The useful question is what changes for users, developers or buyers, and whether the announcement stays industry context or becomes something people can actually use.

Field service organizations are rapidly adopting AI, with 95% already using some form of the technology and 85% planning to increase investments within two years. Leaders cite customer satisfaction, mobile worker productivity, safety, and revenue growth as top priorities for the next 12 months. AI tools are currently deployed for customer communication (54%) and field employee assistance (51%), aligning with these goals. However, the pace of adoption has outstripped workforce preparation, creating new challenges.

AI’s impact is most evident in scheduling and dispatch, where 57% of organizations using AI-powered systems report higher revenue per job. Additional benefits include increased mobile worker productivity (57%), reduced emissions (52%), and lower labor costs (49%). Despite these gains, 61% of organizations say mobile workers lack access to critical customer data, limiting their ability to act on AI recommendations. This data gap reflects broader fragmentation, with only 16% of organizations operating on a unified technology platform.

A workforce crisis is emerging, with two-thirds of field service leaders reporting increased mobile worker turnover over the past two years. Leaders attribute the rise primarily to insufficient training or support during technology rollouts. The tension between rapid AI deployment and workforce readiness threatens to undermine potential benefits. Organizations are now prioritizing transparency, data security, and vendor support when selecting AI partners, reflecting the critical nature of AI infrastructure.

The survey, conducted April 22–May 12, 2026, gathered responses from 2,317 field service professionals across nine countries. While 85% of leaders claim to have measured AI ROI, 40% struggle to definitively assess effectiveness due to fragmented data systems. The organizations that succeed will likely be those that not only deploy advanced AI but also invest in workforce training and data integration to fully realize its potential.