Talking heads prevail with questions about how AI will affect your technician’s productivity in the field. Get familiar with some top FAQs about how AI actually works (for good) in the field service industry.
Q:❓ How can AI be applied to the existing workflows my technicians follow on the job?
A: AI can be applied to existing workflows by leveraging the data captured in XOi and using AI to generate job summaries, work summaries, and other narrative outputs. By providing prompts and inputs to AI systems based on the existing workflow steps, technicians can reduce the amount of manual writing and documentation, leading to increased efficiency and standardization in the output.
Q: ❓ Can ChatGPT provide comprehensive answers for maintenance questions?
A: While AI systems like ChatGPT can provide impressive answers quickly, they have limitations. The answers may not account for brand specifics, advanced issues, variables like model year, weather, time of year, or past maintenance history.
Q: ❓ How does XOi software contribute to successful AI tools?
A: XOi software is built on data collection from the field. Technicians have been collecting video, photos, and notes from jobsites for over 10 years. This data is transcribed to fuel AI prompts, enabling the generation of highly specific suggestions and answers.
Q: ❓ Is historical data enough for successful AI tools in field service?
A: Historical data is just the beginning. Truly successful AI tools require a continuous cycle of data collection, engagement, and reengagement from technicians in the field. This ongoing process ensures the AI system remains up to date and relevant.
Q: ❓ What should be the role of AI in field service?
A: The role of AI in field service is to enhance the job of technicians by providing highly relevant suggestions. It should not aim to replace the human element or the expertise and nuance that technicians bring to their work.
Q: ❓ Why is human-collected data essential for field service AI?
A: Field service AI technology relies on data collected by humans on jobsites. This data is crucial for training AI models and ensuring the AI system can make technicians better, faster, and smarter. AI needs human input to provide valuable insights in the field.