Fixing Broken Customer Service Before Agentic AI Arrives With Parloa

Why are companies preparing for agent-to-agent customer service when many customers still cannot get a chatbot to answer a straightforward question?

In this episode of Tech Talks Daily, I speak with Latané Conant, Chief Marketing Officer at Parloa, about the state of customer experience and what businesses must repair before agentic AI becomes another barrier between customers and support.

Parloa’s State of Agentic CX report assessed 10,000 enterprise websites, 4,000 chat interactions, and 100 phone trees. According to the company’s findings, fewer than 10% of the tested chat conversations achieved the customer’s goal. Only 1% of enterprises demonstrated readiness for automated agent-to-agent interactions.

Those results raise a difficult question about years of customer experience investment. Businesses now have websites, chatbots, mobile applications, email, messaging, and phone systems, but customers frequently struggle to find help or complete the task that brought them there.

Latané argues that part of the problem comes from treating customer service primarily as a cost center. When the objective is reducing contact volume, organizations can unintentionally make themselves harder to reach. This overlooks the commercial and operational information contained within customer conversations.

Calls can reveal onboarding problems, unexpected product uses, recurring faults, and potential sales opportunities. Latané explains how analyzing service conversations can give marketing, product, operations, and executive teams a clearer picture of what customers are experiencing.

We also examine why so many chatbots reproduce the frustration of traditional phone trees. Although the interface looks conversational, the system underneath may still rely on rigid categories and predefined routes. Customers then find themselves trying different words or repeatedly requesting a human agent.

Latané describes a better agentic customer experience as being closer to talking with someone who already knows you. A personal AI agent could remember previous interactions, understand preferences, work across voice and text, and complete a request without making the customer repeat information.

That possibility also introduces questions about trust, permissions, personal information, and oversight. Latané discusses the need to monitor what AI agents are doing, identify when conversations move away from approved subjects, and use supporting agents to detect potentially harmful behavior.

Human involvement remains particularly important when a conversation involves distress, vulnerability, or emotional care. In Latané’s roadside assistance example, AI can arrange a tow truck for a flat tire. If it detects signs that the caller is in distress, the conversation should move quickly to a person.

We finish by considering what this means for customer service employees. Latané believes experienced representatives and operations teams can become builders and managers of AI agents, applying their customer knowledge across a much larger digital workforce.

If the existing customer service front door is confusing and unwelcoming, should businesses repair that experience before inviting AI agents through it? Listen to the episode and share your thoughts with me.