
• It’s less efficient — without big data analysis, you can only create large subscriber groups using superficial criteria, which is better than nothing but has room for improvement.

Neural networks are great at quickly recognizing patterns and extracting valuable insights from humongous datasets. When they see your huge subscriber base with all the behavioral data, they create smaller groups based on more complex criteria in seconds. For example, AI tools like Mailchimp allow you to create prediction-based segments with customers who are likely to move down the sales funnel or drop over a time period of your choice. 

Technologies like this bring lead nurturing to the next level. With predictive segmentation, you can send reactivation emails to customers you’re about to lose with higher chances to win them back. And fine-tune your nurturing campaigns so warm customers get one last gentle push to purchase at the right time, which will skyrocket your conversions.

Optimizing send times

There’s no consensus about the perfect send times. In 2023, I did an overview and our own research on the best time to send an email, but even today none of the benchmark numbers count as a foolproof success recipe. Manual or automated, send times optimization without AI has a lot of problems:

• The time zone data is yielded automatically from IP addresses — but what if your subscribers use VPNs? In this case, this data has no information on where your customers really live and what their daily schedule looks like.
• Once a customer subscribes to your newsletter, the time zone can’t be changed. So, if they were abroad at that time, they’ll get your emails with send times adjusted to the wrong location.
• Even if you create time zone-based subscriber groups, they’re not checking their inboxes at the exact same time.

That’s where AI comes in handy. Machines are better at detecting data patterns than humans — they’ll optimize send times specifically to your subscribers’ email browsing habits. A great example is the Smart Send feature created for Hubspot by Seventh Sense. Here’s a little sneak peek at what it looks like:

And while that would work great with newsletters and some promo emails, nowadays you need to pay even closer attention to your send time. Moreover, email marketers must choose hyperpersonalization now. What it means is AI gathers customers’ data from different touchpoints (think location, purchase history, website visits, etc.) and creates micro-segments based on it. Certain triggers are set so customers would receive the right email at the right time. 

Take Levi’s, for example. They don’t rely on just scheduled emails. Partnering with AI-focused messaging software Cordial, they personalized their marketing campaign and used revenue-based scheduling. The customer gets their messages when they are most likely to make a purchase. While neither company disclosed how it affected Levi’s revenue, Cordial claims that for some of their clients, such strategies bring a significant boost. We talk about it in detail in our article on recent smart email campaign cases from the biggest brands in the world, so be sure to check it out!

Cleaning up email lists

List hygiene is vital for email deliverability. If you keep unengaged subscribers in your list for long enough, it might trigger spam filters and ruin your sender IP’s reputation. Some ESPs have a list-cleaning feature that allows you to automatically remove inactive contacts.

However, automated non-AI filters are rather coarse — like a mesh sieve that only allows you to strain pasta water but grains like rice will pass through it. AI filters are better at detecting more subtle patterns of subscriber activity — it will be a fine mesh sieve that allows you to sift flour. Some ESPs already have the right feature, so AI can clean email databases and lists. But if yours doesn’t, you can use separate apps for it — for example, Listclean. This tool can remove temporary emails, spam traps, role-based addresses, and other contact list infestants. It also provides AI-based verification to make sure you only send promotional newsletters to real people.

Email retargeting

Targeting ads or emails is showing promotional content to people who don’t know a lot about you but might be interested in your offer. And retargeting is showing data-powered content to those who are already interested but haven’t bought stuff from you yet.

Retargeted emails include content based on the customers’ browsing history — here’s an example:

In this case, AI tracks user behavior and tweaks the email content for each user — both the browsed items and recommendations. You can achieve that both by integrating your ESPs with third-party AI tools and in-build ESP features. For example, Mailchimp has a tool that predicts the potential customer lifetime value of all your subscribers and suggests sending them special promotions based on these predictions. 

Recommending certain products

I already mentioned Netflix as an example of AI-powered product recommendations. This AI use case in marketing is probably one of the oldest in our list. Many retailers use it to recommend products that are:

• Bought together often — for example, fitting batteries or lenses for a camera
• Bought by people with similar purchase history
• Bought by people who liked the same product
• Better alternatives to the product
• Similar to a certain product

Here’s a great example from Amazon:

AI-powered recommendations bring email personalization to the next level — without it, you can do as much as generic selections of the most popular items from your store. Machine learning will help you provide more relevant content for your subscribers and upsell more efficiently.

Benefits of AI-Based email marketing

Now that we know all the use cases of AI in email marketing, let’s discuss how investing in machine learning can do good for your business.

Higher ROI

According to 2024 HubSpot’s report, 68% of marketing leaders reported ROI on their AI investment. No wonder, since even in 2022 McKinsey reported that AI implementation in sales and marketing leads to cost reduction by up to 20%. Even better, using AI in marketing also leads to increasing revenue by 5% and above, which sums up a higher marketing ROI. So no wonder, that in 2025, marketing and sales are two functions where AI use increases year after year. 

What causes such an effect? AI optimizes campaigns so they get more customer engagement and sales. It takes care of everything from copy to automation, from personalization to analyzing your email performance. AI optimization also helps you send less irrelevant and ineffective email content, so you burn less marketing budget without earning it back. And here’s how you get a higher ROI with the help of machine learning!

Cost efficiency

AI significantly reduces labor costs — we’ve already mentioned the Sage example with savings on copywriters. Even without such drastic measures AI automates repetitive and routine tasks and can provide results in mere seconds even with large data sets or complex tasks. All of this saves time for much more important work — marketing strategy and creating captivating campaigns. However, not everybody views the cost-saving future as bright. For example, 78% of marketers believe that more than a quarter of their tasks will be AI-automated in the next 3 years. 

Easy personalization opportunities

Customers don’t like being treated like walking ATMs — email marketing statistics prove it. According to Wunderkind, even in 2023, 73% of US consumers expect personalized communication — and 90% of them are loyal to brands that are good at adjusting messages to their needs. In 2025, personalization is not just a marketing trick — it’s a must.

Email personalization is still possible without AI — for example, you can use merge tags to address your recipients by their first names. But AI digs deeper and allows you to include or refer to a lot of customer data in your emails automatically. This level of personalization and email experience leads to an incremental increase in revenue. For example, an eyewear retailer GlassesUSA increased their revenue by up to 88% just by implementing AI-powered personalized recommendations. And you can go beyond emails! Personalizing push notifications and home page content with AI will bring you more money and happier customers.

Automation

Imagine starting every morning with a coffee brewed in a cezve. To follow this routine, you need to wake up at least 20 minutes earlier to pour coffee and water into a cezve, put it on a stovetop, and keep watching it so it doesn’t overspill. But what if you had a coffee machine that automatically makes you a perfect cup of Joe minutes after you wake up? You could spend these 20 minutes sleeping or doing more pleasant things instead of watching a cezve on a stove.

Now imagine that you have to manually set up each bulk email you’re sending. In this case, creating automated sequences that will work for as long as you wish to will save you hundreds of hours. And using AI will save you even more time — especially when it comes to designing complex, behavior-based sequences. And, instead of doing boring but important work, you can refine your email marketing strategy, take Selzy’s free course on email deliverability, or just chill. It’s a win-win situation!

So, can AI replace email marketers?

Long story short, not really. AI can perform marketing data analysis more efficiently than humans and help you save time and money on mundane tasks. However, even the most advanced neural network can’t replace an email marketer today. Here’s why:

• Humans set the rules and push the buttons. Automated writing content? Someone has to write prompts for ChatGPT or whatever GAN you’re using. Hired a neural network for data analysis? Someone has to come up with a task that an AI can solve, prepare a dataset, and interpret the results. Neural networks are not autonomous entities — these are apps that need turning on and off, and they still need human input to give output.
• AIs can’t “think” strategically. Artificial intelligence can only do narrow and specific tasks — but marketing is more than that. Defining a UVP, building a brand, and coming up with a long-term strategy — all that is on human email marketers for now.
• AIs don’t have soft skills. Even if you outsource most of the tasks to AI including content creation, managing a marketing team is still a job for humans.
• AI content generation is not that good yet. Yes, you can use generative algorithms to speed up the writing process or create illustrations — however, all the AI output still needs human supervision and editing.

Even though AI is a helpful instrument for campaign optimization and saving time for more labor-intensive tasks instead of getting buried in the routine, none of the existing algorithms can replace the entire email marketing department. Good news for the anxious marketers scared of losing their jobs!

Final thoughts

AI can’t replace email marketers — but it can ease their jobs with automation and boost the efficiency of marketing efforts. There are many types of machine learning algorithms. Some simply search and detect patterns, others learn to create something new. All of them can be used for email marketing — here’s how:

• Drafting email copies — they still need editing but it’s a great starting point.
• Writing catchy subject lines — both generating and optimizing your ideas for maximum efficiency.
• Restructuring email campaigns — finding the best structures for automated sequences using historical data.
• Segmentation — looking deeper into your subscribers’ behavior and automatically improving deliverability. 
• Cleaning up email lists — eliminating all the inactive subscribers for the sake of your domain reputation.
• Email retargeting — creating personalized emails and messages to boost sales.
• Recommending certain products — sending data-powered recommendations your subscribers will love.