5 benefits of AI in the contact center

Contact centers throughout Asia-Pacific (APAC) face mounting pressure from a range of operational demands, including call volume surges, multilingual support requirements, and agent retention. 

According to CX Network's 2025 Global State of CX research, building a customer-first culture is among the top challenges for practitioners in the region.

Artificial intelligence (AI) is changing how organizations respond. From voice analytics to automated knowledge retrieval, AI tools enable contact centers to deliver faster, more consistent support while reducing the burden on agents.

On that theme, here are five key benefits from common AI use cases as contact centers in APAC respond to escalating customer demands with effective use of technology.

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1. Real-time agent support cuts handling time and improves accuracy

When agents have to search extensive documentation during live interactions, resolution times increase and customer satisfaction declines.

Australian telecom giant Telstra addressed this challenge by deploying AI-powered tools built on Microsoft Azure OpenAI Service. The company developed One Sentence Summary, which converts customer interaction history into concise summaries, and Ask Telstra, which enables agents to search internal knowledge bases quickly and easily.

During trials in 2023, One Sentence Summary was tested with customer-facing staff. Ninety percent reported time savings and increased effectiveness, with the tool reducing follow-up contact by 20 percent. Team members said it helped them quickly understand sensitive customer circumstances, enabling more tactful responses.

Ask Telstra, which provides AI-generated responses to employee queries via a simple search interface, was piloted with approximately 200 staff. More than 80 percent of users reported that it improved their customer interactions.

2. Speech analytics optimizes agent performance

Many contact centers struggle to extract actionable insights from customer interactions quickly enough to improve service quality and agent effectiveness.

National Telecom in Thailand addressed this challenge by implementing Verint Open Platform with AI-powered speech analytics. The deployment enabled automated analysis of close to 75,000 contact-center interactions, with Verint Da Vinci AI identifying keywords, phrases and themes across customer conversations.

The technology reduced the time required to generate analytical insights from one week to 24 hours. What’s more, by analyzing transcribed calls, National Telecom identified that the longest average talk times stemmed from internet connection issues. 

Following changes to troubleshooting processes and agent support, the company recorded an 18 percent reduction in average talk time and a three percent increase in overall customer satisfaction scores.

3. Multilingual AI delivers seamless cross-border customer service

In regions serving diverse markets, language barriers can create operational complexity, requiring either specialized multilingual teams or forcing customers or agents to communicate in non-native languages.

DBS Bank addressed this challenge by developing CSO Assistant, a generative AI co-pilot built entirely in-house by the bank's AI engineers. The system used a large language model adapted to local languages and speech patterns, alongside voice telephony and speech-recognition technology.

Its capabilities meant that CSO Assistant was able to transcribe customer queries in real time and search the bank's knowledge base to retrieve query-specific information, supporting the bank's 500-strong customer service workforce in handling more than 250,000 consumer and corporate customer queries each month.

Pilot data showed transcription and solutioning accuracy of close to 100 percent. Nearly 90 percent of customer service officers involved said the tool had a positive impact on their workflow and that they were comfortable using it as an ongoing support tool.

On that basis, DBS made the decision to roll out CSO Assistant to other markets, including Taiwan and Hong Kong.

4. AI-assisted call summarization simplifies high-volume workflows

High agent turnover creates training costs, service inconsistencies, and a loss of organizational knowledge in contact center operations. Roles dominated by repetitive inquiry handling can also be difficult to sustain, making it harder to retain experienced staff over time.

Singtel turned to technology to reduce the workload placed on call-center agents during customer interactions. The company deployed an AI-powered customer support system that summarized, synthesized, and highlighted key issues by topic, giving agents a clearer view of customer needs without requiring them to manually review or piece together information during live calls.

Rather than automating interactions end to end, Singtel applied AI to support agents in handling inquiries more effectively and consistently. By helping staff focus on resolving issues instead of navigating information, the approach was aimed at making call center work more sustainable and engaging, while improving the overall quality and continuity of customer support.

5. Voice AI creates natural, accessible customer interactions

While text chat-based AI has become common, voice interactions still represent a significant portion of customer service contacts.

Rakuten Mobile deployed an AI-powered voice assistant to handle customer calls directly, using OpenAI’s Realtime API alongside its in-house large language model, Rakuten AI 7B. The system was designed to support natural, speech-to-speech conversations in Japanese and English.

With around 30 percent of Rakuten Mobile's customer inquiries still handled by phone, the voice assistant was used for tasks such as signup, onboarding, and routine customer support that would otherwise have been handled by contact center agents. The aim was to make phone-based support easier to access for customers who preferred calling, without relying on long wait times or complex call routing.

Running on Rakuten Mobile’s own infrastructure, the system avoided speech-to-text delays and kept customer data within the company’s environment while integrating with existing contact-center operations.

Contact centers, AI, and the future

These examples demonstrate that successful AI implementation depends on identifying specific operational challenges and deploying targeted solutions to reap the benefits. Whether addressing multilingual support, knowledge access, agent workload or customer self-service, the common thread is using AI to eliminate friction.

Organizations that approach AI adoption strategically – starting with clear use cases, measurable outcomes, and frontline team buy-in – are seeing returns in customer satisfaction, operational efficiency, and employee engagement.

In contact centers across Asia-Pacific, AI enables organizations to deliver service quality that was previously impossible to achieve at scale. As CX Network's research shows, the contact center industry is expected to reach US$113.8 billion by 2027, with AI-powered automation emerging as the number one investment priority.

The question facing leaders is not whether to adopt AI, but how quickly they can deploy it effectively while maintaining the human judgment and empathy that define exceptional service.

Quick links

• How 9 APAC countries are regulating the use of AI
• The customer behaviors guiding CX strategy in APAC in 2025
• 5 things to know about CX technology in APAC