AI and customer care: balancing automation and agent performance

We all know that technology has revolutionised the fintech industry, making transactions faster, more convenient, and accessible to everyone. But with all these great advancements, it’s important to remember that it’s still a relationship-based business. The importance of building and maintaining trust and establishing authentic human connections are crucial when forging strong bonds between brands and customers. 

Three AI use cases for developing top-performing contact centre agents: AI simulation training, immersive learning & performance monitoring

At Zenarate, we apply artificial intelligence (AI) to transform how contact centre representatives learn through immersive training that engages them through focused, stress-free practice. By investing in AI to empower customers to manage everyday issues and freeing contact centre agents to manage more important customer issues, your customer care organisation can win the loyalty of ever-demanding customers.

AI’s reach continues to expand

Today, AI is impacting virtually every business sector. In financial services, AI-powered algorithms and machine learning models have revolutionised data analysis, risk assessment and fraud detection. From a products and services perspective, AI has enabled the development of robo-advisors, chatbots and virtual assistants that can handle routine tasks but fall short when it comes to understanding human emotions, nuanced conversations and personalised issues.

We’ve also seen how AI-driven customer engagement strategies have transformed how organisations interact with customers. Across the board, AI has brought transformative change to drive operational excellence, expand product offerings and deliver superior customer engagement.

Let’s look at the balancing act of using AI for customer care automation and improving the performance and development of contact centre agents. 

AI for better customer care 

AI has made significant strides in customer service, bringing forward new levels of efficiency and convenience. Today’s chatbots and virtual assistants now manage simple tasks like checking bank balances or resetting passwords. Still, as innovative as these AI tools may be, their limitations become apparent when dealing with complex issues where the human element becomes critical.

AI alone brings real challenges to delivering outstanding customer service and satisfaction. For starters, this technology must be perfect, or it can lead to misunderstandings and errors that frustrate customers. It also lacks the humanised context of empathy and understanding of every customer’s individual and unique needs. 

A concern we see repeatedly is whether AI will eventually replace human engagement in customer service. Despite the recent advancements in AI technology, I think we can agree it remains increasingly unlikely. Complex issues that arise daily with customers still require human assistance. While AI’s strength lies in dealing with low-touch tasks and making agents more effective and productive, at this point, more nuanced issues still demand the human touch. 

However, the expectation from AI shouldn’t be to replace humans. Instead, the focus should be on how AI can streamline access to live-agent support and enhance the end-to-end customer care process.  There’s a need to alleviate the fear of job displacement among human agents by focusing on AI’s assistance. We see the need for a narrative that highlights how AI can make customer service agents more efficient, not how it will eliminate jobs.

Here are three of the leading AI use cases for developing top-performing contact centre agents:

• AI simulation training

Using AI and natural language processing (NLP), simulation training creates realistic customer scenarios that contact centre agents can practice. Like a flight simulator, it helps agents develop the skills to handle various customer interactions, from basic inquiries to complex problem-solving. By providing a safe and controlled environment for training, AI simulation training ensures that agents are well-equipped to handle real-life situations with confidence and efficiency.

• Immersive learning

AI-based training creates a more interactive and engaging learning environment than outdated classroom and PowerPoint training. For contact centre agents, it offers a more interesting and meaningful training experience, leading to better knowledge retention, improved performance and increased customer satisfaction.

• Performance monitoring

AI algorithms are increasingly used to analyse and monitor agent performance in real-time, identifying areas of improvement and providing personalised feedback. By tracking metrics such as call resolution time, customer satisfaction ratings, and agent adherence to protocols, AI helps contact centre managers assess agent performance and provide targeted coaching for continuous improvement.

AI is clearly transforming the financial services industry, providing new ways for businesses to increase efficiency and profitability by streamlining processes, enabling the creation of new products and services, and improving customer experiences. From our work with the largest banks to technology-driven fintech companies, it’s important to focus on how AI can automate and improve how people learn and serve customers. 

Maintaining a balance between automated customer care and developing contact centre agents is crucial for gaining the maximum benefits AI offers. Striking a balance between automation and human touch ensures that customers receive personalised assistance when needed while benefiting from the efficiency and convenience of AI-powered solutions.

For more on how AI transforms the financial landscape, check out this episode, AI simulation training in financial services, with customer service expert Casey Denby, on our “What the FinTech?” Podcast.

Sponsored by Zenarate, the winner in the “FinTech of the Future – Artificial Intelligence & Machine Learning” category at the Banking Tech Awards USA 2023.