For years, automation in the contact center promised transformation but delivered frustration. Callers had to navigate rigid decision trees, robotic voices, and a single overriding goal: deflection. But as Joe Havlik, Vice President of Global Revenue at Synthflow, told CX Today in an interview, something fundamental has changed.
“There's been an evolution where I can now have a conversation with an AI agent that is enjoyable, and I feel like my problem can be solved. I don't think that that's been the case for the last 10 years, even the last five years.”
What came before was not conversation at all. But customers were yearning for a system that could solve their problems effectively.
“I'd love nothing more than the first thing that an AI agent says to me is, how can I help you?” The difference today is not marketing language or interface polish. “The technology is finally getting there where that's what we'll be able to do.”
Leaving Containment Behind
The contact center industry has spent more than a decade framing automation around efficiency metrics. Havlik, who was previously Vice President of North America at Cognigy, believes that framing is now outdated.
“This is not about containment. This is not about… features and functions. This is about ROI and problem solving.”
That shift also changes how vendors should demonstrate value. “Nobody wants to go to a demo where I give you a harbor tour of the inside guts of my system,” Havlik said. Instead, the moments that immediately resonate with enterprise users center on outcomes. “If I show you that first notification of loss, then the wheels start turning.”
At its core, the work is about customers, not technology, Havlik said.
“This is about creating an experience for the end users... I'm not selling software. I'm selling an outcome that is enjoyable.”
A major driver of this shift is architectural.
LLMs Change the Economics
Havlik contrasted earlier generations of conversational AI based on natural language understanding (NLU) with what large language models (LLMs) enable today.
“Think about… the LLMs being a foundation and then building the NLU around the edges versus the other way.” With an LLM as a foundation, enterprise developers can build working AI agent prototypes within hours, compressing timelines in a way enterprises understand.
“That drives an ROI timeframe that's very different than what we've seen… we can see a real ROI in weeks, not months... That's a different conversation. People are much more willing to try that out.”
Start Small, Then Scale, While Keeping the Human Element
Despite the new capabilities, Havlik warned against sweeping replacements.
“I see customers all the time almost getting to the point of analysis paralysis, [asking] ‘do I make this wholesale change?’ No, don't make this wholesale change.”
Instead, he advocated for narrow, well-defined entry points. “Pick a part of your business. Pick a phone number.”
Havlik pointed to a customer who did exactly that and scaled up successfully. The customer “started out with a single phone number to a single contact center” and the payoff came through iteration. “They grew that to out and out,” Havlik said. “And within less than two years, they grew that over a thousand percent because they started small.”
Even with better reasoning, customer acceptance hinges on something more visceral. “We are still creatures that want to feel like we're talking to something that is like us,” Havlik said.
The older interfaces failed that test. “The robotic voices of yesterday didn't make you feel that way.” Today, the response is different. “Now the voices have gotten so good that they really make it where we’re willing to have this conversation.”
Guardrails, Not Guesswork
As systems become more capable, safety becomes more complex. Havlik describes security as layered by design.
“You don't just leave it as purely an LLM and good luck. You do need some guardrails.”
Those guardrails include third-party validation as well as internal testing. “Having a third party do that is incredibly important,” Havlik said. “Because now it's not just me and my people saying we built it, and we tested it ourselves.”