Humans in the loop
– 8 min read
Front CEO Dan O’Connell on reinventing customer support for the AI era
When everyone has AI, human connection becomes the competitive advantage
Dan O’Connell wasn’t the kid who took apart computers to see how they worked. He was the one who wanted to be captain of every sports team he played on. Fast forward a few decades, and that competitive spirit has led him to one of the most challenging leadership positions in enterprise software: CEO of Front, a B2B support platform serving thousands of companies worldwide.
But here’s the twist. In an industry racing to automate everything, Dan is making a contrarian bet: that when AI can handle complex customer interactions at scale, the real competitive advantage won’t be the quality of your chatbot — it’ll be access to actual humans.
In this episode of Humans of AI, Dan sits down with host Alaura Weaver to explore the strategic tension at the heart of Front’s reinvention: How do you transform a 10-year-old company for the AI era while staying true to the mission of empowering human connection?
- 10-year-old companies wondering if they need to reinvent should ask three questions: Do you have an AI-first product architecture (not just features)? An AI-first narrative? Are customers choosing you for the future or switching costs?
- Front flipped the script on AI deployment—instead of waiting for chatbots to break and sending humans to apologize, they tell customers upfront where AI has high confidence and where it doesn’t, putting control in their hands
- Here’s the paradox: When every brand has powerful chatbots, the competitive advantage becomes access to actual humans—Front is betting that human connection becomes more valuable, not less, as AI becomes ubiquitous
- The strategic choice: Front traded short-term growth for long-term differentiation by prioritizing human-centric design over automation velocity — freeing support teams to focus on relationships instead of repetitive tasks
- Want to move fast? Don’t eliminate structure — build better structure with clear ownership, transparent communication, and alignment that enables rapid, distributed decision-making at AI speed
The AI reinvention diagnostic
Front is at a pivotal moment that many venture-backed companies eventually face. “We are viewed as a legacy company,” Dan admits. “And I think many of the businesses that have been around for 10 or 15 years that are venture funded are in this moment.”
It’s a moment that requires honest self-assessment. Dan shares a three-part diagnostic that Front uses to determine whether—and how—to reinvent:
1. Do you have an AI-first product — not just features sprinkled in, but actual architectural transformation?
2. Do you have an AI-first narrative that resonates with customers and investors?
3. Are people actively choosing your platform for the future, or are you winning on switching costs from the past?
Most legacy companies can answer “yes” to one, maybe two. But all three? That’s where the real transformation happens.
“If you’re a 10-year-old company wondering whether you need to reinvent, run this test,” Dan explains. “Do you have an AI-first product—not features, but architecture? Do you have an AI-first narrative that works with customers and investors? And are people actively choosing your platform for the future, or are you winning on switching costs from the past?”
This isn’t about adding ChatGPT to your product. It’s about fundamentally rethinking how you create value in an AI-powered world.
Flipping the script on AI transparency
When most companies deploy AI in customer support, they follow a familiar pattern: stand up a chatbot, wait for it to break or frustrate customers, then send in humans to apologize and save the day.
Front is doing something different.
“We’ve basically flipped the script on that,” Dan reveals. “You connect to us, we tell you where we have high confidence on repetitive tasks or things that we cannot fully automate, and you get to decide whether to turn them on or off.”
It’s radical transparency about AI capabilities from day one. Instead of hoping customers won’t notice when automation fails, Front is upfront about where AI excels and where it doesn’t. Control sits with the customer, not the algorithm.
This approach represents a fundamental shift in how companies think about AI deployment. It’s not about perfect automation — it’s about honest partnership. And that honesty builds trust in ways that even flawless chatbots can’t replicate.
“We think that we probably trade off a little bit of revenue growth,” Dan acknowledges. “But what we deliver is a more controllable, more empathetic, better customer experience and gives people control.”
The human touch paradox
Here’s where Dan’s thinking gets really interesting. He believes that as AI becomes ubiquitous, human interaction becomes more valuable — not less.
“If everyone stands up chatbots and voice bots out in the world, and let’s just say they can do all sorts of crazy complex tasks, if that’s the experience every single brand has, then what makes a brand unique is the fact that you actually get to talk to somebody.”
It’s a counterintuitive insight in an industry obsessed with efficiency and scalability. But Dan’s bet is strategic: Front is positioning for a future where computational power is commoditized, and human empathy is the differentiator.
This isn’t about resisting automation. It’s about redefining its purpose.
“I want the support and customer success person to show up every day and say, I don’t have to deal with the rudimentary work. All of that is solved. And because I’ve taken the easy stuff away, I now get to focus on the quality of relationships and experience that I can bring to the other customers for their other needs.”
The vision: AI handles the repetitive tasks, freeing humans to do what they actually do best — build relationships, solve complex problems, and create memorable experiences that turn customers into advocates.
“I know that I can be myself at work for my customers because this piece of software empowers me to do that,” Dan explains. “And it takes out the BS repetitive tasks that I don’t want to deal with.”
The strategic tradeoff
Every strategy involves tradeoffs, and Front’s is explicit: they’re trading some short-term revenue growth for long-term differentiation.
In a world where every SaaS company is racing to show AI-powered revenue acceleration, Front is taking a different path. They’re betting that controllability, transparency, and human-centric design will matter more than pure automation velocity.
It’s a patient strategy, and it requires conviction. But for Dan, the alternative — chasing automation for its own sake — misses the point of what makes customer relationships valuable in the first place.
“We deliver a more controllable, more empathetic, better customer experience and gives people control,” he says. That’s the tradeoff: slower near-term growth, stronger long-term positioning.
Structure as an enabler, not a constraint
One of the most striking insights from the conversation comes when Dan challenges the startup mythology that structure kills speed.
“In order to move fast and be innovative, what do you have to have? You have to have alignment, you have to have structure and process. That allows you the structuring process and alignment. It allows you to move fast.”
This matters for AI implementation. The companies that can move fast enough to iterate on AI aren’t the ones that eliminate process. They’re the ones that build the right processes — clear ownership, transparent communication, and structural alignment that enables autonomy.
Dan’s insight: information flow determines decision velocity. In a world where AI is changing product requirements weekly, the companies that can make fast, distributed decisions will win.
“What Dan really learned: at scale, information flow isn’t a nice-to-have cultural value. It’s the thing that determines whether you can move fast enough to survive.”
The paradox: structure doesn’t slow you down. Bad structure slows you down. Good structure—the kind that enables rapid, aligned decision-making—is what allows organizations to move at AI speed.
What this means for enterprise AI strategy
Dan’s approach offers a template for how enterprise companies can think about AI reinvention:
1. Be honest about where you are. Run the diagnostic. Don’t pretend you’re AI-first if you’re not.
2. Build for transparency, not perfection. Customers value honesty about AI capabilities more than flawless automation.
3. Optimize for human elevation, not replacement. The goal isn’t to eliminate people—it’s to free them to do higher-value work.
4. Make strategic tradeoffs explicit. Short-term growth vs. long-term differentiation. Automation velocity vs. controllability. Own your choices.
5. Build structure that enables speed. Information flow, alignment, and clear ownership are what allow organizations to move fast in the AI era. For enterprise leaders navigating agentic AI governance, WRITER provides the comprehensive framework needed to deploy autonomous AI systems safely and effectively.
The companies that get this right won’t just survive the AI transformation. They’ll define what it means to be human-centered in an AI-powered world.
Listen to the full episode of Humans of AI with Dan O’Connell wherever you get your podcasts. Watch the video interview on WRITER’s YouTube channel.
Ready to build AI that amplifies your team rather than replaces them? Discover how WRITER’s AI agents work in the enterprise and explore the comprehensive guide to agentic AI use cases across departments.
Learn how WRITER’s enterprise AI platform can help you achieve human-centric transformation at scale. Visit writer.com to learn more.
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