During Field Service Palm Springs 2025, industry leaders convened to explore how artificial intelligence is transforming field operations and technician safety. In a compelling fireside chat, Rajib Bora, VP Field Services at Freudenberg e-Power Systems, shared practical applications of AI in battery manufacturing and large-scale field service. This session provided actionable strategies for decision-makers focused on reliability, scalability, and safety in the field service vertical.

Key Takeaways

1. Big Data is the New Backbone

As battery operations scale globally, the sheer volume of BMS data is driving a shift toward automated analysis. AI enables continuous monitoring and rapid identification of anomalies, making it easier to manage fleets and battery health at scale. This data-centric approach is becoming essential for leaders aiming to maximize uptime and safety while handling larger asset portfolios.

2. From Reactive to Proactive Service

Traditional service models relied on technicians reacting to problems as they arose. With AI-driven monitoring, the transition to a proactive service model means customers receive warnings about battery health before failures occur. By preempting issues, organizations cut downtime, improve customer satisfaction, and set a new standard for operational reliability.

3. Scaling Without More Staff

The demand for field technicians is outpacing supply. Leveraging AI workflows, Freudenberg is scaling battery pack production sixfold without proportionate increases in headcount. AI’s real-time diagnostics automate boring, repetitive tasks, freeing technicians to focus on high-value work and enhancing both labor efficiency and safety—even as customer bases grow.

4. Prioritizing Safety and Sustainability

Safety remains vital in field operations, and battery management systems (BMS) play a critical role in preventing incidents like thermal runaway fires. By integrating AI with BMS data, companies more effectively monitor risks and maintain sustainability standards, protecting both their staff and the communities they serve.

5. Building Infrastructure for Future Growth

AI-powered field service demands new infrastructure and training. Investing in robust digital systems and teaching AI agents proper boundaries is crucial for reliable performance as operations scale. Leaders should recognize that effective AI deployment isn’t just about technology—it's about people, training, and long-term adaptability.

In Their Words

“We’re building an AI model that can periodically report the health and condition of our battery packs... Soon, we’ll be able to warn the customer about the state of battery health before failure happens, by continuously monitoring BMS data and proactively identifying anomalies.” — Rajib Bora, VP Field Services, Freudenberg e-Power Systems

Why It Matters

AI-fueled labor optimization is rapidly redefining the landscape for field service organizations. As companies expand operations, balancing safety, scalability, and efficiency is no longer optional. Rajib Bora’s insights highlight a pragmatic path toward reduced downtime, enhanced customer satisfaction, and better resource utilization. Leaders in field service must embrace data-driven automation to adapt to new safety standards and sustainability mandates, ensuring they remain competitive and resilient in a changing marketplace.

Actionable Insights

• Automate diagnostics: Use AI to handle routine battery health checks and fault detection.
  
• Transition to proactive support: Leverage real-time data to prevent failures before they happen.
  
• Invest in technical infrastructure: Build scalable systems for big data and AI deployment.
  
• Prioritize technician training: Equip teams to interact with AI tools for safer, more effective operations.

Go Beyond the Blog

Want more insights from Field Service Palm Springs? Explore the full agenda and learn about upcoming sessions to stay ahead in field service innovation.