2025 State of AI Email Marketing Report with Key Trends

AI Adoption and Usage Stats

• 63% of marketers employ AI in campaigns.
• 91% use AI in workflows, primarily for automation and personalization.
• 87% of businesses adopting AI apply it to email marketing.
• 47% use AI for campaign generation; 49% for content creation.

The Shift from Manual to AI-Led Campaigns

Gone are the days of generic blasts. AI now:

• Generates content tailored to each subscriber.
• Predicts open times and engagement.
• Automates entire campaign workflows.

HubSpot and Salesforce emphasize this transition: marketers are no longer campaign managers—they’re strategy architects.

Hyper-Personalization

Dynamic AI content tailors product recommendations, offers, and layouts in real time. Litmus calls this “privacy-proofed personalization.”

Predictive Analytics

AI helps marketers take action before losing a lead by forecasting client lifetime value, purchase cycles, and attrition.

AI-Powered Automation

Real-time adaptation has been included to smart drip campaigns. AI slows cadence when a user ignores emails. AI accelerates if they use it extensively.

Conversational AI & Interactive Content

Emails now feature embedded chatbots, quizzes, and calculators—turning passive messages into active experiences.

AI and Email Deliverability

AI protects inbox placement by:

• Avoiding spam traps.
• Optimizing send times by individual behavior.

1. E-commerce: Hyper-Personalization and Smarter Cart Recovery

AI has emerged as the foundation of contemporary email campaigns in the e-commerce sector. Up to 40% more money is being made by retailers who use AI-driven customisation techniques than by those who only use generic promos.

AI actively adjusts to each customer's experience rather than only making product recommendations. For example, a single reminder message is no longer sufficient for cart recovery emails. AI instead assesses whether a discount, a scarcity-based push ("only 2 left in stock"), or a social proof component ("150 people bought this item this week") will increase a shopper's likelihood of responding. Based on past exchanges, it even optimizes the voice tone and send time.

Fashion brands, for example, use AI to suggest complementary products based on browsing history, while electronics retailers leverage predictive analytics to forecast when a customer may be due for an upgrade. These strategies keep customers engaged, improve average order value, and dramatically reduce cart abandonment.

2. SaaS & Technology: Smarter Onboarding and Retention

For SaaS companies, onboarding and customer retention are make-or-break moments. AI-powered email campaigns are now central to these strategies. By analyzing customer usage data, AI can predict which features a new user is most likely to find valuable and then trigger personalized onboarding emails.

Instead of sending every customer the same “getting started” sequence, AI segments users by behavioral triggers—for example, whether they’ve set up an integration, created a first project, or invited teammates. Based on this, the system sends the most relevant guidance at the right time, significantly reducing churn.

Take the example of a SaaS project management tool: if AI detects that a user has yet to invite team members after a week, it may send an email emphasizing the benefits of collaboration, complete with a one-click invite option. Other users who are actively creating projects might receive tips on automation or advanced features instead.

The outcome? Higher product adoption, lower churn, and a smoother path from trial to paid subscription.

3. Healthcare & Finance: Personalization with Compliance and Trust

Few industries face compliance and privacy challenges as intensely as healthcare and finance. Yet, these sectors are also proving how AI in email marketing can deliver secure, timely, and personalized communication while adhering to regulations.

In healthcare, AI is being used to send personalized appointment reminders, prescription refill alerts, and wellness updates—all tailored to patient needs and delivered securely under HIPAA guidelines. Hospitals and clinics also leverage AI to segment patients by condition, age, or treatment plan, ensuring that messaging is both relevant and compliant.

When suspicious activity is identified in the financial industry, AI-driven fraud detection connects with email workflows to provide real-time warnings. When an unexpected transaction occurs, customers are alerted right away, and AI tailors the message's severity and next-step instructions according to account risk.

Banks and insurers also use AI for financial wellness campaigns—delivering tailored advice on saving, investing, or policy renewals, aligned with customer goals and behaviors. The challenge lies in balancing personalization with privacy, but the payoff is stronger trust, improved engagement, and better long-term loyalty.

1. Pipedrive: AI-Powered CRM for Smarter Drip Campaigns

Pipedrive, a well-known sales CRM platform, has been integrating AI deeply into its email marketing workflows. Their AI models analyze customer interaction data—such as open rates, click behavior, and historical purchase patterns—to generate highly personalized drip campaigns.

For example, a SaaS company using Pipedrive’s AI features can automatically segment leads into micro-groups based on buying signals. Instead of sending a one-size-fits-all follow-up, the AI predicts the most relevant messaging and timing. The results are clear: higher engagement, faster deal cycles, and reduced manual workload for sales and marketing teams.

This use case demonstrates how AI in email marketing not only saves time but also enables sales reps to focus on relationship-building rather than repetitive campaign setup.

2. Adobe: Predictive Analytics Driving Personalization at Scale

Adobe’s 2025 Digital Trends Report highlighted how enterprises are using predictive analytics to deliver truly personalized experiences at scale. Adobe Experience Cloud leverages AI (powered by Adobe Sensei) to anticipate customer needs before they’re explicitly expressed.

Adobe's predictive analytics, for example, can anticipate which product a consumer is most likely to purchase next in the retail sector and then send them a personalized email with recommendations. After moving from rule-based segmentation to predictive AI-driven personalization, a multinational clothing company partnered with Adobe reported a 28% boost in email-driven revenue.

This example underscores the power of AI to move beyond basic personalization (“Hi [First Name]”) into proactive, context-aware recommendations that feel intuitive and relevant to the customer.

3. McKinsey: Uneven AI Adoption and the ROI Divide

McKinsey’s 2025 State of AI research paints a broader picture of adoption trends across industries. While nearly 63% of marketers report using AI in some capacity, only a smaller group of leaders are scaling AI effectively across their workflows.

These AI leaders are seeing 2–3x higher ROI compared to peers who are still experimenting with isolated pilots. For example, financial institutions that deployed AI for both fraud detection and hyper-personalized customer outreach saw measurable gains in both revenue protection and customer trust.

However, the report also notes that uneven adoption persists. Many organizations lack the internal expertise, clean datasets, or change management frameworks required to unlock full AI potential. This creates a widening gap between early adopters and laggards—one that may decide market leaders for the next decade.