Exploring the impact of GenAI on email marketing: Turning hype into value in MarTech

Marketing is one of the first areas in which AI tools have quickly become adopted by professionals seeking to work faster and more creatively. Email marketing hasn’t been left out, either. It’s one of the oldest and most reliable digital channels, in which personalization, design, and branding play a crucial role, making it both a promising and challenging area for GenAI implementation.

Email creation often requires technical skills, but developers are rarely good marketers. Conversely, marketers aren’t always tech-savvy. AI helps bridge this gap by simplifying workflows, but as it does, it also introduces new challenges. Let’s explore them step by step.

Key takeaways

1. Generative AI is amazing for content and idea generation, especially for speeding up brainstorming and drafting.
2. Treat AI like a junior assistant. Educate it with your style, personas, and rules, and it will grow into a partner.
3. Divide and conquer. Break complex tasks into smaller, controlled steps to maintain consistency in quality.
4. Automate the routine. Let AI handle anything repetitive. Save your energy for strategy and creativity.
5. Don’t over-delegate. AI is powerful, but you decide where the human touch matters most. That balance is what makes your emails truly resonate.

AI in email marketing: What do marketers want?

If you look at this chart from Litmus (now Validity), you can see where marketers expect the most impact from AI in email marketing next year. The top answers are clear: creating emails and personalizing them.

The ideal AI workflow that email marketers would like to see looks like this:

• AI immediately generates a ready-made email or even an entire sequence of emails for the campaign, aligned with your brand guidelines, tone of voice, and coding standards for all email clients and accessibility requirements;
• each version is personalized for different audience segments, based on your own customer personas. 

What do email marketers actually face? These are the challenges:

• AI ​​is often viewed as a junior-level assistant who can only handle simple tasks;
• the code quality is poor, design doesn’t follow brand guidelines, and both structure and copy need to be reworked; the images usually have to be replaced;
• the tools can produce something, but the effort to correct and fix it often feels bigger than just doing it manually;
• due to a modular approach, the results often look too similar. The emails feel a bit generic, predictable, and sometimes even unnatural, like something you’d never write that way. And this hurts engagement.

In this article, I’ll focus on how to use GenAI’s existing capabilities and the tools built on them to create high-quality emails that meet all the marketer’s requirements — brand consistency and the technical side.

Five levels of email content generation 

Creating email content is a multistage process that includes goal definition, briefing and planning, and creating the copy, design, and layout. After that, review and approval, scaling and optimization, deployment, and, finally, real-time personalization are needed.

But the real challenge appears in the creation stage. The email needs to be well written, on-brand, designed to match guidelines, and coded properly so that it works across all clients and meets accessibility standards.

The levels of email production are as follows:

1. Single-line elements: These include subject lines, preheaders, or headers. 
2. Paragraph text inside the email: These are paragraphs with different formatting, such as bulleted lists, highlights, links, and more. 
3. Content blocks or modules: These comprise structural elements, including headers, text paragraphs, buttons, CTAs, and links, in a single style.
4. The whole email: This consists of several content blocks that are united by a single idea and arranged in the correct sequence, taking into account the brand component and marketing goal of the email.
5. A complete email series: This refers to an entire email campaign, structured logically to achieve a goal.

1. Single-line elements

These are subject lines, preheaders, or headers. It’s a natural starting point because short text is easy for AI to produce and easy for us to test.

How to use AI effectively on this level:

• general tools, such as ChatGPT, Gemini, and Perplexity, are especially handy;
• provide context for your email and the necessary information. To ensure more predictable results, try paying attention to these points;
• instead of just saying “write me a subject line,” you can guide AI with frameworks, such as Cialdini’s principles of persuasion;
• use specialized tools with pre-built prompt templates, such as the AI subject line generator inside the Stripo editor. These are tested and optimized for brainstorming or for creating email copy on the fly. Instead of reinventing prompts every time, marketers can rely on these libraries to generate consistent, brand-friendly subject lines and headers much faster.

2. Paragraph text inside the email

Beyond surface-level elements, such as emojis and tone, AI now needs to handle elements, such as paragraphs, bulleted lists, highlights, links, and more. That’s already a step closer to real production content.

Many tools, such as Stripo, already offer built-in text generation and text improvement features. These let you to draft or refine content directly within the editor, without having to switch between platforms. It’s convenient, but the challenge remains: The text must still fit the broader context of the email.

Because no text in an email exists on its own, each piece has to work together with the headlines, images, buttons, and descriptions. Real power comes when everything feels cohesive and consistent. And that’s where AI still needs our guidance to make sure the entire structure of the email makes sense as a whole, not just line by line.

How to use AI effectively on this level: Provide context and give examples. A vague prompt produces generic output, while a structured prompt with personas, tone of voice, and context produces something that feels real and relevant. In other words, better input, better output.

3. Content blocks or modules

With content blocks or modules, we’re not just addressing text blocks but entire content modules, which are much more complex mechanisms. They combine copy, visuals, buttons, and formatting into reusable building blocks.

Think of it this way: SpaceX doesn’t build a new rocket from scratch every time. They reuse and adapt standardized components. The same principle applies to email production. Instead of reinventing the wheel for every campaign, marketers can rely on structured blocks and modules.

You don’t even need to recreate your modules; you just reuse them. With modular email design, you can create complex structures, describe their dependencies, and let AI manipulate them safely.

How to use AI effectively at this level:

• when you have a structured description of a module and its components, you can simply connect a data source, for example, a blog article. With your brand style defined, AI can instantly generate the content in your tone of voice and fill the module automatically;
• if you’re preparing a webinar, you can provide a link to the event details. AI can quickly assemble a full announcement or invitation module with all the right information, formatted and styled for your brand;
• for making interactive modules, you can describe what you want to ask, or provide a document with the survey questions. AI can then generate a working interactive block that renders across email clients. Tasks that required days of coding can now be completed in minutes.

We already have public libraries of free interactive modules. These can be reused, customized, and combined with AI-driven content. Instead of reinventing the wheel, marketers can pick from these libraries, and let AI adapt them for specific campaigns.

4. Entire email in brand design

From a production perspective, an email is made up of several content blocks united by a single idea. These blocks are arranged in the correct sequence while maintaining brand consistency and aligning with the email’s marketing objective. Now, our task is to scale the approach we’ve applied to these modules and create a fully fledged email in a consistent brand style.

At this level, when working with AI, special attention should be given to the following points:

1. Brand consistency is about how a company shows up in the inbox every single time. While AI can draft copy, it doesn’t have the full context of brand guidelines, long-term positioning, or subtle emotional cues that make a brand feel authentic.
2. The technical side is equally crucial. Rendering is one of the toughest challenges in using AI in email production. What looks perfect in Apple Mail may break in Outlook. A layout that works beautifully on a desktop might not display correctly on a mobile device. 

Generally, AI struggles at these tasks, but scaling the module approach and designing the entire email are possible if you have the right building blocks.

You need to prepare the following system elements:

• a library of ready-made modules that will combine copy, visuals, buttons, and formatting into reusable building blocks;
• a source of new information for creating an email, such as a link to an article or a webinar plan for which you want to prepare an email sequence;
• email templates with branding.

AI can select the right modules, fill them with data according to your rules, and arrange them in the correct order inside the template. As a result, you get a complete email that’s already aligned with brand guidelines.

How to use AI effectively on this level: To put this into practice with AI, you need a common, formalized language that will help you define what data you feed into it, what output you expect to get, and how you’ll improve it step by step.

Here’s an example of how I implemented this using ChatGPT:

• I created a vocabulary of terms and rules for our interactions. The vocabulary included key interaction points: assets, strategy, brief, modules, mapping, and email payload;
• then I shared it with myGPT. This way, the model and I spoke the same structured language;

Here’s what the strategy description looked like in the vocabulary:

• divide and conquer. Any long, complex prompt you give to AI has limitations, such as timeouts, a lack of context, and inconsistent results. But if you break the task into smaller, structured steps, you can always control the outcome.

That’s why having a clear vocabulary and a step-by-step process matters. Once you define the stages of email creation, AI delivers more consistent and controllable results.

5. Email sequence

Take webinars as an example. They require the same routine set of emails every time: announcements, reminders, and follow-ups. This process typically requires several hours of repetitive work. But once you’ve written the briefs once with modules, templates, and landing page data, AI can regenerate the entire flow in minutes.

Here’s how to structure the new workflow:

1. Set up: Give AI as much context as possible, including your company, tone of voice, and personas with real descriptions of jobs, pains, gains, and motivations. Add your past landing pages, sample emails you like, and references. The more context you provide upfront, the better and more consistent the results.
2. Describe the task in as much detail as possible: For example, prepare a set of emails to support a webinar, based on the landing page.
3. Strategy and briefs: AI generates both the strategy and the briefs for each email in that sequence. A key advantage is that every stage can be saved and reused. So, once you’ve defined the rules for one webinar, you can apply them again for the next.
4. Adjusting with prompts: Thanks to the pre-prepared vocabulary, everything is structured, and you can easily tweak any single part or even an entire stage. 
5. Module selection and filling: AI helps you find the right module and fill it with contextual data (text, visuals, and links). 
6. Review and deployment: In Stripo, you can keep all your emails neatly organized in folders and then export them to whatever platform you use with a single click. This ensures a seamless workflow, from generation to sending.

Thus, by smoothly moving from working with a single line to working with entire emails and series, you can make AI a reliable assistant in email production.

The future of AI in email marketing: From chatbots to strategic partners

Let’s see the future of AI in email marketing. Over time, AI will begin solving problems on a human level. For example, it will analyze which email flow is more effective for a webinar, suggest optimal times for sending reminders, or adapt calls-to-action depending on the audience segment.

In other words, it becomes your strategic partner. This is where the future of email personalization begins.

Ways to use AI in email at this stage:

• you can ask for feedback. Take a finished email, attach metrics, such as click maps or engagement rates, and then ask AI, “What could be improved?” AI will review clarity, conciseness, relevance, grammar, and formatting and propose specific changes;
• you can teach AI to apply these recommendations to improve emails, conduct tests, and then use the best emails for the campaign. 

Today, we see fast-growing integrations through the MCP protocol, which makes it easy to connect large language models with different data sources and services. In addition, agent-to-agent protocols are emerging, allowing tools to communicate directly and delegate tasks to specialized services.

This means AI will become part of the ecosystem, orchestrating actions across platforms.

How will this affect email editors?

The evolution of email editors has followed the path from raw HTML, then WYSIWYG editors, which made design more visual, to drag-n-drop tools that let us work with blocks, such as text, images, and buttons.

And then came modules, which are reusable, more complex structures we could drop into emails like Lego bricks.

This shift will make email editing more intuitive and allow marketers to maintain control without manually adjusting the layout.

Wrapping up

Generative AI is great for generating content and ideas, so be sure to use it to speed up brainstorming and drafting. Combining AI with modern email editors and a modular design system will soon help you create higher-quality, more personalized, and more consistent emails while also speeding up your technical workflow.

Let’s continue experimenting, sharing best practices, and pushing the boundaries of email.