Generative AI’s Role in Rapid Advancement of CX

Authors: Robin Gareiss, CEO and Principal Analyst Beth Schultz, Vice President of Research and Principal Analyst Not available for licensing. As companies look to improve the agent experience, develop strong customer relationships, and otherwise optimize around customer experience (CX), the increasingly common assumption is that artificial intelligence (AI) and automation are givens. Today, companies leading on CX understand this to mean, specifically, the adoption of generative AI capabilities. They’re drawn to the technology for its promise of enabling them to streamline processes and offload cumbersome tasks for everyone involved in customer interactions. Those companies that haven’t yet explored the use of generative AI could quickly find themselves on the wrong side of the gap between the technology haves and the technology have-nots. To keep ahead on CX advancements, companies should:

• Get up to speed on generative AI, vetting vendors not only on their specific product plans, but also on how they use customer data, which Large Language Models (LLMs) they use, how they’re cultivating trust, and how they’re charging for generative AI.
• Identify where processes are breaking down and creating pain points, such as lack of insight, agent inefficiency, and prolonged time to resolution. Think about applying generative AI to address these pain points, and plan proofs of concept.
• Educate agents, supervisors, and customers on how they’re using generative AI and how each role is benefiting. Focus too, on data privacy and trust, and response accuracy.
• Establish processes that enable the ability to capitalize on generative AI capabilities as they become available. Account for budget, usage policies, security and privacy, rollout, continuous improvement, change management, and so on.

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Table of Contents

• Executive Summary
• Art of the Possible: What Are CX Leaders Missing?
  • Common Sticking Points
  • Introducing Generative AI
    • Primary Use Cases for Generative AI
    • Top Priorities for Generative AI
  • Addressing Generative AI Concerns
• Generative AI Key Benefits
  • Value to Agents
  • Value to Supervisors & Managers
  • Value to Customers
  • Value to Operational & Business Performance Insights
• Next Steps to Benefit from Generative AI
• Conclusions and Recommendations