Sustainability Atlas
Robotics & Automation·14 min read··...

Interview: the skeptic's view on Agricultural robotics & autonomous farming — what would change their mind

A practitioner conversation: what surprised them, what failed, and what they'd do differently. Focus on safety cases, unit economics, deployment constraints, and ops playbooks.

Despite a global agricultural robotics market valued between $11-17 billion in 2024 and venture capital funding rising 9% year-over-year, 30% of ag-tech startups remain at high risk of liquidation—and only 27% of farms use precision agriculture technologies. We spoke with skeptics across farming operations, agricultural research, and sustainability advocacy to understand their reservations about autonomous farming and, critically, what evidence would shift their perspective.

The gap between industry hype and field-level adoption tells a sobering story. Abundant Robotics, the celebrated apple-picking startup backed by Google Ventures, shut down in 2021. PrecisionHawk, a leading agricultural drone manufacturer, filed for bankruptcy in December 2023. Farmwise closed operations in April 2025 before being acquired at distressed value. Yet proponents insist the technology is ready. Here's what skeptics are seeing that investors might be missing—and what would convince them otherwise.

Why It Matters

Agricultural labor shortages have reached crisis levels: 60% of U.S. agribusinesses postponed projects in 2024 due to inability to secure seasonal crews, and labour accounts for 40% of production costs on high-value farms. The UK has lost 2.5 million farm jobs over the past decade. Dairy farms cannot access H-2A seasonal worker visas because their operations require year-round labour. The demographic reality—an aging farm workforce with few young replacements—creates genuine urgency for automation.

Yet skeptics argue that urgency is precisely the problem. "When we keep running into the same problems, it's not our tools needing reworking—it's our failure to understand the system we're working in," argues Ryan Erisman, a Wisconsin farmer who has written extensively on regenerative agriculture. For these practitioners, agricultural robots represent another round in an arms race against nature rather than a fundamental solution to food system challenges.

The stakes extend beyond farm economics. Agriculture is the second-leading industry for workplace accidents in the United States; in the UK, fatal injuries occur 21 times more frequently per 100,000 workers than the cross-sector average. Farm workers face heat stress, musculoskeletal disorders, pesticide poisoning, and mounting mental health concerns. Robots could address these hazards—if they actually work at commercial scale.

Understanding skeptic perspectives matters because they identify failure modes that optimistic projections overlook. Their concerns about unit economics, outdoor complexity, and systems integration represent real barriers that will determine which robotics investments succeed and which join the growing list of agricultural technology casualties.

Key Concepts

The Outdoor Complexity Problem

Agricultural robots face fundamentally harder challenges than their warehouse or manufacturing counterparts. Unlike controlled indoor environments, farms present unpredictable conditions that limit sensor reliability: variable lighting, dust, leaf occlusion, diverse soil types, and topographical variation.

"Operating outdoors is significantly harder than controlled warehouse or hospital environments," explains a senior researcher at a leading agricultural robotics lab. Technology must adapt to variable crop row widths, plant densities, weather conditions, and seasonal changes—often across different geographies and crop varieties within a single operation.

This complexity explains why harvesting robots for delicate crops remain commercially unviable. Apple-picking robots currently harvest at 1 apple per 5-10 seconds, compared to human workers who average 1 apple per second. For soft fruits like strawberries, robots frequently damage or miss produce entirely. The performance gap remains too wide for economic viability despite decades of research.

The Unit Economics Challenge

Skeptics consistently point to disconnected unit economics as their primary concern. High initial investment costs remain prohibitive for small and family farms—precisely the operations most vulnerable to labour shortages. Even with Robot-as-a-Service (RaaS) subscription models, cost benefits don't materialise where infrastructure is lacking.

A harvesting robot might theoretically pay for itself in 2-3 years through herbicide reduction, labour savings, and yield increases. But skeptics note that these calculations often ignore maintenance costs, downtime during critical harvest windows, and the technical expertise required for operation. "We find them very frustrating," one dairy farmer told researchers studying automated milking system adoption—a sentiment echoed across multiple studies of early adopters.

The consolidation dynamics also concern skeptics. Robotics development requires massive R&D investment, long sales cycles, and seasonal revenue patterns that squeeze standalone startups. This pushes the sector toward acquisition by major equipment manufacturers, potentially limiting competition and keeping prices elevated.

The Interoperability Gap

Existing farm equipment represents decades of capital investment that farmers cannot simply abandon. Yet agricultural robots often struggle to integrate with legacy machinery, creating operational friction that undermines theoretical efficiency gains.

The absence of shared communication protocols and data standards risks industry fragmentation. Farmers face the prospect of managing multiple proprietary systems that don't communicate effectively—each requiring separate training, maintenance relationships, and data management approaches.

What's Working

Precision Spraying Delivers Measurable ROI

John Deere's See & Spray technology, developed by Blue River Technology (acquired for $305 million in 2017), uses computer vision to identify crops versus weeds at the pixel level, spraying herbicide only where needed. Real-world deployments show herbicide reductions of up to 90%, with some implementations achieving 98% reduction.

Solinftec's Solix Ag robot, released in November 2024, demonstrates similar capabilities with fully autonomous operation including 100% autonomous docking stations. These precision spraying systems address a specific, high-value problem—herbicide costs and resistance—with measurable returns that justify investment even for skeptical adopters.

Dairy Automation Reaches Commercial Maturity

Automated milking systems (AMS) represent the most mature segment of agricultural robotics. DeLaval and Lely systems have achieved widespread commercial deployment, with documented improvements in productivity, cow comfort, and reduced labour requirements.

Even skeptics acknowledge that dairy automation works—though many note the substantial learning curve. "The technology works, but you need to completely redesign your operation around it," observes a dairy consultant. "That's a different proposition than adding a tool to your existing workflow."

Targeted Applications in Controlled Environments

Vertical farming and controlled-environment agriculture (CEA) provide conditions where robots can operate more reliably. Indoor growing environments eliminate the variability that plagues outdoor agricultural robots, enabling consistent performance for tasks like planting, monitoring, and harvesting.

Companies like Iron Ox and AppHarvest (which acquired Root AI's Virgo harvesting robot for $60 million) have demonstrated functional systems in greenhouse and vertical farm settings. The challenge is that controlled-environment production currently represents a tiny fraction of global agricultural output.

What's Not Working

Harvesting Robots Remain Commercially Unviable

Despite substantial investment, no general-purpose harvesting robot has achieved commercial scale for outdoor soft fruit or specialty crop operations. Abundant Robotics' 2021 shutdown—despite backing from Google Ventures, Yamaha Motor Ventures, and successful trials with T&G Global in New Zealand—demonstrated that even technically capable systems cannot survive without sustainable unit economics.

FFRobotics (Israel), Tevel, and Ripe Robotics (Australia) continue development, but none has achieved the speed, reliability, and cost structure required for widespread adoption. Skeptics view continued investment in harvesting robots with understandable wariness given the sector's track record.

Regulatory Frameworks Lag Innovation

The EU's 2006 Machinery Directive hasn't seen meaningful updates addressing autonomous agricultural equipment, effectively requiring human operators behind the wheel and limiting autonomy benefits. U.S. and EU policymakers have not consistently addressed agricultural robot standards, creating uncertainty that complicates procurement decisions and investment planning.

The International Forum of Agricultural Robotics (FIRA) has formed to coordinate standards harmonisation, but progress remains slow. For skeptics, this regulatory gap represents both a practical barrier and a signal that the technology isn't ready for widespread deployment.

Infrastructure Deficits Undermine Field Performance

Rural areas lack the charging stations, reliable internet connectivity, and technical support infrastructure that robots require. Battery charging and fuel refills in remote locations remain problematic; solar-powered and hybrid solutions are still in research phases rather than commercial availability.

Connectivity issues particularly affect cloud-dependent systems that require real-time data processing. A robot that works perfectly in demonstration conditions may fail when deployed to farms with limited cellular coverage or unreliable power supply.

Data Ownership Creates Unresolved Tension

Farmers express significant concern about who owns the data collected by agricultural robots. Trade secrets, competitive intelligence, and privacy considerations create friction that slows adoption. Unclear rules on data ownership, sharing, and monetisation represent a governance gap that the industry has not addressed.

Key Players

Established Leaders

  • John Deere — Acquired Blue River Technology ($305M, 2017) and Bear Flag Robotics ($250M, 2021). See & Spray Ultimate system launched 2024. Dominates large-scale row crop automation.

  • AGCO Corporation — Sold grain division in August 2024 to focus on precision agriculture. Invested in Brazilian AI agronomic mapping startup Bem Agro in February 2024.

  • CNH Industrial — Parent company of New Holland and Case IH. Partnered with Bluewhite in June 2024 for autonomous orchard and vineyard operations.

  • Kubota — Major Japanese manufacturer expanding agricultural robotics portfolio across Asian markets with government support.

  • DeLaval/Lely — Leading automated milking system manufacturers with established commercial deployments worldwide.

Emerging Startups

  • Monarch Tractor — Secured $133 million Series C in July 2024, the largest agricultural robotics investment of the year. Develops electric, autonomous tractors with driver-optional operation.

  • Carbon Robotics — Laser-based weed control systems achieving commercial deployment. Uses high-powered lasers to eliminate weeds without herbicides.

  • Bluewhite — Retrofit autonomy solutions adding autonomous capability to existing tractors via RaaS subscription model.

  • Tevel — Israeli company developing tethered drone fruit pickers. Won 2021 RBR50 Innovation Award.

  • Solinftec — Brazilian company with Solix Ag robot achieving 98% herbicide reduction. Released 100% autonomous docking station in August 2024.

Key Investors & Funders

  • DCVC (Data Collective) — Early Blue River Technology investor; continues active investment in agricultural AI and robotics.

  • Google Ventures/GV — Backed Abundant Robotics; maintains agricultural technology portfolio.

  • Yamaha Motor Ventures — Invested in Abundant Robotics; active in agricultural drone and robotics space.

  • USDA/Agricultural Research Service — Federal research funding supporting robotics development across U.S. land-grant universities.

  • EU Horizon Europe — Major funding source for European agricultural robotics research and demonstration projects.

Action Checklist

  1. Audit labour vulnerability exposure: Map which operations face the greatest labour shortage risk and quantify current costs including recruitment, training, seasonal wage premiums, and productivity losses from unfilled positions.

  2. Evaluate precision spraying first: Start with proven technologies like See & Spray that deliver measurable herbicide reduction and demonstrable ROI before considering more experimental harvesting or general-purpose robots.

  3. Assess infrastructure readiness: Survey connectivity, power availability, and technical support access at each farm location. Factor infrastructure investment into total cost of ownership calculations for robotic systems.

  4. Demand interoperability guarantees: Require data portability and equipment integration commitments from vendors before procurement. Avoid proprietary lock-in that limits future flexibility.

  5. Pilot before scaling: Run limited trials on representative fields or operations before enterprise-wide deployment. Document actual performance against vendor claims under real operating conditions.

  6. Plan workforce transition: Develop training programmes for existing staff to operate and maintain automated systems. Address job displacement concerns proactively with affected workers.

  7. Track regulatory developments: Monitor EU Machinery Directive updates, USDA guidance on autonomous equipment, and emerging international standards through FIRA and ISO working groups.

  8. Build contingency protocols: Develop manual backup procedures for critical operations when automated systems fail during harvest windows or other time-sensitive periods.

FAQ

Q: What would actually convince skeptics that agricultural robots are ready for widespread adoption? A: Skeptics consistently identify three threshold requirements. First, demonstrated commercial viability across multiple harvest seasons—not just successful trials, but sustained profitable operation. Second, interoperability with existing equipment rather than requiring complete system replacement. Third, total cost of ownership (including maintenance, downtime, and technical support) that compares favourably to labour costs in their specific region. A Wisconsin dairy farmer summarised it simply: "Show me ten farms like mine that have run these systems for five years and are still happy. Not cherry-picked showcase sites—real operations dealing with real problems."

Q: Why have so many well-funded agricultural robotics startups failed despite obvious market demand? A: The gap between laboratory capability and commercial viability is wider in agriculture than in other sectors. Outdoor environments present fundamentally harder challenges than controlled settings—variable weather, diverse crop conditions, and unpredictable soil types confound sensors and algorithms that work perfectly in testing. Additionally, agricultural markets have seasonal revenue patterns and long sales cycles that strain startup cash flows. Abundant Robotics had functional technology and major partnerships but couldn't achieve the market traction needed for continued funding when COVID-19 disrupted harvest seasons. The 30% of ag-tech startups at liquidation risk in 2024 face similar pressures: high development costs, extended timelines to profitability, and competition from well-capitalised equipment manufacturers.

Q: Are regenerative agriculture advocates fundamentally opposed to robotics, or are their concerns more nuanced? A: The opposition is more nuanced than often portrayed. Regenerative agriculture advocates argue that robots address symptoms rather than causes—labour shortages and pest pressure result from industrial monoculture systems that could be redesigned. However, many acknowledge that robots could support regenerative practices if designed appropriately. Precision weeding robots that eliminate herbicide use, for example, align with regenerative goals. The critique focuses on robots that enable continuation of extractive practices versus those that support transition to more sustainable systems. "We're not against technology," one regenerative farmer explained. "We're against technology that locks us into the same failed approaches with fancier equipment."

Q: How should procurement teams evaluate competing vendor claims about robot performance? A: Request verified performance data from operations comparable to your own in terms of crop type, scale, geography, and existing infrastructure. Vendor demonstration sites often operate under optimised conditions that don't reflect typical farm environments. Ask for total cost of ownership data including maintenance, software licensing, training, and downtime costs—not just equipment purchase prices. Speak directly with current customers without vendor mediation. Require contractual performance guarantees with meaningful remedies for underperformance. Finally, verify that claimed herbicide reduction, labour savings, or yield improvements have been measured under independent third-party protocols rather than self-reported by vendors.

Q: What role should government policy play in accelerating or regulating agricultural robotics adoption? A: Skeptics generally support updated regulatory frameworks that establish clear safety standards and liability rules for autonomous equipment—the current regulatory uncertainty creates risk for both farmers and manufacturers. Many also support infrastructure investment in rural connectivity and power access that would benefit robotics adoption alongside other applications. Views diverge on direct subsidies: some argue that subsidised adoption masks poor unit economics and delays market-ready technology development, while others contend that public support is necessary to bridge the gap between current costs and future scale economics. Most agree that data governance standards—clarifying ownership, privacy, and portability rules—should precede rather than follow widespread deployment.

Sources

The path forward for agricultural robotics requires honest acknowledgment of current limitations alongside continued investment in promising applications. Skeptics provide a valuable service by identifying failure modes that optimistic projections overlook. Their criteria for adoption—demonstrated commercial viability, interoperability, and competitive total cost of ownership—represent reasonable standards that the industry should embrace rather than dismiss. The $11-17 billion market will continue growing, but sustainable growth requires technologies that work for farmers, not just for investors and manufacturers.

Topics

agriculturalroboticswarehouse automationMRVLCAcompliancelast-mile

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