The launch of ChatGPT last November has fuelled the rise of AI as it has removed some of the friction explaining how AI works and its potential. Mature organisations have been using AI for years now by integrating chatbots into the work of the 50,000 customer service agents in Hong Kong so call centres can achieve their business goals, including cost efficiencies, improved customer satisfaction and increased retention rates.
These organisations also find that as technology develops, there is no longer an excuse for them to deliver poor customer experiences, and therefore, striking the right balance between human empathy and robotic efficiency is all the more important.
AI has been interweaved with our day-to-day work for decades. Take the banking and finance industry as an example. AI was first commercialised back in the 1980s when the technology was used to predict market trends and provide customised financial plans.
Since then, AI has been increasingly used to automate mundane tasks and reduce the risks of human mistakes in the likes of financial and market analysis.
Fast forward to today, banks and pension funds have incorporated the use of natural language processing (NLP) and sentiment analysis to improve the quality of their customer service. Other financial service providers have saved money by deploying virtual assistants to handle a high volume of enquiries around the clock.
For example, Hang Seng Bank’s AI chatbot virtual assistant HARO and Bank of China and Prudential’s joint offering My MPF Bot have both helped address product enquiries and offer hassle-free services with fast and simple interactions. Where are the other gaps AI can fill in the future?
The engagement capacity gap in the customer service business
The customer service business, which costs US$2 trillion to operate globally, is facing an “engagement capacity gap”: the mounting pressure on contact centres to continuously provide an immaculate customer experience in high volumes across online and offline channels while the number of resources, budget and time costs remain the same, or even experience a crunch.
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Customers today are demanding a higher standard of efficiency in service: they want it instantaneous, and they now have more channels than ever to get it. According to a Frost & Sullivan report, 30 per cent of Asia-Pacific organisations pointed out that providing omnichannel customer service is their top IT challenge, as customers still expect meaningful, personalised and genuine interactions with the option of human assistance when required.
Naturally, generative AI has become front of mind as a solution given the technology’s recent developments. In fact, a recently released study by the National Bureau of Economic Research has found that the availability of AI assistance is able to increase productivity by an average of 14 per cent. Does this mean we can transition all work from a human agent to a chatbot?
Human and bots: Competition or coexistence?
In the customer service business, every minute counts. Being able to save time to summarise a call with a customer means that an agent could take an extra call with another, ensuring they stay happy with your company’s services. AI has so far been commoditised to help agents. The question is then: can AI excel on customer service standalone, or requires a hybrid approach of human and bots?
When AI was first introduced to the financial industry, there was a similar scepticism to today that it would take over jobs, and we have had a lot of learning since then. The key one is that a negative chatbot experience may even drive away 30 per cent of customers as they are not always reliable enough to handle complex questions nor even provide accurate answers. Therefore, we see a hybrid approach as the most effective and could help in the following ways:
- Funnelling enquiries by priority and complexity as the first touchpoint for all customers
- Summarising calls on behalf of human agents to free up their reporting time
- Analysing customer data to provide human agents with context and recommendations background on the customer for appropriate follow-up
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Striking a balance
Despite the efficiencies, the core of customer service is inherently about being human, and AI will not be able to replace that element, especially the empathy and experience required when dealing with emotionally charged situations or complex issues.
Technological developments in automation can enable agents to achieve more in less time, complementing human agents by performing a plethora of mundane tasks. Having said that, the implementation of AI in customer service comes with its own risks.
If not developed with proper oversight and ethical considerations, AI systems can perpetuate bias, discrimination and unfair treatment of individuals. Striking a balance for an effective blend of AI and human empathy is key in the future of customer service.
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