Anastasia Braitsik is a global authority in SEO and digital marketing, renowned for her ability to decode the complex intersection of data analytics and human-centric content. With years of experience leading high-scale marketing initiatives, she has consistently championed the idea that while algorithms drive visibility, it is the resonance of the brand voice that secures long-term loyalty. Today, she joins us to discuss a significant shift in the email marketing landscape, where technical perfection is being overshadowed by the need for authentic, human-sounding communication.
In this conversation, we explore the evolving role of tone as a primary performance lever in an AI-driven world. Anastasia breaks down why traditional personalization is losing its edge, the specific linguistic traps that signal low-effort automation, and how Gen Z is leading a broader movement toward radical authenticity. She also provides actionable frameworks for integrating brand voice into AI workflows and designing tests that measure emotional impact rather than just clicks.
While basic personalization like using a recipient’s name often sees lower engagement, a human-sounding tone has become a primary driver for staying subscribed. Why is this shift occurring now, and how can brands balance automation with the emotional depth needed to build trust?
The shift is occurring because consumers are becoming immune to the “table stakes” of automation; seeing your first name in a subject line no longer feels like a personal touch, it feels like a programmed trigger. Recent data from Adobe Express highlights this clearly, showing that while only 26% of people care about basic personalization, a staggering 68% say tone is the reason they stay subscribed. People are craving a sense of genuine connection in a digital landscape that feels increasingly automated and cold. To balance this, brands must move away from the “set it and forget it” mentality of automation and start using technology to facilitate, rather than replace, human warmth. Trust is built when a brand sounds like a person who understands your needs, with 37% of consumers explicitly stating they trust brands more when their emails feel like they were written by a human.
Overly polished language and pushy sales tactics are frequently cited as the biggest turn-offs for modern consumers. What specific linguistic patterns signal “low-effort” communication to an audience, and what step-by-step adjustments can marketers make to ensure their AI-generated drafts feel more intentional and less wordy?
Low-effort communication is usually betrayed by “corporate-speak”—those overly polished, flowery phrases that take many words to say very little. In fact, 78% of consumers report that pushy, sales-heavy language is their biggest turn-off, and 46% are frustrated by wordiness. When an email feels too perfect or follows a rigid, “AI-typical” structure, it loses its soul and signals to the reader that no real thought went into the message. To fix this, marketers should first strip away unnecessary adjectives and “marketing fluff” that AI tends to hallucinate to fill space. The second step is to inject intentional imperfections, such as varied sentence lengths or a more casual opening, to break the robotic rhythm. Finally, always read the draft aloud; if it feels like something you wouldn’t say to a colleague over coffee, it’s still too polished and needs a rewrite.
Younger audiences, specifically Gen Z, are exceptionally skilled at identifying AI-generated content and are highly sensitive to tonal shifts. How should marketing strategies evolve to meet these higher authenticity standards, and what are the risks of relying on generic AI outputs when targeting this demographic?
Gen Z serves as the “canary in the coal mine” for the future of content because they have spent their entire lives filtering out digital noise. A significant 72% of this demographic says tone directly dictates their subscription habits, and they are the most confident group when it comes to spotting AI-generated text. The risk of using generic AI outputs with Gen Z is immediate disengagement; they value transparency and can feel when a brand is being “inauthentic” or lazy. Marketing strategies must evolve by prioritizing “unpolished” excellence—content that feels raw, direct, and honest rather than a sanitized version of a brand’s message. If you lose their trust through a robotic tone, you aren’t just losing a click; you are losing a generation that controls billions in spending power and influences the trends of older cohorts.
Efficiency in email marketing often leads to content that is technically correct but emotionally flat. How can teams integrate brand-specific voice training into their AI prompts from the start, and where should a human editor intervene to provide the most impact on engagement?
The mistake most teams make is using generic prompts that yield generic, emotionally flat results. To fix this at the source, you should train your AI on a library of your past high-performing emails—the ones that actually sparked replies or high conversions—rather than generic templates. This ensures the baseline output already carries the DNA of your brand’s specific quirks and vocabulary. However, the human editor is still the most critical part of the loop, specifically during the final “nuance check” where they can add emotional stakes or timely references. An editor’s intervention is most impactful at the beginning and end of the email, where the “hook” and the “parting thought” live, as these are the moments that leave a lasting sensory impression on the reader.
Testing typically focuses on subject lines or offers, yet tone is proving to be a critical performance variable. How should a brand design an A/B test specifically for tone, and what nuances should they look for when analyzing why one version feels more “human” than another?
To test tone effectively, you have to keep the offer and the subject line identical while varying only the “personality” of the body copy. For example, Version A could be written in a professional, structured style, while Version B uses a conversational, narrative-driven approach with more colloquial language. When analyzing the results, look beyond the click-through rate and pay close attention to “unsubscription” rates and qualitative feedback or replies. A “human” version often feels more effective because it uses active voice, addresses the reader’s pain points with empathy rather than just data, and avoids the repetitive sentence structures common in AI. If Version B sees 10% fewer unsubscribes despite similar click rates, that is a clear signal that the human-centric tone is building better long-term retention.
What is your forecast for AI-driven email marketing?
I believe we are entering an era of “The Great Refinement,” where the novelty of AI-driven volume will be replaced by a demand for AI-driven craftsmanship. In the near future, the most successful brands won’t be the ones sending the most emails, but the ones using AI to hyper-analyze which specific tonal nuances resonate with individual segments. We will see a shift where AI is used less for “writing” and more for “simulating” how a specific persona might react to a human-written draft. Ultimately, the brands that win will be those that treat AI as a sophisticated paintbrush rather than the artist itself, ensuring that every automated message still carries a heartbeat. My advice for readers is to stop optimizing for the algorithm and start optimizing for the person on the other side of the screen; if your email doesn’t feel like a one-on-one conversation, it’s just more digital noise.
