AI, Meet Spam Filters: A Modern Email Cautionary Tale |
Not every sales or marketing leader is a winner. Case in point: Terrible Terry (a real person, not his real name). Terry was infamous for yelling at individuals until they cried. No joke. During onboarding, we were told, “Terry makes people cry,” as if that were a known part of the job.
But emotional chaos wasn’t the only damage he caused. One of his worst offenses was forcing our team to send daily marketing emails to enterprise prospects with $50k+ contract values — folks who definitely didn’t want a daily check-in. |
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Terrible Terry’s daily email strategy. |
These daily sends went on for months. After Terry left and we were finally free to audit the system, the truth was brutal: Our deliverability had cratered. Our domain was so deeply spam-flagged that we had to rebuild our entire email program from scratch, using a new domain, platform, and process.
Reading Faithe’s email recap on deliverability frameworks took me back to my days with Terrible Terry (thanks, Faithe!). But it also got me thinking about deliverability and how AI is affecting it today.
Validity’s 2025 email deliverability benchmark report found that 1 in 6 legitimate marketing emails never reach the inbox, with AI-generated content now making things worse by triggering spam filters. AI is accelerating everything from copywriting to scheduling, so more teams are walking into traps like Terrible Terry’s, but even faster than before. So today, I’m diving into what AI means for email deliverability — not in theory, but in practice: how it’s tripping up smart teams, what to watch out for, and how to build a deliverability-safe program that still moves fast. |
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How smart teams avoid the AI deliverability burn |
If you're deploying AI for cold outreach or follow‑ups, you’re playing with fire because spam filters are watching for patterns and volume spikes. So any shortcut in scale or automation can backfire hard.
It’s been well-argued that cold outreach has to evolve in a world where “blasting” is dead and relevance is your only defense. Here’s how you can do your part to prevent AI from hurting your deliverability. |
- Cap volume per inbox and ramp slowly
AI has a ceiling. UserGems reports that crossing 200 emails per rep per day consistently hurts deliverability, even if engagement looks fine at first. Sending more too quickly, especially from new or untrusted domains, flags you as spammy at the internet service provider (ISP) level.
→ Instead, stagger send times, rotate mailboxes, and use warm-up tools to avoid triggering rate-based penalties.
- Human-edit your AI output every time
Spam filters are getting better at detecting robotic phrasing, overly structured syntax, and other AI writing patterns. Introducing variation is the new standard for deliverability.
→ Instead, change subject lines, adjust intros, and rewrite CTAs manually to break the pattern recognition most filters now rely on.
- Watch your engagement and know when to douse the flames
Email tools aren’t the only ones measuring open and reply rates. Inbox providers are too. If your open rate falls below 10%, or reply rates dip under 2%, you’re already hurting your domain.
→ Instead, rethink the sequence. Persistent low engagement trains spam filters to deprioritize your future sends, even if the content improves later.
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Overall, AI is great for helping scale effort, but pure automation leads to uniformity — and that’s detectable. Your highest-value leads deserve handcrafted messages, while mid-tier segments might get more AI-generated drafts. But blend them with edited, personalized messages to create a sending fingerprint that feels human.
Advanced senders are even training AI warm-up tools to simulate authentic behavior (i.e., delayed opens, staggered replies, varied response patterns) because authenticity is now a deliverability lever. |
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AI marketing plays that don’t scorch inboxes |
First, if you have a Terrible Terry in your life, I am very sorry. 💐 You’ll get through this.
While AI can accelerate your team's email workflow, speed is only an asset if it doesn’t compromise your deliverability. Spam filters today don’t block content just because it’s machine-written. They flag behaviors, such as low engagement, repetitive phrasing, and mass-sending without variation.
Marketers using AI to accelerate campaigns are also unintentionally triggering spam filters due to a lack of personalization and over-reliance on templates, leading to major drops in inbox placement.
My recommendation: Use AI to start from what already worked, not from scratch. Let your highest-performing past email serve as the seed. Ask AI to adapt tone, reframe CTAs, or reshape it for a different segment. This preserves the DNA of your best content while reducing uniformity and avoiding predictable phrasing that spam filters flag.
Then, consider working natural variability into your sends. Rather than blasting a single template to 10,000 addresses, break that into several micro‑variations (different intros, rearranged sections, alternate subject lines, etc.).
Variants help break patterns that filters train on. List hygiene plays a big role here, too. Campaigns that include low‑quality or unverified addresses raise bounce rates and trigger spam signals.
Finally, insert guardrails into your process: tag AI drafts, require human review, and experiment with transparency. If you run one test version that says “AI-assisted” in the footer, you can build a culture of oversight, signal trust, and future‑proof your sends for upcoming regulations. |
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Leadership says, “We don’t sell in Europe, so the EU AI Act doesn’t apply to us.” |
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Looking at you, Terrible Terry. 👀 |
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That’s the kind of thinking that could quietly burn you later. The EU AI Act became law in August 2024, and it’s the world’s first major regulation classifying AI systems by risk and imposing rules on transparency, data governance, and accountability.
And under Article 2, it applies to any company whose AI outputs reach EU users — yes, even emails or chatbot replies. The law also requires clear labeling of AI-generated content (Article 50) and flags potential risky use cases, such as manipulation or unfair targeting. That makes human oversight, output review, and labeling necessary legal checkboxes and sales/marketing best practices. Even if you never intend to expand into European markets, your AI tools might.
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→ Translation: Your stack, your vendor, or your AI workflows might get nudged toward compliance. And that could force changes you’ll feel stateside, too. |
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Skylar has spent more than a decade creating sales and marketing content that works. She's held key content and leadership roles at TechnologyAdvice, Equifax, and Intuit — turning complex ideas into strategies and stories that drive growth. |
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