Over the course of the last year, generative AI achieved a meteoric rise in popularity, with 88% of organizations now evaluating the technology’s use across all departments. Meanwhile, customer experience (CX) ranks higher than ever on leaders’ lists of priorities—forward-thinking CX leaders are already leveraging generative AI to address common challenges and stand apart from their peers.
To clarify the value of generative AI in improving customer experience, Metrigy Research explored Generative AI’s Role in Rapid Advancement of CX in a recent whitepaper. We’ll highlight some of the report’s key insights to support your CX journey below.
Top priorities and use cases for generative AI
When asked about their reasons for using generative AI, CX leaders most often cite goals of better serving customers (25.9%), improving customer ratings such as CSAT and NPS (22.4%), and making agents more efficient (20%).
To achieve those goals, the most common use cases for generative AI reported by CX leaders are content creation, classification, and auto-summarization.
Overcoming trust issues
While the widespread interest in generative AI is undeniable, it still faces headwinds. Only one-quarter of IT, CX and business leaders and 12.9% of consumers say generative AI can be fully trusted for customer interactions.
However, business leaders and consumers agree that steps can be taken to increase their trust in generative AI. These include limiting the data it can use to create content, human oversight of content content creation, and limitations on the AI’s capabilities.
Still, about one-quarter of companies say generative AI’s “newness” is a concern. As the report points out, this perception is largely due to the fact that many CX vendors have productized generative AI within the last year, but some vendors (such as Cresta) have been working on generative AI models for five or more years.
Unpacking the impact of generative AI
Generative AI plays a role before, during, and after customer interactions; in turn, it provides value for contact center agents, supervisors, and customers alike.
For agents, generative AI can streamline conversations—even for organizations within highly complex industries—by automatically surfacing relevant information from disparate knowledge bases at the right moment in the conversation. Generative AI can also make it easier to meet the sales quotas increasingly placed on customer service representatives by prompting them with upselling guidance and other tips based on the context of the conversation, the individual customer’s buying history, and general sales trends.
Managers and supervisors benefit from generative AI’s ability to simplify QA. Rather than reviewing a small portion of agents’ calls, managers can rely on generative AI to report on individual and team performance, identifying high-value coaching opportunities based on desired outcomes. By leveraging a system of outcome-based analysis, supervisors and managers can more easily implement continuous improvement.
As agents become more efficient and effective, CX naturally improves. Customers avoid long hold times, receive accurate answers more quickly, and gain a record of their interactions through AI-generated summaries delivered through the channel of their choice—something 47% of customers say they want following high-value interactions.
Adopting generative AI for CX
The benefits of adopting generative AI to improve CX are compelling, but to unlock the full potential of these solutions, businesses must get up to speed on generative AI and understand the organizational changes it could require.
From there, leaders can identify the pain points they hope to solve, engage in discussions with vendors, and establish processes for fully leveraging the latest generative AI innovations.
To learn more about how generative AI is driving CX evolution, download the full whitepaper here. For a personalized look at generative AI’s potential impact on CX in your organization, contact the Cresta team!
