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GenAI Copilots in the Customer Service Function
GenAI Copilots in the Customer Service Function
An AI copilot has the potential to improve customer experience by helping the customer service function become more efficient and effective.
A prime example of this is the implementation of a GenAI model by a technology company, designed to understand customer intent, which is central to many customer service use cases. It operates by first comprehending the customer’s query and then searching through various knowledge sources for the answer. These sources can include web links, the knowledge base, customer relationship management (CRM) systems and various other customer databases, which also enable personalisation. The process involves the AI system trawling through these sources to automate a relevant customer response. The generated response is then evaluated by a human or an AI agent, who can edit it, if necessary, before forwarding it to the customer. This application of GenAI in customer service has several benefits: significant reduction in the time taken to respond to customer queries, thereby improving service efficiency; allowing customer service agents to focus on more complex tasks as the AI handles routine queries and, lastly, providing personalised responses, thereby enhancing customer experience.
GenAI and Marketing
The marketing function is benefiting from GenAI through innovation in product, creative and experience development. An Asian beverage company was looking to enter the EU market and turned to GenAI to help answer two questions: What kinds of new beverages might appeal to European customers and drive growth, and what innovative methods might speed up the product innovation process from end to end? The beverage company used ChatGPT to provide user insights by feeding it aggregate, non-confidential customer information and then asked questions about flavour trends to generate a baseline understanding of beverage consumption and consumer behaviour in the EU market.
Product designers also turned to GenAI to refine concepts. Using a text-to-image generative AI tool, the company was able to produce high-fidelity beverage concepts with detailed imagery. Marketers then took these concepts into the field to perform rapid testing with customers, ultimately helping the company complete a year-long process in just one month.4
GenAI for Societal Impact
Beyond the realm of business, GenAI has the potential to enable countries and societies to address challenges that were previously insurmountable in sectors spanning from healthcare to education, from sustainability to accessibility, and beyond. In the realm of education, AI tools like Khan Academy’s Khan Migo are revolutionising the way we learn. Khan Migo uses AI to generate custom learning paths for students, thereby enhancing educational outcomes. This personalised approach to learning ensures that each student receives instruction tailored to their unique needs and learning style. As a result, students are more engaged in their education and are more likely to succeed academically.
One of the challenges in sustainability is optimising resource allocation. GenAI and agentic workflows can address this in real time, reducing waste and enhancing efficiency. For instance, AI can optimise energy usage in smart grids, contributing to a more sustainable future. This application of GenAI could play a crucial role in combating climate change and preserving our planet for future generations.
In terms of accessibility, AI is surging ahead in making digital content more accessible to individuals with disabilities. For example, AI can generate real-time captions for individuals with hearing impairments. Making digital content more accessible ensures that everyone, regardless of their abilities, can fully participate in the digital economy.
GenAI can be a tool for societal transformation, unlocking possibilities in healthcare, education, sustainability and accessibility, enabling us to solve problems that were previously thought to be impossible. As we continue to explore and develop this technology, we can look forward to a future where GenAI plays a crucial role in shaping our society for the better.
练习题
In the customer service example, what does the GenAI copilot do immediately after understanding the customer's query?
Which outcome best shows how GenAI improves the marketing innovation process in the beverage company example?
Which example from the source material is a direct application of AI for accessibility?
Which statements about GenAI in customer service are supported by the source? Select all that apply.
In the beverage company example, ChatGPT was used with aggregate, non-confidential customer information to generate baseline market insights about EU flavour trends and consumer behaviour.
The source claims that personalised AI learning paths decrease student engagement because every student follows a different route.
GenAI and agentic workflows can support sustainability by optimising resource allocation in real time, reducing waste and improving efficiency.
In customer service, the generated response can be evaluated by a human or an AI agent, who can ___ it if necessary before forwarding it to the customer.
Explain how GenAI can contribute to societal transformation using any two sectors from the source.
Compare one way GenAI improves customer service in this section with one way it improved banking back-office work in the prior section.
Which scenario best shows a shared use of across customer service and banking operations?
Which statements correctly compare how uses personal or customer-related data across marketing, customer service and insurance underwriting? Select all that apply.
Because can generate customer service responses and automate recruitment or banking tasks, it always removes the need for human involvement in business processes.
Both personalised customer service responses and -generated learning paths in education are examples of using data to provide more ___ experiences.
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