Key Takeaways
- ASI applies an OEM-agnostic autonomy stack (Mobius command & control plus add-on sensors) to off-the-shelf tractors and equipment, aiming for “one-to-many” operator ratios in large operations.
- The company prioritizes end-user and dealer partnerships over exclusive OEM integrations to accelerate real-world deployment.
- Reported benefits extend beyond labor efficiency to consistency, fuel and maintenance savings, and site safety—varying by operation and use case.
- Reliable performance in variable outdoor environments is addressed via multi-sensor fusion, improved GNSS constellations, and automotive-grade components.
- Successful adoption hinges on change management: workflow redesign, role transitions, and clear data-governance agreements with customers.
ASI: From Utah Lab Work to Cross-Industry Autonomy
For more than two decades, ASI has built autonomy solutions by adapting existing industrial machines rather than manufacturing robots from scratch. Ag Product Manager Bret Turpin—who joined ASI as a mechanical engineering intern and now leads customer-driven product strategy—summed up the approach: “We take a vehicle off the dealer lot and apply our autonomy tools to that platform.” The company’s roots include early projects with John Deere, followed by deployments across automotive proving grounds, open-pit mines, construction sites, distribution yards, and landscaping. Agriculture is a natural fit for Turpin, who grew up on a farm in Idaho: “I just love agriculture, so it’s a great fit to work in the world of robotics.”
Central to ASI’s model is Mobius, its command-and-control software designed to run mixed fleets. “One of the things that sets us apart,” Turpin said, “is we take any brand of machine, characterize it, adapt our automation technology, and then you can run a fleet of multiple-brand vehicles.”
Why OEM-Agnostic Matters
While ASI has collaborated with major OEMs, Turpin noted that direct integrations have not always translated to market rollouts. The company increasingly focuses on solutions that emulate operator inputs and plug into drive-by-wire systems already present on many modern tractors (throttle, brake, steering). This route preserves vehicle warranties while enabling autonomy without waiting on bespoke OEM software updates. “We’ve found the most success deploying through end users and dealer networks,” Turpin said, describing a faster path to value for growers and service providers.
Matching Solutions to Real Operational Needs
When a customer asks for “an autonomous tractor,” ASI starts with a site assessment: fleet composition, duty cycles, terrain, and labor constraints. For some, the immediate path is retrofitting current machines; for others, it’s aligning future fleet purchases with autonomy-readiness. The target outcome is one operator supervising multiple vehicles, which is where labor savings and consistency start to compound. Turpin pointed to lessons from automotive testing—where autonomous systems delivered more repeatable results over rough courses than human drivers late in a shift—as an analogy for agriculture’s repetitive tasks.
On measurable gains, ASI defines case-by-case KPIs with customers (e.g., matching or exceeding human-operated productivity). Turpin emphasized that side benefits often emerge: “Maintenance costs went down, fuel usage went down,” he said of prior deployments in other industries, while cautioning that specific percentages vary by site and should be validated per project.
Reliability in Real-World Conditions
Outdoor environments are dynamic: signal occlusion at field edges, dust, heat, and variable lighting. ASI addresses reliability through multi-sensor fusion (GNSS, wheel speed, obstacle-detection sensors) and by leveraging the rapid maturation of automotive-grade components. “With additional constellations in the sky, we don’t lose position around the trees like we used to,” Turpin noted. The team pairs proven components with environmental testing and is selective about adopting “latest and greatest” parts until early bugs are resolved. Where off-the-shelf components don’t exist, ASI has developed and manufactured enabling modules locally.
Where Autonomy Fits First For ASI: Specialty Crops and High-Utilization Fleets
Asked about crop focus, Turpin pointed to specialty crops—including sugarcane, orchards, vineyards, and vegetables—where equipment sees more days of use per year and repetitive operations create strong autonomy economics. “Higher utilization helps the model,” he said, adding that ASI has historically done less in small grains, where large OEMs are already active. The company’s sweet spot remains larger corporate operations seeking labor leverage and consistent execution across big acreages or complex multi-tasking workloads.
AI, Analytics, and the Next Layer of Capability
ASI has used elements of machine intelligence for years (e.g., sensor-driven models), and its R&D team is now exploring how modern AI can speed problem-solving in perception, planning, and diagnostics—while staying within well-defined boundaries. “There are places you should use it and places you shouldn’t,” Turpin said. The near-term emphasis is on blending established control methods with learning-based tools to improve overall system capability and development velocity.
Data Governance: Security, Access, and Ownership
Data access has evolved from strictly site-local systems to more collaborative support models. Turpin described customer-by-customer agreements that spell out access, security protocols, and segregation measures: “We really need access to data to better support you,” he tells customers, “and then we put the security around it so it’s not bleeding over.” The principle: farmer-first governance, explicit contracts, and secure channels that enable remote diagnostics and improvement while respecting ownership and privacy.
Adoption’s Hardest Part: Change Management
Technology alone doesn’t deliver ROI; organizations do. Turpin called change management the critical success factor—planning role transitions (e.g., moving operators into multi-vehicle control, maintenance, or other functions), training teams to manage breakdowns differently, and re-sequencing workflows for autonomous execution. “Progressive farms are saying, ‘We already have labor shortages, and they’ll get worse. How do we roll this out?’” he noted. The cautionary tale: farms that expect a plug-and-play experience without operational changes risk disappointment.
Partnerships that Move the Needle
Beyond OEM dialogues, ASI prioritizes end-user partnerships and dealer collaborations to ensure support, services, and uptime in the field. “It’s all about those relationships,” Turpin said. Joint efforts with large farms and construction companies have proven instrumental in early adoption, while dealer networks provide on-the-ground installation and service capacity tailored to regional needs.
Looking to 2035 For ASI
Asked to peer ahead, Turpin framed the next decade as sustained, incremental capability growth once robust base systems are running: data-driven improvements, more efficient operations, and wider task coverage. “There are plenty of problems to solve in my career—and my kids’ careers—in this space,” he said. ASI’s VP Alice DiSanto added a light note on long-term ambition: after land and sea, “interstellar” is a tongue-in-cheek destination—once adoption on Earth is squared away.
