AI and the Evolving Landscape of Email Marketing

This blog expands upon the topics discussed in our webinar, "From Insights to Strategy: Using Negative Marketing Signals and Campaign Analytics to Excel in Email Marketing."

In the rapidly changing world of email marketing, some challenges persist year after year while new ones emerge. Four areas continue to define the conversation: artificial intelligence (AI), privacy regulations, performance tracking, and email deliverability.

When we first published this post, AI in email marketing mostly meant a marketer pasting a prompt into ChatGPT to get five subject line options. Three years later, AI writes the email, AI summarizes the email, and in a growing number of inboxes AI decides whether the email is worth surfacing at all. The questions have changed along with it. Ownership of AI-generated content is still working its way through the courts, but disclosure obligations have arrived, and a new interpretive layer now sits between every sender and every subscriber.

Here is where each of those issues stands, and what email marketers should do about them.

 

AI and Ownership of Content

Artificial Intelligence (AI) has garnered immense interest among marketers due to its potential to streamline processes, enhance content creation, and analyze results.

 

However, AI also raises questions and challenges. One pressing issue is determining ownership of content generated by AI tools. Different platforms have varying terms of service, with some granting users unlimited ownership while others retain certain rights.

Marketers are advised to read and understand the terms of service governing these AI platforms to ensure clarity on content ownership.

Three years on, that advice has not changed, but the terms have. Before your team standardizes on a tool, confirm four things in writing:

• Ownership. Do you own the output, and can you use it commercially without attribution?
• Training. Are your prompts and uploads used to train the vendor’s models, and can you opt out?
• Indemnification. Will the vendor defend you if the output draws a copyright claim? Enterprise tiers frequently offer this. Free consumer tiers frequently do not.
• Confidentiality. Is customer data, list data, or unreleased offer detail leaving your environment when someone pastes it into a prompt?

That last one is where most marketing teams have exposure and the least documentation.

 

Where the AI Copyright Question Actually Stands

When this post first ran, the legal picture was pure speculation. It is no longer. It is still unresolved, which is a different thing.

The New York Times sued OpenAI and Microsoft in December 2023 over the use of its articles in model training. A federal judge allowed the bulk of the case to proceed in April 2025, it has since been consolidated with similar publisher suits, and it remains in discovery. In July 2026, the Times and several other publishers asked the court to sanction OpenAI over its handling of that discovery. No court has yet issued a final ruling on the central question of whether training a model on copyrighted material is fair use.

The largest number to date came from a different case. Anthropic agreed to a class settlement of roughly $1.5 billion covering approximately 500,000 books, announced in September 2025, working out to about $3,000 per covered work. Notably, that settlement addressed how the material was obtained rather than granting any license for future training.

For an email marketer, the practical read is this. The litigation risk sits with the companies building the models, not with the marketer writing a subject line. What sits with you is everything downstream: whether you can claim ownership of the output, whether your vendor will stand behind it, and whether the claims in the copy are substantiated. Those are contract and compliance questions, and they are answerable today.

 

AI Is Now the First Reader of Your Email

The biggest AI shift in email marketing is not that AI helps you write the email. It is that AI reads the email before your subscriber does.

Gmail moved AI summaries into the inbox at scale in early 2026 through its Gemini rollout, reaching billions of accounts. Apple Mail has generated summarized previews since Apple Intelligence shipped with iOS 18. Outlook does the same through Copilot. Alongside summarization, relevance-based sorting has quietly retired the old assumption that the newest message sits on top.

The consequence is concrete. The preheader you wrote may never be seen, because a model rewrote it. Your carefully sequenced narrative may be flattened into two lines and a to-do item. Send time optimization matters less when arrival order is not what determines placement. And open rate, already degraded by Mail Privacy Protection, becomes an even weaker proxy for attention.

 

The email that performs in this environment is the email that summarizes cleanly. One core message. The offer stated in the first two sentences rather than built up to. Live text instead of a single hero image, because testing by inbox specialists has repeatedly shown that image-only sends produce vague or actively unhelpful AI previews. Real alt text, not file names. Plain language rather than clever misdirection. An explicit call to action a model can identify and restate.

Summarizability is the new above the fold.

How to write email that survives AI summarization

• Lead with the offer or the ask. Do not bury it after a story.
• One goal per send. Multi-promotion emails summarize badly and get deprioritized.
• Balance images with live, selectable text. Never ship an image-only email.
• Write alt text that carries the message, not the file name.
• Use plain, literal language in the first paragraph. Save the wordplay for the body.
• Make the call to action an unambiguous verb phrase.
• Keep semantic structure. Headings and lists give the model something to anchor to.
• Test how your send actually summarizes in Gmail and Apple Mail before the full deployment.

 

The Disclosure Rules Caught Up

In 2023, AI regulation was a hypothetical. In 2026, it is a compliance calendar.

The Federal Trade Commission has been enforcing against AI-related marketing claims since it launched Operation AI Comply in 2024, bringing more than a dozen actions against companies making inflated or unsubstantiated claims about AI capability. The standard is the familiar one under Section 5. What is new is where it is being applied. The Endorsement Guides reach synthetic testimonials and AI-generated personas the same way they reach human ones, and recent FTC settlements in lead generation show how quickly that exposure travels down a marketing chain.

At the state level, New York General Business Law Section 396-b took effect on June 9, 2026. It requires advertisers to conspicuously disclose the use of an AI-generated synthetic performer, meaning a digital asset built to look like a person who is not a real, identifiable human. Penalties run $1,000 for a first violation and $5,000 for each violation after that, enforced by the state attorney general with no private right of action.

Colorado went the other direction. The state enacted SB 189 in May 2026, replacing the 2024 Colorado AI Act with a narrower framework centered on disclosure and transparency for automated decision-making technology, and moving the effective date to January 1, 2027. In the EU, the AI Act’s high-risk obligations have been provisionally pushed to 2027, though the transparency obligations are the ones most likely to touch marketing teams. For a fuller picture of how state AI laws affect marketing compliance, the landscape is moving faster than most compliance calendars are built to track.

The pattern across all of it is the same. Regulators are converging on disclosure and substantiation rather than on prohibition. For email specifically, that means: if AI generated a person, a testimonial, a review summary, or a performance claim in your message, assume a disclosure or substantiation obligation attaches, and keep a record of which tool produced what.

 

AI Made the Partner Channel Louder

Here is the part that does not show up in most AI-and-email articles. Generative tools did not just make it easier for your team to write email. They made it effectively free for every affiliate, partner, and third-party mailer promoting your brand to produce unlimited creative variants.

A partner who once ran three subject lines can now run three hundred. Body copy that used to come from an approved template is now generated, rephrased, and regenerated between deployments. Each variant is a fresh opportunity for an unsubstantiated claim, a missing disclosure, a misleading subject line, or an offer you never approved. And when a consumer complains or a regulator asks, the brand answers for it, not the affiliate.

CAN-SPAM's prohibition on deceptive subject lines does not distinguish who, or what, wrote the subject line. A model-generated variant carries the same obligation as one a copywriter typed by hand. The operational problem is arithmetic. Spot-checking a sample of partner emails was a defensible process when partners produced a handful of creatives per campaign. Against machine-generated variation at scale, sampling produces a rate of coverage close to zero. Discovery and monitoring have to be continuous, automated, and run across the emails you did not know were being sent.

That is the gap LashBack was built to close. ComplianceMonitor scores partner-sent messages against your compliance and brand rules, BrandAlert surfaces unknown placements of your brand in third-party email, and ListMonitor manages your seed lists and enforces exclusivity.

 

An AI Email Governance Checklist

If you take one thing from this post, take this list.

1. Inventory the AI tools your team and your partners actually use, including the ones nobody approved.
2. Record each tool’s terms on output ownership, training data reuse, indemnification, and data confidentiality.
3. Require human review before send. AI drafts, a person approves.
4. Substantiate every claim in the copy, including the ones the model produced confidently.
5. Disclose synthetic performers, AI-generated testimonials, and AI personas wherever they appear.
6. Keep opt-out and suppression discipline intact. Automation volume does not change CAN-SPAM obligations or state law.
7. Monitor the partner channel continuously rather than by sample.
8. Document the workflow. If a regulator asks who approved what, the answer should not require reconstruction.

 

Frequently Asked Questions

Who owns content created by AI tools?

Ownership depends entirely on the terms of service of the tool you used. Most major platforms now assign output rights to the user, but free and consumer tiers often reserve broader rights than enterprise plans, and some reuse your inputs for training. Confirm ownership, training reuse, and indemnification in writing before standardizing on any tool.

Is AI-generated content protected by copyright?

Not on its own. The U.S. Copyright Office has consistently held that material generated by AI without sufficient human authorship is not eligible for copyright registration. Work that combines meaningful human creative input with AI assistance can be protected, but only to the extent of the human contribution. For marketers, this mainly limits your ability to stop others from reusing purely AI-generated assets.

Do I have to disclose that an email was written using AI?

There is no blanket rule requiring you to disclose that AI drafted your copy. There are specific rules for specific uses. New York requires conspicuous disclosure of AI-generated synthetic performers in advertising as of June 2026, and FTC standards on endorsements and substantiation apply to AI-generated testimonials, personas, and claims exactly as they do to human ones.

What are AI email summaries and how do they affect marketing emails?

AI email summaries are machine-generated previews that inbox providers display in place of, or above, your own preheader text. Gmail generates them through Gemini, Apple Mail through Apple Intelligence, and Outlook through Copilot. The practical effect is that the first impression of your email is now written by a model, not by you.

How do I optimize an email for Gmail and Apple Mail AI summaries?

Front-load the offer in the first two sentences, keep each send to one core message, and use live text rather than a single image. Add descriptive alt text, write plainly instead of cleverly at the top of the message, and make the call to action an explicit verb phrase. Then test how the send actually summarizes before full deployment.

Does using AI to write emails hurt deliverability?

Not by itself. Mailbox providers evaluate authentication, sender reputation, engagement, and complaint rates rather than whether a human typed the copy. AI does create indirect risk: higher send volume, near-duplicate variants across a partner network, and weaker list hygiene all damage reputation. Keep SPF, DKIM, and DMARC in place and keep engagement-based segmentation tight.

What is the biggest AI-related compliance risk in email marketing?

The partner channel. Generative tools let affiliates and third-party mailers produce unlimited creative variants at almost no cost, which multiplies the surface area for misleading subject lines, missing disclosures, unsubstantiated claims, and unapproved offers. The brand carries the regulatory exposure for those messages even though it never wrote them.

How can brands monitor AI-generated emails sent by affiliates?

Through continuous discovery and automated monitoring rather than manual sampling. Effective programs find third-party emails carrying the brand, score every message against defined compliance and brand rules, and alert on violations in time to remediate. LashBack ComplianceMonitor, BrandAlert, and ListMonitor are built for exactly this pattern of oversight.

 

Conclusion

Three years ago, AI was a promising tool with unclear rules. Today it is embedded in how email gets written, how it gets delivered, and how it gets read. The ownership questions are still moving through the courts. The disclosure questions largely are not: those obligations exist now and are being enforced.

The email programs that hold up under this are the ones treating AI as a production accelerator wrapped in human review, not as an unsupervised author. That is true for your internal team, and it is doubly true for the partners sending on your behalf.

See how LashBack discovers and monitors the emails being sent on your behalf, so AI-scale creative volume does not become AI-scale compliance risk. Request a demo.

Updated: August 5, 2026