Transforming contact centers with AI: 4 essential use cases

To meet customers’ growing expectations for the convenience and personalization they have obtained in other consumer-focused industries, some banks are prioritizing investment in artificial intelligence (AI), especially generative AI, capabilities in their contact centers.

For sure, prioritizing customer experience (CX) was one of the major takeaways of a new Talkdesk report, revealing that bank executives realize quality of CX directly correlates with their organizations’ ability to retain business. The CX in Banking report showed that CX has become a strategic priority in the prior year for 98% of banks and credit unions, with 83% of survey respondents regarding it as a leading driver of customer trust and loyalty.

More AI, better CX
The CX in Banking report, which surveyed 200 financial services executives on bank and credit union plans over the next few years, makes clear that most financial institutions are committed to investing in AI-based technologies to improve CX.

For example, the report found that banks and credit unions with integrated AI capabilities are more than twice as likely than organizations that aren’t effectively leveraging AI to believe their contact centers are having a positive impact on CX (80% compared with 28%).

Additionally, 63% of respondents that deployed AI in their contact centers reported they can consistently link CX metrics to return on investment, compared with 21% of respondents that lag in AI adoption.

Finally, 56% of respondents reported that they expect their organizations to increase investment in CX technology by 10% or more over the next three years. Among respondents anticipating more spending on CX technology, improving digital service with AI was the technology priority most often cited at 59%.

AI use cases for contact centers
When supported by gen AI, machine learning and automation, contact centers can provide bank customers with a personalized experience and self-service options, while also empowering contact center employees with the tools needed to deliver superior customer service.

Following are bank and credit union executives’ most frequently cited use cases for deploying AI to boost CX:

• Virtual autopilots for customers (66%): Banks and credit unions can deliver frictionless CX by offering self-service capabilities that enable customers or members to complete routine tasks, such as answering FAQs, checking an account balance, transferring funds, stopping payments on checks, or finding out the latest mortgage rates. Additionally, offering more self-service options for customers frees call center agents to work on more complex interactions focused on their financial well-being.
• Optimizing self-service and assisted service with Navigator chatbot or guided conversations (73%): Making sure the conversation is being held in the right place at the right time is critical for delivering excellent customer service. Large language models (LLMs), coupled with natural language processing (NLP) technology, empower AI to better detect customer intent and sentiment, conduct sentiment analysis of customer and contact center interactions, and enable smart routing interactions, helping virtual agents, chatbots, or human agents identify the most appropriate and relevant responses to questions and requests.
• Improving contact center agent effectiveness with copilot (73%): In addition to guiding agent conversations with customers, AI can instantly retrieve customer information brought up during a call, saving the agent and customer time wasted in a search by the employee. First Call Resolution is top of mind for most banks. Providing instant access to knowledge and real-time contextual guidance allows agents to navigate through the most complex and stressful conversations. Scenarios such as dispute management or fraud management can be candidates where a smart AI-enabled copilot can be extremely effective.
• Enlightening contact center with actionable insights (83%): The effectiveness of AI in CX will be determined by the amount of predictability and proactiveness it empowers banks and credit unions with. Advanced analytics can help banks and credit unions better understand customer or member preferences, enabling greater personalization of offers and services. Real-time insights can make the banks and credit unions become proactive and lead with empathy, especially in situations when customers or members are anxious or stressed.

What’s holding back the adoption of AI?

While most banks and credit unions are eager to adopt AI, the CX in Banking report revealed there are several barriers preventing or delaying these plans. As an example, 34.5% of respondents reported that their organizations struggle with digital transformation initiatives, such as migrating legacy CX technology to the cloud.

Some of the challenges limiting AI adoption and implementation in larger financial institutions include lack of quality data (74%), resistance to change (63%), and insufficient availability of talent to maintain the technology (61%).

Alternatively, smaller banks and credit unions reported that their top obstacles are resistance to change (69%), insufficient AI/IT talent (64%), lack of quality data (51%), and uncertainty about return on investment (51%).

Partnering with technology providers that have AI as a core part of their platform and who are willing to work closely with banks and credit unions to continuously test, learn and optimize AI can help overcome some of the above barriers.

Conclusion
Leaders at banks and credit unions understand they must infuse AI technology into their contact centers to deliver the highest level of customer service.

Whether they believe AI is already here or coming, the time to lay the foundations to aggregate customer data from all interaction touchpoints on a modern AI-led contact center platform is now.

When banks and credit unions invest in AI technology purpose-built for the contact center, the result is greater personalization and convenience for customers and efficient operations.

Rahul Kumar is Vice President and General Manager for Financial Services at Talkdesk.