As customer expectations rise and support volumes spike, simply being available on every channel isn’t enough. The real challenge is showing up well—every time, on every platform, without burning out your team or breaking the bank.

That’s why in the sixth and final episode of our ACX Framework Series, we focused on what might be the most operationally daunting, but ultimately most rewarding, dimension of AI maturity: scale and coverage.

I had the pleasure of sitting down with two leaders who’ve figured out how to make omnichannel AI support not only scalable, but lovable. Toby Moors from Loop Earplugs , who’s led a two-year journey with Ada that now automates 50% of tickets across chat, email, and social. And Aisha Ben Kahla from Photo Booth Supply Co., who’s built an intentional, phased approach to AI that’s turned every channel into a strategic asset.

Here’s how they’re making omnichannel AI work —without sacrificing quality, consistency, or creativity.

start where your customers are

Too many AI implementations start with the question: “What can the tech do?” But smart teams start somewhere else entirely: “Where are our customers already trying to reach us?” That mindset helped both Loop and PBSCO prioritize the right channels, right from the start.

Both companies took similar paths: launching in chat, scaling into email , and then for Loop, unlocking a surprising win on social.

The progression was grounded in customer behavior—not just technical possibility. Both Toby and Aisha based their rollouts on actual customer engagement. “Our priority was absolutely written in channels,” as Aisha put it. That decision gave them clarity on where to invest their effort and allowed them to learn channel by channel.

crawl, walk, resolve—phased rollouts win

For anyone feeling overwhelmed by omnichannel support , here’s some good news: you don’t have to launch everywhere at once. In fact, you shouldn’t.

Aisha emphasized the importance of scaling intentionally, focusing first on low-risk automation that could deliver high confidence and quick impact. The team launched on chat with FAQs, then refined performance before expanding.

That structured, data-driven expansion helped them avoid the burnout that often comes with overextending AI too fast—and gave both Aisha and Toby’s team the confidence with every new launch.

embrace high-volume channels, unlock big-time ROI

Channels like email and social often get left behind in automation strategies. But as Toby and Aisha both pointed out, they’re too valuable to ignore.

At Loop, the team leaned into high-volume moments like Black Friday and saw Ada dramatically reduce agent workload without missing a beat.

They’ve also brought automation to social DMs—a traditionally manual channel—by building flows that handle everything from returns to product info. It’s been a game-changer for efficiency and customer satisfaction.

PBSCO is taking a forward-looking approach to voice, one of their largest volume drivers. By building a strong foundation across written channels first, they’re preparing to bring AI into voice with the confidence that they can maintain tone, accuracy, and intent-matching at scale.

Both teams agreed: the most intimidating channels are often the ones with the most upside—especially if your team is drowning in high-volume, low-complexity work.

coach your AI like it’s on payroll

AI isn’t a fire-and-forget tool. Just like your agents, it needs training, feedback, and ongoing refinement. That’s why both teams invest in AI coaching that ensures Ada gets better every week.

Loop treats their AI agent like a team member—reviewing interactions, adjusting flows, and tracking resolution accuracy with the same rigor they’d apply to a new hire.

PBSCO has a distributed ownership model. “We have someone who owns Ada content and someone who owns Ada performance.” That cross-functional structure allows the team to track CSAT and unresolved inquiries while constantly identifying opportunities to expand coverage and improve quality.

The key isn’t just volume. It’s feedback—built into the process, owned by real people, and applied with intention.

from support channel to brand channel

Done right, AI doesn’t just resolve tickets—it represents your brand. And that means tone, personality, and voice matter.

Your AI agent doesn’t just need to resolve tickets—it needs to sound like you.

Toby and the Loop team invested time in training Ada to match their tone of voice across every channel. From playful language to product-specific nuance, they’ve built an experience that’s distinctly Loop—not generic automation.

At PBSCO, tone and trust are equally important. The team evaluates CSAT as a guardrail, not just a KPI. Their goal is to ensure that even when a conversation is automated, it feels personal, empathetic, and on-brand.

Support channels aren’t just operational anymore—they’re experiential. With the right tuning, they can become brand-building touchpoints.

final thoughts: scaling without compromise

Scaling omnichannel support with AI isn’t about cutting corners. It’s about amplifying the best parts of your team—with coverage that never sleeps, tone that feels human, and performance that gets better every day.

You don’t need to roll out across every channel overnight. Start where it matters. Build your foundation. Coach your AI like it’s a teammate . And when you’re ready—step confidently into the next channel, knowing your support experience won’t just scale. It’ll shine.