AI has the potential to unlock trillions in value over the next decade with generative AI at the forefront, reinventing experiences and creating never-seen-before applications, which is why over 80% of companies are already working with or planning to adopt generative AI. Issues around implementation, cost and trust can often be roadblocks to value, but those challenges can be addressed by approaching AI holistically with a clear strategy—from the data that trains it to the infrastructure it runs on to the problems it’s designed to solve.
In the landscape of customer service, efficiency and prompt response times are crucial. Our recent collaboration with Česká Spořitelna, one of the largest banking firms in Czech founded in 1825 and serving a vast clientele of 4.5 million, stands as a testament to this principle. With a workforce comprising 1,500 contact center agents and 4,500 branch customer representatives, the client faces a significant challenge understanding client requests, seeking missing information, searching for accurate responses, and formulating replies.
To evaluate the potential of generative AI in customer service, IBM Consulting stepped in to architect a modular prototype leveraging the expansive capabilities of Large Language Models (LLM) on the AWS platform. This prototype, crafted within three months, was made possible through the backing of AWS and was seamlessly incorporated into IBM Consulting’s Contact Center Modernization (powered by Amazon Connect) solution.
Our approach was multifaceted. We introduced an ‘Agent Assist’ feature that can revolutionize the way information is accessed and utilized. With the Semantic Search capability, agents can delve into the knowledge base in real-time, pulling up information relevant to the ongoing conversation.
We also emphasized the importance of understanding the nuances of customer interactions. Sentiment analysis was deployed to analyze client sentiments, which informs the routing process and supervisor monitoring. The transition between virtual and human agents can be streamlined through handover summarization, with potential to significantly reduce average handling times. As a result, after-contact summarization can provide structured insights for future reference and action.
The Automated Email Handling system marked another leap forward. It intelligently categorizes incoming emails and extracts vital information based on these categories. If an email misses some data, the system can generate contextual responses, ensuring continuity in customer service.
The non-production prototype focused on proving the feasibility and potential value of generative AI in customer service was successfully finished during autumn 2023. The possible value of these prototypes is vast. Agents can gain direct access to all necessary information, potentially cutting down significantly on the time spent conducting manual searches. This would not only reduce average handling times but also would enable agents to spend more time for complex, human-centric tasks. This can lead to improved customer satisfaction, fueled by quicker responses and an improved first call resolution rate.
IBM and AWS have built targeted use cases for generative AI that are unlocking real business value today, driving step-change improvements whether in human resources, customer care and application modernization.
Join us at AWS Summit Stockholm 2024 to discover the ways IBM and AWS can unleash the transformative value of generative AI in your business with greater speed, scale and trust.
Read more: https://www.ibm.com/consulting/aws