Welcome to the exciting world of generative AI and its potential to transform the customer experience. While the media has largely focused on the impact of AI on the nature of work, a McKinsey study shows that 80 percent of customer tasks can be automated across channels, resulting in a 20 percent savings for cost-to-serve. ChatGPT and other similar tools have the power to reshape customer support, marketing and sales, supply chain, and product development.
However, there are five challenges that need to be addressed before ChatGPT can be adopted on a large scale. The first obstacle is that current generative AI tools cannot personalize messages, which is critical for increasing customer loyalty and sales. Secondly, generative AI solutions often “hallucinate” content that isn’t accurate, creating issues with customer confusion and errors. Thirdly, generative AI cannot apply business rules that would ensure standardized responses. Fourthly, generative AI cannot ensure compliance with legal and regulatory requirements, which could result in fines, censure, or customer harm. Lastly, ungoverned use of ChatGPT can create security risks.
To overcome these challenges and realize the full potential of generative AI, enterprises need to deploy two different architectures: one for human-augmented interactions and one for fully automated interactions. Both architectures use open-source generative AI tools like ChatGPT and employ similar processes that range from prompt input to data synthesis to content creation, cleaning, and personalization.
For human-augmented B2C and B2B operations, a marketing professional can enter prompts into an enterprise interface, using a predesigned questionnaire to guide content development. The employee enters key information, which is then enriched with customer personas to provide information that will appeal to this segment. The enhanced question is then sent via an external API to ChatGPT or a similar generative AI tool. A curator applies business rules and legal guardrails to ensure that the content meets enterprise and regulatory standards before being sent for approval and distributed to customers.
For fully automated B2C interactions, after a user enters a question, the query is enriched with customer persona data. The updated query is then routed either to a domain chatbot or via an external API to ChatGPT for routine questions. The domain chatbot personalizes content, while ChatGPT does not. The resulting content is then scrubbed for errors and compared against business rules and guardrails before being automatically distributed to customers.
In conclusion, the potential business gains from ChatGPT and other generative AI tools are substantial, including team productivity, enhanced customer experience, decreased service interaction costs, and new product sales. Enterprises that recognize the challenges and deploy the appropriate technology architectures will be able to reap the rewards of this exciting new field.
Editor Notes:
Generative AI is an exciting technology that has the potential to change the way we interact with customers. As companies look to streamline their operations and improve the customer experience, generative AI tools like ChatGPT will become increasingly important. To stay up-to-date with the latest developments in AI and related fields, be sure to check out GPT News Room at https://gptnewsroom.com.
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