Digital assistants are next-generation conversational AI systems that go beyond chatbots and voice processing. While the Generative AI in the Enterprise white paper discusses multiple use cases for generative AI across various industries, some examples of use cases specifically for digital assistants include:

• Customer service—Customer service and support activities use conversational agents, chatbots, and digital assistants extensively by generating natural language responses based on user queries or instructions. While the 2010s focused on automating tasks and business processes “behind the service desk,” AI-powered digital assistants enable enterprises to automate the frontend aspects of customer service. In an age in which staffing customer service agent positions is a challenge, digital assistants represent a welcome opportunity to scale up the virtual work force through an additional conversational channel.
• Education and training—Digital assistants provide personalized responses, recommendations, and content creation. While generative AI can be used to generate education and training materials, a digital assistant can deliver the training itself interactively and allow for questions. In contrast to a human trainer, a digital assistant is always patient and never runs out of time.
• Marketing and sales—Digital assistants can be used in marketing and sales to automate and enhance communication with customers. They provide personalized responses, product recommendations, and content creation. For instance, a digital assistant interprets customer queries and generates relevant responses, improving customer support, which leads to higher customer engagement and conversion rates.
• Digital kiosks—Digital assistant-enabled kiosks can revolutionize customer service by providing intelligent, personalized, and efficient service. They use AI technologies such as machine learning, natural language processing, and computer vision to interact with customers in a more human-like manner. Also, they can understand and respond to customer queries, provide personalized recommendations based on customer preferences, and potentially recognize customers through facial recognition technology. Equipping these kiosks with 3D displays provides a seamless, personalized customer experience that goes far beyond what traditional kiosks can offer. Moreover, digital kiosks can learn from each interaction, continuously improving their performance and accuracy over time. By integrating such AI workforce-enabled kiosks into their customer service strategy, enterprises can provide superior service, enhance customer satisfaction, and gain a competitive edge in the market.

In addition to these use cases, there are multiple other applications for digital assistants, including applications such as:

• Self-service knowledge bases—Generative AI can automatically generate and update knowledge base articles, FAQs, and troubleshooting guides. When customers encounter issues, they can search the knowledge base to find relevant self-help resources that provide step-by-step instructions or solutions.
• Contextual responses, problem solving, and proactive troubleshooting—Digital assistants using generative AI can analyze customer queries or problem descriptions and generate contextually relevant responses or troubleshooting suggestions. By understanding the context, the solution can offer tailored recommendations, guiding customers through the troubleshooting process.
• Interactive diagnostics—Digital assistants can conduct interactive diagnostic conversations to identify potential issues and guide customers towards resolution. Through a series of questions and responses, the system can identify the problem, offer suggestions, or provide the next steps for troubleshooting.
• Intelligent routing and escalation—Generative AI models supporting digital assistants can intelligently route customer inquiries or troubleshoot specific issues based on their complexity or severity. They can determine when a query must be escalated to human support agents, ensuring efficient use of resources and timely resolution.
• Automating contact center operations—Contact centers typically operate in a voice-only mode. A first step to introduce digital assistants is to use the voice feature of this conversational AI system to replace human labor by starting with Level 1 and Level 2 customer support.

While the validation work that we performed in this design is primarily centered on an avatar in front of a static background, there are also logical extensions to the use cases of generative AI that include virtual worlds and environments. Digital assistants can be placed in virtual worlds, landscapes, or architectural designs for use in augmented reality (AR), virtual reality (VR), the Metaverse, or simulations.

These examples show how generative AI-powered digital assistants are applied across various domains. The versatility of this cross-industry solution allows for creative and innovative applications in customer service, content and code generation, creative arts, virtual environments, personalization, and more. The use cases continue to expand as digital assistants powered by generative AI technologies advance.