The most successful companies are well on their way with foundational AI technologies, and are ahead on generative AI adoption, too.
With the pace at which technology is changing the customer experience (CX) landscape today, imagining what a contact center looks like five years from now is an interesting exercise. Certainly, artificial intelligence (AI)-enabled automation will be a core functionality—and companies that haven’t begun laying the groundwork have no time to waste. Their competitors may be well ahead of them already.
In Metrigy’s latest CX research, Customer Experience Optimization: 2023-24, fewer than 18% of the 641 companies studied globally haven’t or have only just started developing an AI strategy for CX. All other companies consider their CX-related AI strategies to be fairly far along (36.9%) or even mature (45.5%), already having implemented AI and having processes in place to leverage innovations as they come up.
Not surprisingly, then, many companies already are reaping considerable benefits from AI. Consider these AI-related gains for the most successful companies in our CX Optimization study, as determined by revenue, costs, customer ratings, and agent efficiency:
- Revenue increase – 38.0% for the general use of AI, 34.4% for the use of agent assist, and 33.7% for the use of customer-facing virtual assistants
- Operational cost reduction – 5.6% for general AI use, 9.8% for agent assist, 8.1% for customer-facing virtual assistants
- Customer rating improvement – 45.8% for general AI use, 39.7% for agent assist, 34.0% for customer-facing virtual assistants
- Agent efficiency boost – 36.0% for general AI use, 32.3% for agent assist, 35.1% for customer-facing virtual assistants
Each of these key business metrics are well above the average for all companies measuring results of their AI use.
In addition, the most successful companies use or are planning to use far more AI-enabled CX applications than others. Metrigy’s CX Optimization study shows the number of AI-enabled CX applications increasing from 28 to 72 on average from 2022 to 2025. The numbers are much higher for the success group, at 44 rising to 107. And the gap between the success group and non-success group, which started with 16 AI-related CX apps in 2022 and projects reaching 37 by 2025, is substantial. Clearly, AI-enabled CX applications pave the way to success.
Examples of how AI, coupled with automation, can provide value during customer interactions are plentiful. During a webchat, for example, AI could automatically send terms and conditions or other required documents to customers, as well as other content when triggered from an agent prompt, or send a chat summary. Facing inward, AI could serve up next-best-action workflows in a self-service environment, such as starting a refund process or offering a loyalty reward, automatically. The same sorts of use cases, plus others, apply to virtual assistants lending a hand to agents and customers. AI could initiate the customer verification process, for example, or gather post-interaction feedback from customers.
Of course, no conversation regarding the here and now and, especially, the future of CX would be complete without a discussion of generative AI’s role. The potential of using generative AI to automate tasks exerts an almost irresistible pull, with possibilities galore: creating content for customer engagements, summarizing interactions (especially those dealing with complex issues), classifying customer service or sales topics, training and coaching agents and supervisors, and so on and so on.
Generative AI’s adoption is already strong, with 35.4% of the success group and 27.3% of companies in the CX Optimization benchmark using the technology today. No single use case pops up as overwhelmingly ahead of any other for current deployments, but 40.0% of companies do consider content creation—be it for human agents, virtual agents, or customers—to be the most valuable, compared to classifying sales and customer interactions (30.8%) and summarizing internal meetings (22.9%) and customer calls (6.4%).
Regarding their use of generative AI, companies are drawn to its potential for improving customer ratings, making agents more efficient, increasing revenue, and saving money. Indeed, the lure of generative AI, as for AI and automation overall, revolves around those critical success metrics for CX, with the overarching goal of better serving customers.
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Part of our guest blog series, this post was written by Beth Schultz, Vice President of Research & Principal Analyst, Metrigy.
ABOUT METRIGY: Metrigy is an innovative research and advisory firm focusing on the rapidly changing areas of workplace collaboration, digital workplace, digital transformation, customer experience and employee experience—along with several related technologies. Metrigy delivers strategic guidance and informative content, backed by primary research metrics and analysis, for technology providers and enterprise organizations.