With over 30 years of experience in product development, Jason Penkethman is the Chief Product & Technology Officer at Simpro.
The field service industry is rapidly growing and diversifying, expanding from traditional trades to more complex, technology-dependent services. The U.S. market is expected to grow at a CAGR of 12.2% from 2024 to 2032, driven by increased demand and emerging technologies. For example, IoT integration with HVAC systems enables remote monitoring and predictive maintenance, and AR provides real-time visual feedback and training for technicians.
More advanced technologies can put even more pressure on trade businesses to adapt. Staying competitive means ensuring staff are adequately trained and can integrate complicated systems to provide comprehensive services. Also, the proliferation of AI-augmented software and tools amplifies the need for trade businesses to become proficient in AI advancements for both the use of their customers and in their own businesses.
The Digital Shift In Field Services
Trade businesses have largely joined the rest of the economy in digital transformation after relying on paper-based processes. Trade businesses are increasingly adopting some form of field service management (FSM) software, which enables them to streamline their operations in areas of service, maintenance and project-based workflows for estimating work, planning and scheduling, and managing their finances. FSM software can also help automate routine tasks, allowing technicians to focus more on productive work than on administrative tasks.
Key Areas Of Inefficiency
Despite these advancements, inefficiencies remain and reduce overall performance in field service operations. For an average-sized field services company, each technician may spend between six and eight hours per week on non-billable work such as manual data entry and administrative tasks, which I’ve found can result in a cost impact upward of hundreds of thousands of dollars per year. This is where I believe AI-based tools can have the greatest impact, helping close the inefficiency gap.
AI Opportunities For Field Service Operations
My company, Simpro, surveyed 1,000 commercial trade businesses across the U.K., Australia and New Zealand and identified two key priorities driving AI adoption:
• Time Savings: The majority of respondents cited saving time as their top priority. AI tools that automate administrative tasks and streamline workflows allow technicians to focus on the skilled work they’re trained for.
• Improved Service Quality: Many businesses also see AI as a way to enhance service quality. Tools that deliver accurate, real-time information to field staff can help boost customer satisfaction.
Other notable advantages included reduced errors and increased job satisfaction. While less common, these gains reflect how AI can address inefficiencies and support a more engaged workforce—especially when using tools like retrieval-augmented generation (RAG).
These priorities are already being realized through AI-driven advancements across key operational areas in field service. Below are some of the most impactful applications.
First-Time Fix Rate
IoT-enabled assets can provide companies with real-time data on remote equipment, which enables them to perform more efficient maintenance. When coupled with AI, it can enhance the ability to assign the right technicians to a job and improve first-time fix rates.
For example, Siemens augmented its wind turbine IoT monitoring with AI to enable predictive maintenance and smart scheduling, which reduced downtime by 20%.
Scheduling Conflicts
Inefficient scheduling can reduce productivity, delay customer service and increase operating costs. Using AI to learn from historical logistics, along with evaluating technician availability, skill sets and customer priorities, can optimize resource allocation.
CEBA Solutions notes that “UPS uses AI to continuously refine its logistics and dispatching algorithms. By learning from each delivery and service interaction, UPS ensures that its operations are always improving, leading to better service and operational efficiency.”
Travel Time And Costs
Excessive travel between job sites can increase fuel costs and reduce productive work hours. AI-augmented job routing with fleet management can analyze weather, traffic and road conditions to suggest optimal routes in real time. More importantly, it enables real-time factoring of technician location, skill sets and customer priorities that can change during the course of a day.
Inventory Management
Inefficient inventory management results in service delays, multiple trips and increased resolution time. AI can be used to track inventory, forecast demand and automate reordering, which can reduce repair delays and improve first-time fix rates.
Communication Breakdowns
Inadequate communication between the central office and field technicians leads to service delivery errors, higher costs and lower customer satisfaction. AI can enable real-time information sharing to improve communication and service, saving technicians time and improving documentation.
Advanced AI Applications In Field Service Management
Integrating increasingly sophisticated AI technology can help transform field service management, going beyond the use of AI to cut down on inefficiencies. Important developments include:
• Augmented Reality (AR) For Training And Troubleshooting: AR can help improve training and troubleshooting by showing technicians digital information on top of what they see, as well as by enabling remote expert assistance.
• AI And The Industrial Internet Of Things (IIoT) In Predictive Maintenance: AI can make the transition from proactive to predictive maintenance possible by evaluating sensor data from linked devices.
• AI-Powered Chatbots And Virtual Assistants: These technologies can reduce administrative workloads by answering consumer questions, setting up appointments and giving technicians up-to-date information.
• Automated Reporting And Documentation: AI can automate reports, using RAG to share data from trusted sources, which can help reduce admin work and improve record accuracy and timeliness.
Overcoming Challenges
Despite its potential, AI adoption faces resistance in some segments of the trade services industry. Concerns regarding data security, prices and implementation difficulty are widespread.
• Education: Businesses will require clear, tangible evidence of AI’s return on investment.
• Integration: It is critical to ensure that any existing CRM, ERP, payroll and other systems work seamlessly together.
• Trust: Businesses need to develop transparent policies on data privacy and security.
Staying Ahead
While technology like AI can help field service businesses improve consumer experience and efficiency, it’s important to have a strategy in place. In this way, AI can transform trade businesses, and field services can leverage its potential to move from paper to predictive intelligence, increasing innovation and productivity.
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