Knowledgeable Assistant That Wears Many, Many Hats

Developers love generative AI, because it makes their jobs easier. Marketers love generative AI because it jogs new ideas and concepts. But this is only the tip of the iceberg, as there are countless additional business use cases emerging for AI. Use cases that revolve around AI as serving as a tireless assistant for a huge range of tasks.

Business use cases are the secret sauce to AI success, as Andy Thurai of Constellation Research and I pointed out in a Forbes article published in August. That secret sauce depends on selecting a robust and expansive business use case that moves AI initiatives from disjointed sets of projects to masterful performances.

To make AI as masterful as can be, Deloitte Consulting has come out with an extremely comprehensive guide of generative AI use cases, purposeful to IT shops, marketers, CEOs, and everyone else in the business. “The use cases described in this dossier are a starting point for exploring how this powerful technology can be used to improve the enterprise today and prepare it to lead in the future,” say the team of authors, led by Nitin Mittal and Lynne Sterrett of Deloitte.

The Deloitte guide is packed full of use cases, from patient care to legal services to supply chain optimization, roles in which generative AI serves as intelligent assistants. Here are just a few of the use cases mentioned:

Customer support assistant: “Generative AI-enabled virtual agents can improve the customer experience by providing real-time, personalized support and creating new ways of interacting with customers,” the Deloitte co-authors state. “Customers can gain faster response and resolution, and organizations can free up human agents to focus on more complex customer issues.”

Virtual voice customer assistant: “More traditional chatbots can be limited because they rely on preprogrammed dialogue,” says Deloitte. “A virtual voice customer assistant, powered by a large language model, could overcome the challenges with conversational dialogue.”

Market research assistant: “Generative AI enables rapid market research by efficiently reading and summarizing extensive volumes of pertinent material, presenting the information in a readily understandable format for market research teams.”

Data mining assistant: “A generative AI system can help stakeholders across all business functions better understand the consumer by simplifying data mining and analysis with user-friendly interfaces and natural language queries. Reaching across data silos, the system can automatically identify outliers and summarize issues to guide decisionmakers to areas requiring attention.”

Regulatory compliance assistant: “Generative AI can be used to support and enhance compliance by processing large amounts of regulatory documents from multiple geographies. Text processing Generative AI can be used to extract regulations for one specific purpose from thousands of pages of regulatory texts, expediting and enabling compliance.”

Augmented developer assistant: “Generative AI can be used to supplement the work of software developers by helping create and maintain multiple applications and platforms. Generative AI can augment the completion of repetitive tasks, such as the deployment and maintenance of code across different platforms (e.g., iOS, Android, webapps).”

Procurement assistant: “Generative AI can analyze offerings from existing vendors, match to an organizational need, generate requests for proposals, and analyze the responses. Generative AI can automate the RFP and SoW writing process by generating the initial drafts based on templates, historical documents, or specific prompts provided by procurement officials.”

Follow me on Twitter.