Beyond the Chatbot: Why 'Agentic AI' Is Forcing a Revolution in Customer Experience

By Patrick Griffin | Nov. 12, 2025

For decades, customer support has been trapped in a paradox. It is simultaneously one of the most critical drivers of customer loyalty and brand reputation, yet it's often managed as a reactive "cost center" - a complex, human-intensive operation that struggles to scale. The challenge has always been balancing cost, efficiency, and quality.

The first attempts at automation, rule-based chatbots, solved the cost problem but often failed on quality, leading to customer frustration. The recent explosion of generative AI (GenAI) promised to fix the quality issue, but its propensity for "hallucination" and its fundamentally reactive nature - it waits for a question - left a gap.

Now, a third wave of AI is hitting the market, one that re-frames the entire paradigm. And we are beginning to see concrete data on its impact.

This month, eCommerce marketing platform Yotpo announced a renewed partnership with AI provider Quack, citing staggering results from its initial deployment. The headline figures are significant enough to warrant attention: Yotpo reports that 70% of its customer support tickets are now fully automated. In parallel, the company achieved a 50% increase in the coverage of its internal knowledge base, dramatically reducing the need for human intervention.

These numbers are not just an incremental improvement; they signal a fundamental shift in operational capability. But the technology driving this change is far more sophisticated than a simple chatbot. It’s a move from reactive Q&A to proactive, agentic problem-solving.

The Problem with "Repetitive"

To understand the significance of this, we must first appreciate the problem Yotpo faced - a problem universal to nearly every scaling SaaS, B2B, and D2C company. Yotpo's global support team operated on a traditional multi-tier system, but the vast majority of inbound tickets involved routine, repetitive questions.

This is the classic scalability trap. These queries are simple, but not simple enough for old automation, demanding time from trained human agents who could be handling complex, high-value customer issues. This human involvement creates an operational bottleneck, putting a cap on sustainable growth.

Yotpo’s search for an AI solution was defined by a strict, non-negotiable demand: accuracy. The company, which serves thousands of brands, could not risk a system that provided confident-but-wrong answers. This fear of AI hallucination has been the single greatest barrier to enterprise adoption of GenAI for autonomous, customer-facing roles.

From Generative AI to "Agentic AI"

The solution Yotpo implemented points to the next frontier of enterprise AI. Quack, the provider, describes its platform not as a chatbot, but as a "proactive agentic AI operating system." This distinction in terminology is crucial.

As defined in recent analyses by industry watchers, "agentic AI" represents a significant leap. While a standard generative AI model (like ChatGPT) responds to a prompt, an "AI agent" is given a goal. It can then create a multi-step plan, access a set of tools (like a knowledge base, a CRM, or other APIs), and execute that plan to achieve the goal, reasoning and adapting along the way.

This is precisely what Yotpo required. As Gil Fiarberger, SVP of Client Services at Yotpo, explained, the "real differentiator" was the system's ability to be trained on real customer scenarios for each of Yotpo's products. "We trained Quack on each of our products using real scenarios with real customers," Fiarberger noted. "Essentially building an infinite team of experienced Yotpo agents."

This approach - training the AI not as a generalist but as a team of specialists - is the key to solving the accuracy problem. The AI isn't guessing based on the public internet; it is operating within the confined, verified knowledge of Yotpo's own ecosystem, integrated directly with its Salesforce Service Cloud and Documents360 systems. When Fiarberger’s team "asked Quack a question and it provided an answer as accurate as one of our own human agents," they were convinced.

The "Proactive" Leap

The second half of the equation is the shift from "reactive" to "proactive." Traditional support, including most AI-powered support, waits for a ticket to be filed. A proactive system, by contrast, aims to resolve issues before they become tickets.

By integrating with a company's core systems, a proactive AI can identify points of friction in real-time. For instance, it could theoretically detect a user struggling with a specific feature in an application and surface the correct help article before the user even thinks to open a support chat. This is what Quack’s CEO, Nadav Kemper, means when he says the goal is to resolve issues "before they even reach CX teams."

This moves customer support from a passive, ticket-taking function to an active, in-product guidance system. The 50% increase in Yotpo's knowledge base coverage is a direct result of this. The system doesn't just use the knowledge base; it actively identifies gaps and helps expand it, creating a self-improving loop.

Implications for the C-Suite

The Yotpo case study is an early, powerful signal of a market-wide transformation. The "AI in Customer Service" market, already valued in the tens of billions, is now entering a new phase of maturity.
For business leaders, the implications are threefold:

1. CX Reframed as a Growth Engine: The PR from Quack explicitly frames the shift as moving CX "from a reactive cost center into a growth engine." This is not just marketing hyperbole. By automating 70% of low-level queries, Yotpo’s skilled human agents are now free to focus entirely on the most complex, high-value interactions - the very conversations that drive retention, expansion, and deep customer loyalty.
   
2. The Rise of the CX "Operating System": The market is moving beyond single-point solutions (a chatbot for the website, a co-pilot for agents, a separate KB) toward unified "operating systems." These platforms, like the one Quack describes, act as an intelligent layer that unifies all knowledge, all channels, and all AI functions (auto-response, co-pilot, quality assurance) into one manageable-and-trainable "brain."
   
3. Accuracy is the New Arms Race: The public fascination with creative, generative AI is a poor fit for the enterprise, where accuracy, reliability, and brand safety are paramount. The future of enterprise AI is not in general-purpose models, but in highly trained, specialized agents that act as a true extension of the company's own expertise.

Yotpo’s rapid growth has always been tied to its ability to innovate. By becoming an early adopter of this third wave of AI, it is placing a strategic bet that proactive, agentic AI is the key to scaling its customer experience as rapidly as its technology.

For other business leaders, the question is no longer if they should adopt AI for customer support, but whether their current strategy is merely reactive or truly proactive. The answer will likely define their operational efficiency and customer loyalty for the next decade.