A survey conducted by Gartner has found that chatbots will become the primary customer service channel for about a quarter of the world’s organisations by the year 2027, having evolved over the past decade into a critical technology component of a service organisation’s strategy. There can be little doubt that when designed and deployed correctly, chatbots can enhance the Customer Experience (CX) and drive positive customer emotion at a lower cost than live interactions.
However, to effectively deploy and measure chatbot performance, Customer Service and Support (CSS) leaders must create an appropriate deployment strategy based on use cases and service interactions’ complexity.
The rise of chatbots represents a major shift in the way that businesses interact with customers. By leveraging the latest Artificial Intelligence (AI) and natural language processing capabilities, chatbots can provide faster, personalised, and more convenient customer service experiences.
Businesses will undoubtedly reap the benefits of chatbots over traditional service channels, including 24/7 availability, instantaneous responses, and consistently delivering standardised replies. Multilingual capabilities allow chatbots to not only provide support across many different languages but also communication-based on regions, accents and dialects. This broadens the reach of the customer service function and enhances accessibility to key services.
The evolving role of humans
The rise of chatbots does not necessarily spell the end for human customer service agents but will rather see an evolution of their role. While chatbots will take over mundane and repetitive tasks, humans will be freed up to focus on complex issues and will step in where customers require specialised attention or to deal with sensitive situations that need human judgment, emotional intelligence, or critical thinking.
To deploy chatbots effectively, organisations must invest in the right chatbot-building platforms that will leverage AI and natural language processing capabilities. At the same time, humans will still play a critical role in the training and supervision of chatbots. Businesses will thus need to retain the right skills to refine and update their chatbots, constantly improving their conversational abilities.
In order to deliver a high-quality CX, businesses will have to continually monitor and measure the performance of their chatbots to ensure they are working accurately, consistently and within the ethical confines of the engagements happening across their various channels. This means tracking metrics such as response times, customer satisfaction rates and conversion rates, while also making adjustments as needed to improve performance.
Advanced language models
The emergence of ChatGPT and similar advanced language models has attracted much attention, mainly due to the fact that these AI-driven chatbots have been trained on such huge data sets and have access to the entire internet. ChatGPT also rates highly on contextual understanding, doing a good job of capturing, interpreting, and understanding the context of a conversation. Being able to effectively generate responses aligned with a conversation’s history makes engagement more human-like and coherent.
What makes models like ChatGPT even more formidable is a capability called “zero shot learning”, which is the ability to generalise from limited examples or even to provide answers to topics it has not been exposed to. Hence, such advanced language models are attractive for businesses that want to leverage AI for routine transactions and free up resources for more complex issues.
However, the independence of these models raises questions about their ability to be controlled and whether at some point they will become better than human intelligence or problematic in some way. Unfortunately, there is no clear answer at this stage.
The overarching goal for the development of AI has always been for the technology to complement human beings, rather than to create a situation where it surpasses or exceeds human intelligence.
Yet, the continued development of AI systems does raise ethical questions and makes a strong case for safeguarding policies and procedures to be put in place to regulate what these AI models are ultimately able to do. Still, the optimistic view remains that the combination of humans and AI could provide solutions to even the most complex problems.
George Muhia is Industry Lead – Africa Digital Natives at Infobip