Customers, in particular Gen Zers and millennials, are turning to platforms like YouTube and Reddit to resolve service issues, underscoring a growing preference for low-effort third-party service experiences over traditional company-owned channels, which are often lengthy and complex.
As GenAI becomes further embedded in mobile devices, customers may prefer using these functionalities over official service channels. In fact, Gartner predicts that by 2028, 70% of customer service journeys will begin – and be resolved – in conversational, third-party assistants built into their mobile devices.
Patrick Quinlan, senior director analyst, in the Gartner Customer Service and Support Practice, discusses how leaders must address this decline in tolerance for legacy self-service and focus on simplifying digital services through conversational GenAI.
How will GenAI in mobile devices impact traditional customer service channels, and what strategies should customer service and support leaders adopt for seamless experiences across all platforms?
The integration of GenAI into mobile devices is set to disrupt traditional customer service channels by offering a more efficient and intuitive user experience. As customers increasingly ask their devices to help solve service issues, companies will need to decide whether to compete with these experiences, or embrace third-party support.
If they choose to compete, they will need to enhance their mobile app experience to support conversational interfaces and ensure these tools can leverage knowledge data to effectively resolve issues.
If they choose to embrace the change, companies will need to find other ways to gather data about customer self-service behaviors and ensure their public knowledge bases are accessible by third-party services.
In either case, companies should prioritize simplifying customer journeys by pivoting from omni-channel strategies, which have become convoluted, to omni-modal strategies. An omni-modal strategy enables customers to communicate with a company through a single digital channel using their preferred mode of communication. That mode could be text, voice, video, image, or any combination. By doing so, businesses can maintain customer satisfaction and loyalty while adapting to the evolving digital landscape.
What are the potential risks and benefits of outsourcing information retrieval and question answering to third parties, and how can companies manage their knowledge bases to ensure data security and brand integrity?
Outsourcing information retrieval and question answering to third parties presents both opportunities and challenges. On one hand, it allows companies to integrate into increasingly popular, low effort experiences and leverage the vast resources and expertise of third-party platforms, potentially reducing operational costs and enhancing customer satisfaction.
However, it also raises concerns about data security, analytics insights, and brand control. It is entirely possible that a customer could defect from a brand because they received an incorrect answer from a third-party–without the company ever knowing.
To mitigate these risks, companies must establish robust knowledge management systems that ensure accurate and consistent information is available to third-parties while implementing stringent security measures to protect data integrity. By carefully managing these dynamics, businesses can capitalize on third-party capabilities to improve service efficiency without compromising their brand or customer trust.
In what ways can companies adapt their infrastructure to support the growing use of conversational GenAI and third-party service interactions? How will the development of AI agents impact these interactions?
Companies can significantly enhance service delivery and customer satisfaction by strategically leveraging mobile app architecture and customer data. As mobile devices become central to customer interactions, businesses should embed service workflows directly within their apps, creating a seamless and integrated user experience. This approach not only aligns service delivery with the customer’s mobile journey, but it also allows for personalized interactions based on the data held within the app.
While current third-party GenAI tools mainly handle simple queries using public information, future advancements in large language models (LLMs) and large action models (LAMs) could greatly expand their capabilities. These improvements might enable third-party AI agents to perform complex tasks autonomously, such as navigating portals and completing transactions.
Although it’s early to predict the full impact, customer service leaders should prepare for a future where third-party AI systems manage more sophisticated interactions, potentially increasing service volume through third parties and elevating customer expectations for seamless service.