Reinventing your personalization and orchestration with AI

At the November MarTech Conference, moderator Scott Gillum, CEO of Carbon Design, guided a lively discussion on how AI is transforming personalization from a buzzword into a measurable strategy. His guests — Sara Larsen of Wolters Kluwer Health, Brian McKenna of DMi Partners and Nathaniel Rounds of Braze — shared a common goal: Make marketing communications feel genuinely personal, not just personalized.

Beyond ‘Dear [first name]’

Personalization, Larsen explained, isn’t about filling in name fields or referencing a past purchase — it’s about communicating value in a way that resonates with a specific role or audience.

At Wolters Kluwer Health, that means tailoring messages for everyone from CMIOs and nursing leaders to IT buyers and clinical librarians. “We think of personalization as aligning our value message to each audience,” she said. “AI helps us do that efficiently, across a wide range of segments and geographies.”

The payoff isn’t just in better targeting — it’s in time saved. “Time-to-market, decision time and cycle time are where AI is really proving its worth,” Larsen said. “That’s the common denominator every marketer can relate to.”

From message tokens to meaningful moments

DMi Partners’ McKenna described a shift from basic customization to true orchestration — connecting the right message with the right person at the right moment. His team’s mantra is simple: right message, right person, right time.

To make that real, AI helps his clients decide how to frame offers and when to deliver them. One travel brand, for instance, used AI to test different ways of presenting promotions. “It allowed us to find which approach resonated best with each customer segment,” McKenna said. “The result wasn’t just higher conversion rates — it meant offering smaller discounts without losing engagement.”

The key, he added, is execution. “It’s not enough for AI to recommend the best time to send a message. You need the systems to actually deliver it then, and consistently across every channel.”

The data that fuels better decisions

For Braze’s Nathaniel Rounds, the conversation came back to a familiar truth: Data quality makes or breaks personalization. “AI is only as good as the data you feed it,” he said. “Garbage in, garbage out.”

That starts with getting foundational data — purchases, engagement patterns and customer behavior — organized and accessible. Once that’s in place, reinforcement learning and predictive models can identify which messages, channels, and timings drive the best results.

Rounds also emphasized the human side of machine learning. “The hard part isn’t always the model,” he said. “It’s helping teams interpret what the AI is doing and trust its decisions.”

Crawl, walk, then run

For brands just starting their AI journey, all three panelists agreed: begin small. McKenna recommended using the AI tools already built into existing marketing platforms — like send-time optimization or audience segmentation — before layering in more complex decisioning models.

Rounds framed it as a “crawl-walk-run” approach. “Start with a project that delivers quick, visible value,” he said. “That first success helps get buy-in for the next one.”

Larsen added a more personal challenge: Make AI part of your daily routine. “Try using it every day,” she told the audience. “You’ll naturally find where it fits in your workflow—and your comfort level will grow quickly.”

Orchestrating across channels

Consistency across channels remains one of personalization’s biggest challenges. Rounds noted that cross-channel coordination is essential if marketers want AI to make meaningful decisions. “If your system recommends sending an SMS at 3:04 p.m. but the message actually goes out at 9:00 p.m., the decision doesn’t matter,” he said.

McKenna agreed, adding that mismatched messaging can create more problems than it solves. “If customers see different offers in their inbox and on your website, you’ve created a customer-service issue, not a personalization win.”

Governance and guardrails

AI’s potential has also raised new governance questions — especially in industries like healthcare. Larsen said Wolters Kluwer Health has strict internal guidelines on how and where AI can be used in marketing. “We’re watching the line between AI as a support tool and AI as something that actually drives decisions,” she said. “In healthcare, that’s a big distinction.”

She warned that “shadow AI” — tools deployed by individuals or teams without oversight — can create risks for any organization. Establishing clear policies, she said, is now a must-have part of scaling AI responsibly.

Getting started and showing value

When the conversation turned to practical advice, the panelists were unanimous: start where the impact will be seen and felt.

McKenna urged marketers to explore features they might already have access to. “Many platforms include predictive models or optimization tools you’re not even using yet,” he said. “Experiment, measure, and show what works.”

Rounds encouraged marketers to focus on automating the tedious parts of their day. “If you can use AI to handle repetitive questions or manual tasks, you’ll free up time for the creative work that actually moves the needle.”

And Larsen closed with a reminder that brand consistency still matters most. When using generative tools for copy or creative work, her team trains models on brand standards and approved messaging so every output starts from the same base. “Consistency isn’t just aesthetic — it’s part of our quality control,” she said.

The bottom line

For all three panelists, AI isn’t replacing human marketers—it’s amplifying them. Personalization is no longer about inserting names or guessing at timing; it’s about using insight and automation to make every interaction more relevant and efficient.

Or as Larsen summed it up, “AI gives us back something that’s in short supply for everyone — time.”