IFS, a leading provider of Industrial AI software, has partnered with Boston Dynamics, the global leader in mobile robotics, to transform how asset-intensive industries manage and optimize field operations. This collaboration integrates Boston Dynamics’ autonomous inspection robots with IFS.ai’s agentic AI system, creating a fully autonomous solution that connects real-time sensing, predictive analytics, and responsive actions directly in the field. Amid growing labor and skill shortages causing service interruptions, this technology aims to support and augment field workers, ensuring more reliable operations.
The joint solution was unveiled at Industrial X Unleashed in New York on November 13, showcasing an innovative fusion of physical AI through Boston Dynamics’ Spot robots and intelligent decision-making from IFS.ai. Spot robots conduct industrial inspections by collecting vital asset data such as thermal imaging for overheating, audio detection of leaks, analog gauge readings, and hazard identification. This data instantly feeds into IFS.ai, where agentic AI evaluates conditions, makes predictive decisions, and automatically triggers appropriate responses, establishing a seamless, end-to-end autonomous workflow from detection to execution.
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Focused on critical field operations across manufacturing, energy, utilities, mining, and other asset-heavy sectors, this collaboration targets the majority of the global workforce—70%—who work outside traditional desk environments. By combining robotics and agentic AI, IFS and Boston Dynamics unlock valuable operational improvements in areas previously underserved by generic AI, advancing safety by reducing human risk, enhancing efficiency through faster decision-making, and maximizing uptime with predictive maintenance and automated interventions.
Together, IFS and Boston Dynamics are targeting measurable improvements across three critical operational metrics:
- Safety: Autonomous inspections reduce human exposure to hazardous environments while increasing inspection frequency and thoroughness
- Efficiency: Intelligent automation enables faster decision-making and response times, optimizing resource allocation
- Uptime: Predictive insights and automated actions help prevent failures before they occur, maximizing asset availability
Christian Pedersen, Chief Product Officer, IFS, said: “Asset-intensive organizations face unrelenting pressure to improve operational performance. Together with Boston Dynamics, we’re delivering a truly autonomous system that connects the physical and digital worlds for the first time. IFS.ai and IFS Loops turn robot observations into enterprise action, from preventative maintenance scheduling to predictive failure analysis and automated anomaly detection. Data flows from the field into enterprise systems, decisions are made autonomously, and actions are executed back in the field, all within a single integrated platform.”
Dr. Merry Frayne, Director of Product, Boston Dynamics, commented: “This collaboration represents the future of industrial operations. Our robots excel at navigating complex environments and gathering critical data. Combined with IFS’s agentic decision-making capabilities, we’re enabling organizations to achieve levels of operational excellence and safety that simply weren’t possible before.”
Ron Utterbeck, CIO, Eversource, an IFS customer, said: “As the largest New England energy provider managing critical infrastructure across multiple states, this integration has the potential to radically transform our operations. As our grid continues to advance we need to utilize not only traditional data gathering but more advanced data gathering and modeling. To meet the reliability and the energy demands for our customers, we look forward to the opportunity in utilizing advanced industry technology such to enable data collection at a different level that can support routine inspections of substations and facilities with automatically prioritizing and dispatching our crews. This will allow our highly-skilled crews to be focused on the right priorities at the right time and ensure mission-critical work is completed. It’s a genuine shift from reactive to predictive maintenance.”
