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Home » Why Agents And AI Need Each Other To Drive Better CX
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Why Agents And AI Need Each Other To Drive Better CX

adminBy adminNovember 16, 20230 ViewsNo Comments6 Mins Read
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Sagar Rajgopal is the president and chief customer officer (CCO) of Ubiquity, a leading outsourcer for disruptive brands.

In an era where artificial intelligence (AI) has the potential to reshape industries, businesses stand at a crossroads—either to harness AI’s transformative potential for customer service excellence or risk fading into insignificance. With a staggering 61% of customers willing to switch to a company’s competitor after just one poor customer service experience, delivering exceptional customer experiences is paramount. AI has the power to change CX for the better, but it can’t operate in isolation.

I believe that businesses need to implement a hybrid CX approach by investing in training human agents to collaborate effectively with AI systems. Human agents play a vital role in refining and supporting AI systems in customer service by providing valuable feedback, identifying AI limitations and ensuring ethical oversight. Their expertise and insights enable continuous improvement of AI algorithms, which can lead to more accurate and empathetic responses and ultimately enhance the overall customer experience.

Based on my own experience, here are three ways in which AI can boost CX when applied in an effective hybrid approach.

1. Utilizing Data To Its Fullest

AI’s data-driven capabilities empower customer support teams to deliver personalized assistance. Natural language processing enables AI systems to understand customer queries, analyze sentiments and exhibit emotional intelligence. AI is also a great tool to analyze agent behavior during customer interactions, providing feedback for coaching and training and to enhance the agent toolbox. By observing how agents work with technology, AI can also be used to identify opportunities to establish API-based integrations with external systems to drive efficiency.

Predictive analytics is another area where AI shines, as it can provide proactive assistance to customers. By analyzing vast amounts of data, AI identifies patterns and trends, anticipating potential issues before they arise. In financial services, AI tools can usually predict fraud based on unusual transaction activity. The system then sends an automated alert or triggers an outbound call to customers about the suspected transaction. In healthcare, AI tools can flag missed appointments or preempt missed appointments by triggering outreach after someone is released from the hospital or treatment to ensure they schedule and have a ride to follow-up care.

With AI’s ability to monitor and flag these issues, it becomes far more seamless for customer support agents to step in and solve problems. Furthermore, AI-driven recommendation systems can suggest relevant products or services, helping agents to showcase a deeper understanding of customer needs and preferences.

One of the paramount risks businesses must be acutely aware of when employing AI to parse data, however, is data set bias. This occurs when the data used to train AI models skews toward certain demographics, behaviors or characteristics and does not accurately represent the full target population. The consequence of data set bias is the potential for discriminatory or inaccurate results, perpetuating inequalities and reinforcing stereotypes. To mitigate this risk, invest in diverse and representative data sets, implement robust bias detection and correction mechanisms, and prioritize ethical AI development practices to ensure fairness, transparency and accountability in data-driven endeavors.

2. Empowering Human Agents

While much of the discussion surrounding AI in customer support is about the potential for job displacement, I find that AI needs human oversight to maximize its potential and to protect businesses from AI risks like hallucinations and bias. That opens the door to new roles for building and training AI tools to operate as they should.

At the same time, even as AI becomes more customer-friendly and capable, the future of customer support will likely still require human agents. I believe the best CX future is one where companies embrace a collaborative partnership between technology and human support to enhance efficiency and productivity, inform everything from marketing to product design, and also drive customer satisfaction and loyalty.

As you’re looking to integrate AI into your business, consider how the technology can automate error-prone manual tasks, support your teams with next-best actions, and make it easier for people within your organization to do their jobs efficiently and well.

3. Training For Growth

Proper training and integration are important to achieving synergy between AI and human agents. Training allows human workers to work effectively alongside AI systems and develop skills for collaboration.

Specific training is going to vary depending on the AI tools being deployed. At my own company, we’ve developed an agent digital assistant that provides next-best actions on an agent’s monitor based on trigger words from a live conversation. We’ve observed that newer agents appreciate this guidance, while more tenured employees might see it as an intrusion. If you’re using AI to provide key program updates or alerts that even tenured agents need to be mindful of, be clear about how and why the tool is being used. I also recommend getting feedback from your agents about their experience and comparing that to their performance results.

The bottom line: When adding any new technology tool, it has to be an iterative process. Test and learn. Get feedback from customers and agents. Take your own chatbot for a spin. Do side-by-sides with agents who are using digital assistants. What’s working, and what needs more investment? A good place to start is with call and chat transcription data.

Conclusion

Using AI to mine your existing customer interaction data can help improve your CX by helping you better understand your customers and their pain points and where your customer support agents need additional coaching or praise. For example, Gartner research from June showed that “only 8% of customers used a chatbot during their most recent customer service experience […] Of those, just 25% said they would use that chatbot again in the future.” Adoption will most likely increase as bots get better and customers get more experience using them to self-serve. In the meantime, we still have work to do to ensure that bots and other AI tools are delivering on their potential and work seamlessly in tandem with human agents.

AI holds the transformative power to redefine customer support services, offering advantages like 24/7 availability and swift responses. Yet the essence of human touch is irreplaceable. Intricate interactions, genuine empathy and vigilant human oversight are still needed to elevate support experiences to excellence.

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