by Sarah Nicastro, Creator, Future of Field Service

A little over two years after ChatGPT came on the scene and GenAI became the major buzz and many companies are still sorting through exactly where and how AI will create value for their businesses. While this exercise will be ongoing as AI continues to evolve and use cases become increasingly sophisticated, the low hanging fruit for AI impact can be found by examining your company’s biggest inefficiencies.

For many, the area of knowledge management presents a massive opportunity to apply AI and achieve significant results. In last year’s Stand Out Service Trends report, 59% of respondents reported that between 11 and 25% of their workforce is set to retire within the next five years. Yet only 37% say they have an effective system in place for capturing knowledge and making it accessible for use. With highly-skilled, massively knowledgeable employees retiring in droves, finding more effective and efficient was to serve up accurate information is a pretty urgent challenge – and one that AI is primed and ready to solve.

Agricultural machinery multinational, CNH Industrial, recently launched its AI Tech Assistant tool and is now rolling it out globally. According to the news coverage, “This first-of-its-kind tool was developed with dealer feedback and works by simulating conversations to provide a diagnosis and repair plan for CNH brands’ machines, enabling dealer technicians to save time on repairs by providing fast and accurate answers to technical questions.” Combing 1.5 million pages of equipment manuals and insight, the tool responds rapidly to natural language questions with precise answers, completely changing how efficiently users can find information and resolve issues.

I spoke recently with another company who is leveraging Aquant alongside its core IFS Service Management platform with the initial aim of closing the skills gap. I’ll share the article when it’s published, but again it’s an example of recognizing how AI can be applied to these sizeable knowledge bases and rich historical data to aid in helping employees find what they need, when they need it in order to resolve issues faster and ultimately better serve customers. This company’s AI journey was sparked by the recognition of how long it was taking newer employees to find what they needed within the knowledge base, but the company quickly realized the capabilities can also be used for self-service by customers and with historical data for AI-led triage.

This article shares how Heineken is “quenching the thirst for knowledge” by using GenAI for knowledge management to save employees time and improve decision-making. Thinking about how powerful a tool like ChatGPT can be in our personal lives, it’s easy to begin imaging how applying the underlying technology in examples like these is not only low-hanging fruit for those looking at making use of AI but a transformation that will soon become necessity.

While the upside of applying GenAI to knowledge management is vast, this Forbes article does a good job of drawing attention to some important considerations, including:

• Data readiness
• Ensuring ethical innovation
• Change management
• Getting ready for the rise of AI agents

Imagining what an increasingly AI-powered future looks like is a worthwhile exercise. But when it comes to making use of the technology in ways that can have an immediate impact on today’s operations, areas like knowledge management that represent sizeable inefficiency for many businesses are a great place to start.

Read more about AI in field service here.