Self-service is no longer simply about deflecting contacts, it is becoming the foundation of the customer service experience. AI is fundamentally changing what customers can expect from it.

New CCW Digital research reveals that organizations expect the share of customers beginning in self-service will rise to 77% by 2030, while the share of those interactions fully resolved through self-service is expected to increase to 74%. 

At the same time, 71% of organizations believe that more than half of the inquiries currently handled by humans could already be resolved through self-service given the right capabilities.

So what is holding that potential back, and what will it take to unlock it?

In this analyst chat, Brian Cantor, Managing Director of CMP Channels and Brooke Lynch, Lead Analyst and Divisional Director of CCW Digital, explore how AI is moving self-service beyond basic automation toward a more intelligent model of customer engagement. 

They will also discuss:

• How the business case for AI is evolving
• The foundations that make intelligent service possible
• A deeper look at what the modernized experience actually looks like

AI pilots are everywhere, but customer experience isn't improving at the same pace. The problem isn't too little AI. It's disconnected AI agents, employees, data, journeys, and systems. Customers feel that fragmentation before the business ever sees it in a dashboard.

• Where successful AI programs actually begin
• How to preserve customer context across every human and AI handoff
• What makes autonomous AI safe to scale without losing control
• Which familiar metrics can mask unresolved customer needs
• Where human judgment creates the trust AI alone cannot

Metrigy Research finds that organizations with connected, enterprise-wide AI achieve nearly 80% greater improvement, on average, across key business metrics than those pursuing standalone initiatives.

Leave with a practical framework for identifying where disconnected intelligence is holding CX back and where connecting it will create the greatest customer and business value.

Closing the AI value gap takes more than adding another AI point solution. Individual tools may improve isolated interactions, but when they operate across disconnected systems, they cannot consistently retain context, coordinate workflows, or carry a customer issue through to resolution. Delivering better service requires a connected platform designed around the full customer journey, bringing conversation, context, action, and escalation together to produce the outcome the customer needs.

• Why resolution is the true measure of customer value, whether achieved by AI or a human.
• How to connect context, AI action, and human judgment without losing continuity or accountability.
• How to identify production-ready use cases and evaluate them for business value, risk, and operational readiness.

Customers no longer separate a "good" experience from a "digital" one. They expect the same accuracy, memory and follow-through whether they're on the phone, in a chat window, or talking to a person. The real shift underway in customer care isn't automation replacing people. It's a Total Experience, where human and digital interactions are held to the same standard, and where the AI behind the digital side keeps improving instead of freezing the day it goes live.

• What today's customers actually expect from a modern service experience, and the trends separating organizations that are keeping up from those stuck on a containment plateau.
• How agentic AI resolves genuinely complex, multi-step requests without becoming unpredictable and how self-learning AI takes that further by building and testing its own next agent, with a human approving every change before it goes live.
• Why AI cost becomes unpredictable at scale, and the specific questions to put to any vendor before signing, so cost doesn't become the reason a program stalls.
• What a modernized human-plus-digital balance looks like in production, with evidence from real customer deployments.