AI for field service is no longer a future bet, it’s a present-day advantage.
Artificial intelligence is already helping field teams operate more efficiently, serve customers better and make smarter decisions faster.
And the momentum is building, according to a Field Service USA report: 74% of field service leaders plan to increase their AI investments within the next year.
This article draws on insights from that report, which is based on a survey of senior field service professionals across North America. Participants represented companies with $5M to over $500M in annual revenue, spanning industries like utilities, construction and manufacturing.
At Big Fish, we build custom apps for field service companies, so we pay close attention to how technologies like AI are shaping the way field-based teams work.
Below, I break down the ten most valuable ways companies are using AI in 2025, and where investment is heading next.
1. AI Scheduling and Dispatch
Used by 59% of field service organizations today, AI helps automate and optimize scheduling, dispatching and routing. This reduces travel time, minimizes fuel usage, and increases the odds that the right technician shows up with the right tools. It’s one of the most widely adopted forms of field service automation, and another 35% of leaders plan to implement it soon.
2. Data Analytics for Operational Insights
AI in service operations goes beyond automation. With AI-powered data analytics, companies can track KPIs in real time, surface inefficiencies and make smarter decisions faster.
Currently used by 54% of organizations, this capability is becoming a core feature of modern field service management platforms.
3. AI-Powered Job Prioritization
Not all service requests are created equal. AI can evaluate urgency, SLAs, and equipment condition to decide which jobs get addressed first. This improves customer outcomes while using your workforce more efficiently. Adoption is already at 54% and growing.
4. Predictive Maintenance
Predictive Maintenance is a standout use case for AI in field service. By monitoring equipment condition and usage patterns, AI can recommend the best time to service an asset, before failure occurs.
While only 40% use it today, 59% plan to adopt it, making predictive maintenance one of the fastest-rising priorities in the industry.
5. Diagnostics & Troubleshooting
AI-assisted diagnostics are helping technicians resolve issues faster, with more accuracy. Whether through guided workflows or in-the-moment diagnostic support, this use case is already in use by 42% of companies to improve first-time fix rates.
6. Customer Self-Service
Customers increasingly expect the ability to troubleshoot on their own. AI-powered chatbots and support widgets are making that possible, offering guided steps for basic issues. Adoption is still early (29%) but gaining traction quickly.
7. Training & Knowledge Sharing
AI is helping companies deliver just-in-time training to technicians based on skill gaps, performance or job type. It also improves access to internal knowledge bases in the field – especially valuable when onboarding new hires or upskilling tenured staff.
8. Content Creation
AI tools are being used to generate internal documentation, training materials and customer-facing guides.
50% of organizations report using AI for content creation.
This is a practical and cost-effective way to keep manuals and how-tos up to date without burdening internal teams.
9. Customer Service & Feedback Analysis
AI isn’t just improving customer service, it’s analyzing it. Chatbots can provide 24/7 support, while sentiment analysis helps leaders spot trends in feedback and quickly course-correct. These capabilities turn raw data into actionable service improvements.
10. Inventory & Asset Management
AI supports smarter forecasting of parts usage, reducing both stockouts and overstock.
Used by 45% of companies, this use case is a natural extension of field service automation, and a proven way to keep techs productive and customers satisfied.
Is Your Field Service Software Keeping Up?
The State of AI in North American Field Service report reveals a consistent theme: most organizations (75%) are only somewhat or not very satisfied with their organization’s current use of AI.
Many field service management platforms are still catching up when it comes to AI-powered diagnostics, customer feedback automation or in-the-field technician support.
If your existing software is falling short, or innovation is not happening as quickly as you need, custom field service software may be the better path forward. A custom-built app gives you the control and flexibility to adopt the AI capabilities that matter most – faster, and without waiting for a vendor roadmap.
At Big Fish, we help field service companies build custom software that fits how they actually work. Whether you’re looking to deploy AI in service operations, automate workflows, or improve technician tools, we’re here to help you get there.
Curious what a custom solution could look like for your operation?
Let’s talk. We’ll help you explore what’s possible, and whether custom development is the right fit.
