AI in Customer Support: Enhancing Service in the Asia-Pacific Region
Customer support teams in the Asia-Pacific (APAC) region face growing demands. High inquiry volumes, diverse languages, and rising customer expectations put agents under pressure, increasing the risk of burnout. AI offers practical solutions by streamlining processes and reducing agent workload, enabling faster, more consistent responses and greater capacity.
Reducing Wait Times Through Smart Automation
Long wait times frustrate customers and overload agents, especially during peak periods or disruptions. AirAsia tackled this by automating real-time flight updates via SMS, email, and chat using AI. This led to a 90% message delivery success rate and a Net Promoter Score (NPS) rise to about 50. The airline later enhanced communications with interactive SMS and HTML emails linked to chatbots.
Similarly, Singapore’s StarHub launched a chatbot powered by AI to handle over 3,000 query types—from broadband plans to technical support. This chatbot integrated 50+ user journeys to assist with service activations and troubleshooting. The result? Support wait times were halved, and NPS improved from -40 to +10 by freeing human agents to focus on complex issues.
Streamlining Workflows to Improve Consistency
As teams grow, manual repetitive tasks can introduce inconsistencies. Globe Telecom in the Philippines used Salesforce’s Einstein and Agentforce AI tools to automate case handling. The system identifies customer intent, filters duplicate tickets, escalates complex cases, and reopens closed tickets when needed. Outcomes included a 28% drop in ticket volume, 34% less agent workload, and over 80% accuracy in case classification. Combining AI with robotic process automation (RPA), Globe automated 60% of operations, easing agent pressure and raising service quality.
Using AI in Customer Support in Real-Time
China Airlines focused on improving agent interactions during stressful events like flight disruptions. Partnering with Chunghwa Telecom Laboratories, they introduced an AI-powered voice response system to analyze calls live. This helps categorize queries, guide agent responses, and provide data for training improvements. Real-time AI support boosts agent confidence, reduces fatigue, and helps manage customer emotions more effectively.
Improving Multilingual Support Through Co-Pilots
Multilingual support is essential in APAC but challenging to scale. DBS Bank addressed this by developing an in-house generative AI assistant for voice and digital channels. It transcribes calls in real time, retrieves relevant articles, and generates post-call summaries. Built on a large language model trained with internal data, it understands local languages and slang.
Piloted in Singapore from October 2023, the assistant achieved nearly 100% accuracy in transcription and issue resolution, cut call handling times by up to 20%, and earned positive feedback—90% of agents said it improved their workflow. DBS is expanding the solution to Taiwan and Hong Kong, aiming for full deployment by the end of 2024.
AI – A Key Ally to Support Staff
These examples show AI supporting, not replacing, customer support agents. Whether through automation, real-time assistance, or language capabilities, AI helps teams deliver faster, more accurate, and consistent service.
Importantly, AI reduces repetitive work and burnout, allowing agents to focus on meaningful interactions. This creates better experiences for customers and more sustainable roles for employees. As AI tools evolve, they offer a clear path to efficient, human-centered customer support that meets today’s demands.
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