Gen AI positively impacts operational and business performance. For example, companies using gen AI-powered operator and technician co-pilots in maintenance have seen significant productivity and efficiency gains. These AI tools combine data from manuals, operating procedures and past root cause analyses, suggesting hypotheses and scenarios for troubleshooting. This allows technicians to troubleshoot issues more quickly and effectively on the production line.
In traditional troubleshooting scenarios, root cause analyses could take hours or even days, but with Gen AI assistance, these steps are streamlined to seconds. This reduces breakdown time and boosts productivity, with some companies reporting up to 30-40% improvements in troubleshooting speed and 5-10% increases in line output due to faster response times.
Similar gains have been observed in contract feedback and improvement processes, further enhancing productivity across value chains.
Although these are still individual use cases, broader end-to-end transformations integrating these capabilities could yield even greater impacts in the future.
