Skip to content
Tech News
← Back to articles

Field service is 95% on board with AI but these legacy issues need attention

read original more articles
Why This Matters

Despite widespread adoption of AI in the field service industry, challenges such as legacy systems, data silos, and insufficient training hinder optimal utilization and ROI. Addressing these issues is crucial for maximizing AI's potential to boost productivity and revenue, ultimately benefiting both companies and consumers through more efficient service delivery.

Key Takeaways

Philippe LEJEANVRE/Moment via Getty

Follow ZDNET: Add us as a preferred source on Google.

ZDNET's key takeaways

Ninety-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.

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.

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.

... continue reading