RESOLVING THE LEDGER
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Follow ZDNET: Add us as a preferred source on Google.ZDNET's key takeawaysNinety-five percent of field service organizations use AI. Firms see higher revenues when they deploy AI effectively. However, training issues and data silos can slow adoption. Almost all (95%) field service organizations now use AI, and 85% plan to increase investments over the next two years, according to Salesforce's State of Field Service research, a survey of over 2,300 field service professionals across nine countries. Here are other key findings from the research: AI is working: For companies with connected systems, AI is driving measurable results; 57% using AI-powered scheduling and dispatch report higher revenue per job and higher mobile worker productivity.Workforces are strained: Two-thirds (66%) of leaders report increased mobile worker turnover during the past two years, citing insufficient training or support when new technology is introduced as the number one driver.Data siloes are an issue: Three-fifths (61%) of organizations say mobile workers have limited access to the relevant customer data they need to act on AI recommendations.Legacy stacks persist: Two-fifths (40%) of leaders struggle to measure AI ROI, largely because technology remains fragmented; only 16% have field and back-office technology united on a single platform, while 52% still rely on spreadsheets and 43% on manual paper logs.The research suggested AI adoption has reached critical mass in field service organizations, with clear business objectives and a leadership commitment to improve business financial metrics across the board. Also: The 3 types of people who will excel in the AI agent era, according to tech leadersBut there's also more work to do for services leaders who want to exploit AI effectively.Business goals drive adoption The top business goals for AI adoption in field service are increasing customer satisfaction (35%), improving mobile worker productivity (31%), improving safety outcomes (27%), shifting from reactive to proactive and predictive maintenance (26%), and increasing revenues (25%). More than half of field service organizations (54%) use AI tools for customer communication, and 51% use the tech to help mobile workers on the go. The ability to enhance contextual understanding of the job to be done and awareness of customer expectations and immediate requirements helps explain why AI-powered field service solutions are becoming indispensable. Speed to value is the most important driver of customer loyalty and advocacy. AI ROI for field service firmsThe report found that 85% of field service leaders measure the ROI on their AI investments, with key benefits including higher mobile worker productivity (43%), improved customer satisfaction (40%), and fewer safety incidents (34%). Field service organizations are also seeing increased revenue from field operations (39%), possibly due to faster response times for customers (39%).Also: AI agents are your new colleagues - how to get the best resultsThe biggest positive impact of using AI was felt in mobile worker scheduling and dispatch. Revenue per job has increased by 57% in organizations that use AI for scheduling and dispatch. The higher revenues are due to increased mobile worker productivity (57%) and lower labor costs (49%). Based on current adoption trajectories, it is likely that 100% of field service organizations will use AI by 2027. However, the research also suggests there is a struggle for adoption.There's more work to doThe dissatisfaction among field service professionals is less about AI technology and more about how organizations prepare the workforce for AI. Companies are not training their employees, so some staff members leave. The research suggests that the most common reason for staff to leave is that companies deploy AI solutions faster than they prepare their workers to use them. Two-thirds of service leaders say mobile worker turnover has increased since 2024. Companies must prioritize investments in AI-related employee training. Data siloes are also challenging field service organizations. The report noted that 61% of companies say mobile workers have limited access to customer data. Trapped data across various systems means that, even with sufficient training, service workers cannot deliver value to customers in a timely and efficient manner. AI tools need context -- access to relevant and accurate data -- to provide recommendations or execute on behalf of workers. Also: 40% of enterprises will scrap AI agents - 3 ways to ensure yours don't failThe report found that 49% of workers lack a clear process for converting service visits into sales leads, 44% have limited ability to quote in the field, and 38% struggle with accepting payment in the field. System integration is the root cause of data being trapped. Only 16% of field service organizations have field and back-office functions integrated on a single platform. The integration challenge includes connecting mobile apps, inventory management systems, GPS tracking, connected service sensor info, and databases used to manage and track field operations.Although 85% of service leaders measure AI ROI, nearly half (40%) struggle to measure whether AI is working. One reason for this inability to map business outcomes to AI adoption is a lack of integration. Only 16% of leaders said their data is on a unified platform, meaning most service organizations have disconnected and trapped data. An average enterprise has over 1,000 software applications, with only 28% of firms sharing employee and customer data across the business. Strong partnerships are crucialField service leaders are looking for strong technology and business partnerships to accelerate AI adoption. Cost is not the only priority. Factors that matter most when selecting AI agent partners include transparency into how AI makes recommendations (34%), data security and privacy (33%), quality of outgoing support (33%), external valid...
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