Four operations use cases that are ripe for generative AI

Generative AI, as exemplified by tools such as ChatGPT, has garnered considerable attention due to its ability to engage in human-like conversations spanning an extensive range of topics. This edition of Operations Reflections delves into how generative AI can augment a company's strategic operations by examining four specific use cases. Before we jump in, we need to stress that effective implementation of generative AI hinges on establishing a solid foundation of high-quality data and access to compute. Doing so is crucial to avoiding the "garbage in, garbage out" problem, ability to train the models, and instituting strong governance for ethical usage. 

The four operational use cases we highlight that can benefit from the capabilities of generative AI are predictive maintenance, supply chain planning, proactive risk management, and advanced contract management.

1. Predictive maintenance. Generative AI takes predictive maintenance to new heights by automating the generation of task lists, personalizing recommendations for technicians or plant managers, and fostering collaboration among team members. For instance, envision an experienced technician remotely guiding less-experienced workers through a repair via a generative AI "co-pilot" integrated with a metaverse environment. Multi-modal data further enhances efficiency in this area by enabling technicians to better understand tasks that involve text information, images, and videos. They can generate tickets based on voice input and transform hand-drawn sketches into professional diagrams, freeing up valuable time and resources. Various types of data, such as performance data from asset sensors, production schedules, worker responsibilities, and spare parts inventory status, are vital for making this use case function effectively. 
2. Supply chain planning. Generative AI offers planners increased visibility across supply chains, enabling effective "sensing and pivoting" within volatile and uncertain environments. It functions as an enhanced cognitive engine, identifying relevant business and risk signals, such as emerging customer trends, competitors' moves, market changes, or supply shortages, and suggesting appropriate adjustments in forecasts and plans in response. By learning from past signals and proactively guiding various supply chain segments to make the right decisions in the right sequence, generative AI moves companies closer to achieving optimal synchronization across the supply chain to cost-effectively meet demand. Eventually, generative AI could update plans autonomously in real time based on sensed changes, minimizing human intervention and bias while enhancing overall responsiveness. 
3. Proactive risk management. Generative AI revolutionizes supplier risk assessment by quickly and accurately evaluating vast amounts of supplier-related information available online from various data providers—far more than any individual could possibly gather and assess. It can simulate business impacts based on supplier contract terms, such as in the case of a strategic supplier's plant shutdown, helping companies determine optimal risk mitigation strategies and plan accordingly. By turning human prompts into queries for company ERP systems and simulating potential ripple effects and risk factors, generative AI helps companies determine whether to rely on single or multiple suppliers for specific raw materials, understand the costs associated with specific risks, and make more-informed decisions. 
4. Advanced contract management. Generative AI revolutionizes contract management by intelligently analyzing contract data to pinpoint problematic clauses, contracts nearing expiration, and potential compliance concerns. It simplifies the process of verifying supplier compliance with contract terms, including pricing and Incoterms, by offering rapid and straightforward access to global contract databases. In addition, generative AI can give category managers valuable insights regarding resourcing decisions based on current market conditions. It can conduct comprehensive cost–benefit analyses to determine the potential savings that could be realized from renegotiated contracts and help draft new contracts. By streamlining the contract management process, generative AI empowers organizations to mitigate risks, identify opportunities for improvement, and optimize their contractual relationships. 

Recent advances in so-called action transformers—specialized language models that work in tandem with large language models (LLMs) such as GPT-4—provide the potential for implementing the mentioned use cases. They facilitate seamless and automated communication between transformers and external systems using APIs, which is essential for operations applications that require interaction with external data sources and systems. Soon, action transformers such as Meta's Toolformer will act as middleware between LLMs like GPT-4 and external systems, enabling API-calling abilities for more efficient communication and interaction. The recently announced plug-ins for ChatGPT already bring that concept to life, thus paving the way for even more powerful and versatile AI-based solutions that have the potential to fundamentally change how companies manage their strategic operations. 

This article was written by Bharath and Paul and sent as part of a monthly perspective Kearney shares with our clients on the bigger trends unfolding across the operations landscape.

Interested in receiving next month’s note? Sign up here.

Authors

Bharath Thota is a partner in Kearney’s analytics practice with expertise in the application of advanced analytics and data science to help clients achieve analytics transformation and operational excellence.

Paul Viefers is a director in Kearney’s analytics practice whose specialties include applied statistics and advanced analytics, including expertise in prediction, classification, and testing and simulation. 

Susheel Sethumadhavan is a partner in Kearney’s analytics practice with experience in delivering analytics solutions on digital platforms across a spectrum of industries and clients.