According to Klaviyo's 2026 AI consumer trends research, 41% of consumers say they've purchased a product AI recommended within the past 6 months.
Marketers are using AI to pull and update segments, create email copy and design, run tests at scale, and tailor timing and channel to each shopper.
Not only does AI for email marketing reduce the amount of manual work for marketers, but it also has the potential to increase revenue through volume and more granular targeting.
In this guide, we'll take a closer look at how to apply AI for email marketing across several steps in the process.
What is AI for email marketing?
AI for email marketing uses machine learning to automate and optimize tasks like audience segmentation, content creation, send timing, and testing based on your customer data.
Within guardrails and under human supervision, AI can also suggest email campaigns and flows that marketers may not have thought to set up, through performance and audience analysis.
Ideally, AI marketing functionality is embedded within a CRM with a built-in customer data platform (CDP). This is so that your AI marketing agent is informed by real-time customer data such as stated preferences or actual behaviour.
Without this AI-data integration, your AI agent won't be able to ground its product and offer recommendations in reality. Customer data is what ensures your AI email marketing is personalised to each shopper, rather than sending them AI slop.
Setting AI email marketing guardrails
AI speeds up production and testing, but without clear guardrails, it may over-message underperforming segments, push up unsubscribes, and damage your sender reputation.
As consumers are more exposed to AI, they're becoming more sensitive to low-quality AI content. According to Klaviyo's aforementioned AI consumer trends research, nearly 1 in 5 consumers say they see low-quality or generic AI content from brands on a weekly basis. For 32% of those people, it makes them trust brands less.
Here are some guardrails to set up when you're getting started with AI for email marketing:
- Keep a human in the loop. Nothing sends without a marketer reviewing and approving it. AI drafts and recommends, but a person signs off.
- Build custom guardrails. Configure specific content rules that apply to your brand, such as product exclusions, legal disclaimers, banned phrases, and any regional considerations.
- Conduct regular quality checks. On a weekly or monthly basis, review every generated output to make sure it meets structure, deliverability, and conversion standards.
From email strategy to content: using an AI marketing agent
AI marketing agents have changed the way email campaigns and flows are conceived, created, and measured.
What used to be hours of work for each step—strategy, segmentation, content creation, testing, and performance evaluation—has now collapsed into faster iterations between human marketers and AI agents.
Here's what's changed in email marketing workflows since the advent of AI agents:
- Marketers are generating campaigns with prompts. Single prompts can now build complete campaigns in one go, including audience, copy, channel coordination, and timing. When AI marketing agents are embedded within a CRM, their suggestions are informed by real segments, product catalogues, and performance history, so they're not guessing.
- Marketers are refining copy and design through AI conversations. Without starting over, marketers are asking AI agents to refine campaigns through more prompting and finetuning until they're satisfied with them.
- Marketers are uploading product photography to seed campaigns. With a brief, AI agents can read images, pull brand settings, build an audience, and draft messages with creative references to the visual.
With an AI marketing agent, email campaign creation happens in conversational prompts with human review. Combined with AI-enabled testing that determines the right version for each subscriber, AI for email marketing can produce more versions at scale and increase the likelihood of engagement and conversion.
How AI improves email segmentation with predictive analytics
Predictive analytics uses AI and machine learning to see how the trends, patterns, and relationships in the data today are likely to play out in the future.
Here are some examples of predictive analytics and how marketers can use them to improve their email marketing:
- Average time between orders: Build segments of customers with similar buying cycles, so you can target those who don't purchase frequently with offers that incentivise them to purchase more often.
- Average order value (AOV): Segment your customers based on AOV and create targeted campaigns and flows aimed at incentivising them to spend above a certain amount in exchange for a perk.
- Customer lifetime value (LTV): Build high-spender segments and use these segments to find new customers via lookalike audiences in Facebook Ads or similar audiences in Google Ads.
- Churn risk prediction: Use churn risk in combination with expected date of next order to better understand whether you should be targeting someone with a win-back campaign or even more communication for loyal customers.
- Best cross-sell date: Trigger a flow based on someone's best cross-sell date to see if you can encourage their next purchase faster.
- Expected date of next order: Here, you can segment based on a number of scenarios. For people who purchase consistently, you can push them to your loyalty programme. For people who purchase inconsistently, you can run some A/B tests to see what speeds up time to purchase.
Every Man Jack, for example, sets their reorder flow to send on, or slightly before or after, each customer's predicted next order date. They also send AI-powered re-stock reminders, triggered by the customer's predicted next order date.
As a result, within a 90-day period, 12.4% of Klaviyo-attributed revenue was generated with predictive analytics.
Using AI to personalise content and send time with testing
Generative AI can draft email copy and pull in dynamic product recommendations grounded in your customer data and brand voice. But it can also test many more versions of that copy to make sure each shopper gets the variant they're most likely to engage with.
Running A/B tests on your emails lets you know the specifics of what resonates most with your audience: which subject lines, offers, and CTAs they'll convert on.
AI unlocks advanced A/B testing to identify profile patterns that predict which version each individual customer is most likely to engage with, and sends that version to them, instantly.
Personalisation also means sending emails at the right time. AI can determine when each subscriber will engage based on when they've historically opened and clicked. Rather than adhering to one send time for your whole segment, each customer gets their own.
Extending AI for email to text message marketing
Text message marketing sends short, time-sensitive messages to subscribers who have opted in with their mobile number, while email carries richer, longer-form content like detailed product stories and full catalogues.
To build a text message strategy that complements email, you can use AI to choose the right channel and timing per person. The thing is, the “right channel” is something that's constantly changing for each customer: one month they may really engage with email, but the next month they switch to buying from text.
AI that's embedded within your CRM can keep up with these shifting preferences and automatically send messages on the channel your customers engage with most recently.
When email, text messages, and other touchpoints read from one shared, real-time profile, AI can sequence a customer's experience across channels instead of blasting each one in isolation. This reduces message fatigue and increases the likelihood of conversion.
How to choose an AI email marketing platform
Your AI email marketing initiatives are only as good as the customer data they're based on. Klaviyo is the autonomous B2C CRM with a built-in CDP that AI marketing agents can draw from to make sure every message is relevant and sent to the right person at the right time.
With Klaviyo, brands can use AI to:
- Generate email campaigns from plain-text prompts. With Klaviyo Composer, brands can identify marketing opportunities, create campaigns, optimise performance, and take action faster, all from a single AI conversation.
- Reach customers at the right time. With smart send time, marketers can learn about their customers and reach them at the optimal time with their email campaigns and flows.
- Predict what customers will do next. With predictive analytics, marketers can encourage higher spend, speed up time to purchase, and prevent churn by segmenting customers with AI.
- Keep up with shifting channel preferences. With channel affinity, AI automatically determines which channel each customer is most likely to engage with, which reduces message fatigue and increases the likelihood of conversion.
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