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Finding Signal Through Noise: How Authenticx Carved Its Path in Enterprise AI Before the Hype

In late 2018, most enterprise software companies weren’t talking about AI. The few that were found themselves explaining basic concepts to bewildered executives. Then came 2022’s AI explosion, and suddenly every company needed an AI strategy. But what happens when you’ve been building AI solutions before the hype cycle, and now must navigate a market drunk on possibilities?

In a recent episode of Category Visionaries, Amy Brown, CEO and founder of Authenticx, revealed how she transformed from COO of a global insurance company to founder of an AI platform that’s reshaping how healthcare organizations understand their customers. Her journey offers a masterclass in enterprise GTM strategy during periods of rapid market evolution.

From Manual Analysis to AI Platform

When Amy launched Authenticx, she started with the simplest possible MVP: herself, a laptop, and manual analysis. “In the early days, we started with myself, a laptop and my car, and I had an idea of what I wanted to do with conversation data. But I didn’t have any AI models that I was leveraging at that point in time,” she recalls.

This manual approach proved crucial for early validation. “When I got those early contracts, we were manually listening using myself and a few contractors and manually tagging and labeling what we were hearing in these conversations.”

But Amy soon faced a critical decision point: stay small and consultative or build a scalable AI platform. “I really had to hit a fork in the road moment of do I want to be in the consulting business that helps enterprises think through these types of opportunities and leverage different technology solutions out there, or do I want to build the SaaS solution in the AI myself?”

Navigating the Pre and Post-ChatGPT Enterprise Market

Perhaps the most valuable insight from Amy’s journey is how she maintained credibility through the AI hype cycle. Before ChatGPT, Authenticx had to educate the market differently. “We fell into the business buyer, not so much the tech buyer in the enterprises we sell to,” Amy explains. “We had to use different language to describe AI capabilities. We needed to use analogies, we needed to use other language that could help connect really to the use case.”

When the market suddenly shifted, many AI companies chased the hype. Instead, Authenticx doubled down on responsibility. “Our marketing philosophy is really about being the adult in the room, particularly in this AI hype cycle that we’re in,” Amy shares. “We were an AI company before it began, and no one knew what we were talking about.”

This positioning required careful navigation. “We’ve been very intentional about the markets we’re marketing to. We’ve been very honest about what we say our capabilities are,” she notes. The challenge wasn’t just technical – it was maintaining authenticity when sudden market demand could have incentivized overselling.

Creating a New Category Through Active Listening

Rather than get pulled into existing AI categories, Amy is working to establish “listening AI” as distinct from conversational AI. This isn’t just semantic positioning – it’s about fundamentally different use cases and value propositions.

Her approach to category creation starts with understanding market concerns. “I was just out at the JP Morgan conference… and I listened to dozens of investors, bankers talk about fears, concerns, the promise of AI, the hesitation of AI, the question and skepticism around use case and risks, rewards, all of that.”

This listening-first approach shapes how Authenticx contributes to industry dialogue. “Through listening, I can hear what the big questions are, where the fear is rooted, where the hopes are rooted. And I tend to weigh in on the things that I have a passion about that I feel might help bridge a gap or add some value to the conversation.”

The vision driving this category creation is ambitious but focused. “Three to five years, every corporation in the United States will be bringing the voice of their customer into the boardroom, and they’ll be able to do that in a very scalable and real way,” Amy predicts. This frames AI not as a replacement for human decision-making, but as a tool for bringing customer voices into the highest levels of corporate strategy.

For founders navigating similar category creation challenges, Amy’s journey offers a crucial lesson: sometimes the best way to stand out in a noisy market isn’t to shout louder, but to listen more carefully and speak with measured authority.