The State of AI Customer Experience
The report identifies AI Customer Experience as a key area of AI deployment. The majority of businesses that leverage AI do so for virtual agents, chatbots, Natural Language Processing, and data analytics. It is no exaggeration to say the contact center is leading the AI revolution.
- 28% of businesses using AI do so for marketing automation,
- 19% for Natural Language Processing,
- And 15% for voice recognition.
And it’s easy to see why. AI Customer Experience is reliable and secure, and offers a range of different applications that can reduce workload and drive real value. Those applications can be found before, during, and after a customer interaction:
- Before – Voice recognition can be used to identify customer intent. Rather than choose a routing option from a menu, the customer can state intent out loud and be directed instantly to the best available outcome.
- During – Real-time sentiment analysis gives both agents and supervisors insight into the mood of the customer while the interaction takes place. If sentiment begins to decline, proactive action can be taken to salvage the interaction.
- After – Generative AI-powered, real-time transcription and summarization can automate post-call data entry tasks, automatically populating forms that only require agent review and approval. The result is a nearly 27% reduction in Average Handling Time.
All these applications drive major cost-savings for the contact center, and that’s not all. The agent experience stands to benefit as well.
AI Customer Experience for Agents
Perhaps the most interesting finding revealed by the Census Bureau’s report is that AI has had a limited impact on levels of employment. That is to say; not as many people are losing their jobs to AI as some analysts have predicted. Businesses are discovering the central truth of AI: that it will not replace humans, but enhance them. And AI Customer Experience is no different.
We’ve already outlined how generative AI can intervene at different stages of an interaction to deliver an enhanced experience for customers, by streamlining agent workflows. That’s not the only way in which AI improves the agent experience:
- Customers aren’t the only ones who benefit from a successfully resolved interaction, agents also draw satisfaction from a job well done. The more you minimize workplace friction, and the easier you make it for agents to support customers, the better they’ll feel about their work.
- If an employee is engaged, they’ll be more motivated to improve. The biggest blocker to improvement is often a lack of guidance; supervisors are simply too busy to provide the level of personalized feedback that agents require. Generative AI can draw personalized individual learnings from every interaction, giving the agent continuous opportunities for improvement.
- All this functionality should be available easily to agents, within the same interface they use for every other task. AI shouldn’t be an additional chore, but a seamless injection into agent workflows.
Generative AI hasn’t led to major job losses, because on the whole, agents and businesses have been able to adapt potential use cases into their everyday ways of working. And as the technology continues to develop, even more use cases are likely to emerge.
Self-Service AI Customer Experience
The Census Bureau report is revealing, but it’s not the final word on AI adoption: it’s an ongoing process. And the future of potential applications for AI in Customer Experience are many. One area in which AI is already delivering major efficiencies is customer self-service.
- AI chatbots have already been in use (in some form) for decades; the generative AI chatbot is still a relatively new development. After some early fumbles, businesses are now learning how to adopt appropriate guardrails that curtail the worst excesses. Now, generative AI chatbots are a real possibility.
- The advantage of generative AI chatbots is personalization. Generative AI can adapt tone and language depending on the customer, delivering a level of individual personalization that makes the customer feel at home with your organization.
- When integrated with a Customer Data Platform, an AI chatbot can leverage existing customer data and interaction history to support the customer. If the customer has been in contact about a problem before, for example, the chatbot can draw on those experiences to offer a more informed set of next steps.
The great advantage of self-service is that it takes some of the pressure off your agents. Simple and easily-resolved inquiries can be handled by chatbots, leaving only the most challenging for your agents. That gives your agents more time and headspace to devote to each interaction, leading to a corresponding improvement in customer experience.
