As the off-highway industry battles the staggering impacts of labor shortages and deadly safety risks, autonomy is no longer a vision, it's a necessity. My career started as a mission to help farms improve productivity and safety and now has expanded generally to improve the way the world “works”. This mission is about protecting workers from harm and enhancing productivity in the dangerous, dirty jobs our world relies on daily. By leveraging autonomy, we can reduce risks and optimize efficiency, ensuring safer, more sustainable operations for generations to come.

From founding Smart Ag in 2016 (acquired by Raven Industries, later powering CNH’s autonomy at https://www.cnh.com/) to forming Mach in 2022 (www.mach.io), I’ve built autonomy from scratch, provided it as a third party, and scaled it in-house at a global OEM. With 458,000 new construction workers needed in 2025 and 20% of U.S. workplace fatalities in construction, the stakes are high. For OEMs eyeing autonomous machines, choosing to build internally or partnering with Mach to integrate our proven platform is critical. Below, I’ve tried to consolidate all the insights I have gained into a guide which can help OEM’s navigate this choice while backing it up based on our team’s vast expertise.

Why Autonomy Matters for Off-Highway OEMs

Two critical factors make autonomy a game-changer:

Labor Scarcity: Finding skilled operators for dirty, dangerous and repetitive jobs in agriculture, construction, or defense is increasingly difficult. A 2025 report shows 72% of U.S. employers face talent scarcity, with construction needing 458,000 workers and agriculture’s 40% labor shortage costing $3.2 billion annually in unharvested produce. For years, we’ve built bigger, faster machines to maximize operator efficiency, but this often led to issues like soil compaction, significant capital costs and downtime risk in farming. Autonomy reduces reliance on scarce labor, optimizing operations and increasing efficiency.

Safety: Off-highway jobs rank among the world’s most dangerous due to human proximity to powerful machinery. Construction accounts for 20% of U.S. workplace fatalities (1,074 in 2024), with a fatal injury rate of 4,800 per 100,000 workers, while agriculture sees 100 daily machinery injuries and a fatality rate of 23.1 per 100,000. By removing operators from hazardous environments, autonomous systems can save lives and create safer workplaces—an impact I’m proud we achieve daily at Mach.

Beyond labor and safety, autonomy drives sustainability, cutting fuel use, time, and yield losses. The agricultural robotics market is projected to grow from $5.2 billion in 2021 to $12.8 billion by 2026, and construction robotics will hit $1.1 billion, driven by these challenges. But the path to a safe, scalable, and efficient autonomous machine is complex. Here’s how OEMs can approach the decision to build in-house or partner externally.

Step 1: Understand the Technical Challenges

Autonomous off-highway machines are, essentially, heavy-duty robots operating in unforgiving environments — think deserts, Arctic regions, or dusty, wet construction sites. These conditions demand:

Ruggedized Hardware: Electronics must withstand extreme temperatures, vibration, and electrical surges while delivering high compute power for unmanned navigation. Off-the-shelf solutions often fail within a year or two, while off-highway machines are built for 10,000-hour lifespans. At Mach, we learned this the hard way, iterating since 2018 to develop our own field-tested, ruggedized systems. Our platforms enable edge computing, processing complex tasks like obstacle detection without cloud connectivity, and are safety-certifiable, meeting MIL-STD-810 standards and IP67 ratings for dust and water resistance.

Robust Software: Navigating unpredictable “edge cases” (e.g., irregular terrain, snow, or hidden obstacles like rocks and debris) requires extensive field testing. Prototyping basic navigation is easy, but ensuring safety and efficiency across diverse scenarios is not. Mach’s foundational model, built from years of real-world data, adapts quickly to new use cases, significantly reducing the deployment time and cost versus building these models from scratch internally.

Ongoing Support: Autonomy isn’t a one-and-done project. Software and hardware require continuous updates, technology updates, supply chain management to work through parts obsolescence and a dedicated team to address evolving needs and safety certifications over a machine’s lifespan.

Internal Consideration: While open-source autonomy models are widely available and can enable quick demonstrations, turning them into robust, production-ready systems often requires years of R&D, significant capital, and deep expertise across robotics, AI, and ruggedized electronics. My first autonomy company spent millions over several years to solve a narrow application—an experience that underscored the real investment required. At Smart Ag, we operated with a level of focus and efficiency that helped us move faster than many others in the field, yet development was still complex and resource-intensive.

Building the solution internally may offer more control and potential IP advantages. However, because the foundational technology for autonomy is increasingly accessible—and in some circles viewed as a future commodity—there’s a risk that the IP you develop offers limited strategic differentiation, particularly if your machinery addresses well-known applications. It’s a bit like engines: while every OEM uses one, very few gain a competitive edge from designing their own. Autonomy may follow a similar trajectory, where the value lies less in the core technology and more in how it's integrated, supported, and scaled for specific use cases.

Partnership Advantage: Partnering with Mach taps into our years of expertise integrating autonomous technologies across a diverse range of off-road machine platforms, from agricultural sprayers to construction machines and defense vehicles. While sensors and software get much attention, the true challenge lies in seamlessly embedding these systems into heavy-duty machines designed for harsh environments like dusty fields or rugged terrains. Our team, with deep roots in robotics and machinery, delivers ruggedized, high-compute hardware and adaptable software that work flawlessly within your platforms, significantly cutting development time and costs. Supporting dozens of OEMs, we’ve enabled navigation in GNSS-denied environments and reduced labor costs by up to 90%. Our foundational software model, leveraged across most use cases, continuously evolves with real-world data, delivering ever-improving performance and reliability to every OEM partner. With ongoing support for the entire machine lifecycle, Mach accelerates your path to market without the burden of building autonomy from scratch.

Step 2: Map the Development Process

To create an autonomous machine, follow these steps:

Achieve Full Drive-by-Wire: Ensure all critical functions (e.g., speed, steering) are digitally controlled with closed-loop feedback to validate performance. Many machines lack this, but Mach’s experience integrating with hundreds of vehicle types allows us to guide OEMs toward off-the-shelf systems that achieve an “autonomy-ready” state with a standardized CAN bus interface for scalable integration.

Define the Application: Clarify the job, acceptable limitations, and required functionality. This drives sensor selection, software design, and cost modeling, ensuring solutions fit specific environments like cluttered orchards or complex solar sites.

Model the Business Case: Autonomy doesn’t have to double a machine’s retail price. With Mach’s solutions, the hardware typically adds 10%–30% to the machine’s BOM cost, a range we’ve carefully priced to align with market expectations and deliver strong ROI for end customers. For example, in high-utilization applications exceeding 1,000 hours per year, such as livestock feeding or commercial mowing, this cost is readily justified by labor savings and efficiency gains. Recurring service costs for data, maintenance, and software updates should remain below the annual labor costs for the application, ensuring affordability. Before investing in autonomy, OEMs must understand the end customer’s ROI, factoring in productivity, safety, and sustainability benefits. Our team has experience working together with our OEM partners to support this process, helping define use cases and model business cases to ensure commercial success. The best time to engage with us is as soon as you have the use case defined.

Test Rigorously: Budget for extensive field and simulated testing to validate performance under real-world conditions. Measure key metrics like mean time to intervention (how often human oversight is needed) and mean time to failure (system reliability). Aim for the autonomous system to complete tasks in no more than 10% additional time compared to a human operator. For example, if a human completes a job like mowing or spraying in 1 hour, the autonomous machine should take no longer than 1.1 hours. This ensures productivity remains competitive while delivering safety and labor savings. With one agricultural OEM, we achieved a 1:8 operator-to-machine ratio, reducing labor costs by >87% and enhancing sustainability. Mach’s testing expertise helps refine systems to meet these targets, ensuring reliability and customer trust.

Build Scalable Infrastructure: Autonomous fleet management tools, like Mach’s Ops, are required to enable over-the-air updates, data analytics, and dealer/end-user support. It is critical that this is in place before trying to scale otherwise the support costs per machine will not be sustainable. Furthermore, due to the recurring costs associated with software enabled machines, OEMs need a streamlined way to handle payment processing and allow for the shift from one-off sales to recurring revenue.

Internal Consideration: Executing this process in-house requires a multidisciplinary team, months of engineering, and infrastructure like data management and software provisioning systems. Most OEMs lack the robotics expertise or budget for this, risking delays and cost overruns.

Partnership Advantage: Mach handles integration, pre-release testing, and the provisioning/support infrastructure allowing our OEMs to quickly deliver machines ready for market. Our OEM portal, customizes fleet management, streamlining operations and supporting dealers, freeing you to focus on your core business of building high quality innovative machines. Step 3: Weigh the Make-or-Buy Decision Here’s a framework to decide:

Step 3: Weigh the Make-or-Buy Decision

Here’s a framework to decide:

Build Internally:

• Pros: Full control, potential for proprietary IP and possibly lower per unit costs.
• Cons: Very substantial upfront investment (years, millions in R&D), slower time-to-market, and ongoing costs for a dedicated tech team. My first company’s journey taught me that even a constrained solution takes immense resources. A 2021 McKinsey survey estimates that early Level 4 autonomous vehicle use cases require $0.6–$1.5 billion for technology development, including hardware, software, and testing, with timelines spanning multiple years.
• Best For: OEMs with deep robotics expertise, large budgets, and patience for a 5+ year timeline.

Partner with Mach:

• Pros: Faster market entry, proven technology, and lower risk. On average, we are able to complete vehicle integration projects within 3-6 months. You leverage our hardware, software, infrastructure (e.g., phased-array radar for dust/vegetation navigation—learn more at www.mach.io), while maintaining ownership of all your proprietary data.
• Cons: Less control over IP, reliance on a partner, no need to allow 3rd party (Mach) access to data.
• Best For: OEMs seeking to innovate quickly, capture market share, and avoid reinventing the wheel.

When I left Case IH to start Mach, we acquired two companies with >20 years of combined experience in autonomy and ruggedized systems. This gave us a head start none of our competitors could match.

Step 4: Act with Speed and Vision

The early movers in off-highway autonomy will capture significant value. With agricultural robotics projected to reach $12.8 billion by 2026 and construction robotics hitting $1.1 billion, reducing 32% of accidents, the opportunity is now. Whether you build or buy, commit to:

• Clear Goals: Define success metrics (e.g., productivity, operator ratios).
• Customer Collaboration: Test with trusted clients to refine performance.
• Long-Term Investment: Budget for ongoing support to stay competitive.

At Mach, our goal is to simplify autonomy for OEMs, providing a factory integrated platform that lets you innovate on top of our foundation. Our team, with expertise from leading robotics and machinery firms, has partnered with OEMs across agriculture, construction, land care, maritime and defense to bring commercializable solutions to market quickly, and we’re ready to guide you through this transformation.

Ready to Explore Autonomy?

If you’re an OEM weighing autonomy, let’s talk. No sales pitches, just an open conversation to see if we can support your goals. If we can’t we will be the first to tell you that. Visit www.mach.io or email [email protected] to get in touch. The future of off-highway machinery is autonomous—don’t wait to lead the charge.