Robotics, AI shaping future of industry workforce
Agtech is branching beyond advanced combines and vertical hydroponics. Like many other industries, agriculture is embracing robotics and artificial intelligence (AI) as workforce aids for the next generation.
Experts say these assets are becoming critical fixtures for precision agriculture because of their ability to enable data-driven decision-making and make farms more resilient, productive and sustainable.
AGRICULTURE AUTOMATION DRIVERS
In 1950, around 9.93 million farmworkers — some hired, some family members — labored on U.S. farms, according to the USDA’s Economic Research Service. By 2000, that number decreased to 1.19 million, and shortages persisted.
These vacancies are motivating stakeholders to invest in automation to keep harvests strong. Productive output is more important than ever, as food scarcity remains a concern even in wealthier nations.
Policy changes are also shaping how farms view automation equipment. Sustainable initiatives call for low- waste packaging, and traceability standards expect evidence of ethical sourcing. Agritech investments are becoming necessary to meet both the quality and quantity demands
of food production, especially amid severe food inflation.
In countries like Bangladesh, maize prices increased 30% between 2020 and 2025 because third-party stockpilers controlled the market, according to a report in The Business Standard. Farmers sometimes sell at a loss because they lack storage technology and financial security. Automation is crucial for empowering workers in similar systems and environments.
KEY FIELD APPLICATIONS
The versatility of automated robotics is why farms that can afford integration are prioritizing it. Large-scale machinery like tractors and harvesters can now operate autonomously with GPS guidance, reducing the need for drivers.
Smaller equipment like drones and soil monitors provide a comprehensive picture of crop health without time- consuming manual inspections. Thanks to precise visual cues and nutrient readings, farmers can detect disease early and make informed decisions that could save harvests.
Precision agtech — such as sprayers and weeders — can target issues before they spread. Some have centimeter-level accuracy, using up to 95% less chemical pesticides than conventional options while avoiding damage to surrounding plants, according to a July 2023 Revolutionized.com report.
Robotics and AI remain valuable after farmers ship their goods to packaging facilities. These companies can apply compliant, sustainable labels or detect anomalies in production.
Wyatt Mayham, founder of Northwest AI Consulting, works with several food packagers and agricultural clients who incorporate robots into end-of-line operations. He has noticed several benefits, the first of which is traceable quality control.
“One of our large food processors implemented a computer vision system to scan pack labels and best by dates at full production speed,” Mayham said. “The AI reads date codes and ensures accuracy 100% of the time and automatically rejects misprints. This reduced labeling errors by over 95%, cutting emergency product recalls and improving compliance.”
He said some clients are using robotic arms to pack and palletize, enhancing efficiency. Others are using sustainable smart packaging designs to test hundreds of prototypes in search of durable yet eco-conscious options.
PMMI, The Association for Packaging and Processing Technologies, monitors how these integrations advance sustainability.
Jorge Izquierdo, PMMI vice president of market development, said, “Digitization and AI help companies reduce waste by improving quality control and minimizing packaging errors. Predictive maintenance ensures that machines operate at peak efficiency, reducing energy use and unnecessary wear and tear. Additionally, the shift to AI- supported digital processes allows companies to move away from wasteful paper-based inspections and training.”
EVOLVING ROLES AND REQUIRED SKILLS
Digital transformation necessitates upskilling and training current employees. Their responsibilities will shift from tedious manual labor to harvesting and packaging optimizations. Ideally, robotics and AI will allow workers to participate in more high-value tasks that increase job satisfaction and engagement.
Izquierdo also said that robotics and AI automation could help solve pain points in areas like canning and bottling.
“Food packaging operations, especially those with repetitive or high-precision tasks like palletizing and inspection, have traditionally relied on manual labor,” Izquierdo said. “However, as experienced workers become harder to retain and upskill, connected worker platforms powered by AI are filling the gap.”
Roles are becoming tech-enabled instead of physically intensive. Agricultural and packaging professionals will have new opportunities in data analytics, robotic maintenance and AI training. Additionally, predictive tools can help employees better detect maintenance concerns before they cause costly machine failures in places like bottling lines, which demand constant synchronicity, Izquierdo said.
More involved and influential workflows could boost retention for agricultural and food companies. Izquierdo highlighted one example from a 2024 PMMI report, “The AI Advantage in Equipment: Boosting Performance and Bridging Skills Gap,” detailing the benefits of AI in equipment.
“A major paper and packaging company saw a 72% reduction in onboarding time for new hires and an 18% increase in frontline productivity after deploying the system,” he said. “This kind of technology not only preserves institutional knowledge but ensures consistency and safety across shifts, even in high-churn environments.”
ADAPTATION CHALLENGES
From up-front costs to a lack of infrastructure, there are many reasons agriculture and food companies have yet to fully embrace robotics and AI automation. Digital literacy is also a barrier, as many professionals remain unfamiliar with these systems and their capabilities.
Mayham said the benefits come with challenges, pointing to legacy integration, data quality and workforce training as the primary hurdles.
“Human oversight still remains vital,” he said. “AI handles repetitive tasks and flagging, but maintenance, unexpected jams, shutdowns and supply chain issues still need experienced operators on the floor.”
Izquierdo agreed that obstacles to AI adoption remain.
“Many AI systems rely on access to sensitive operational data to function effectively — data that companies may be hesitant or legally restricted from sharing,” he said. “In addition, the inconsistent quality of data collection infrastructure across facilities can slow implementation, especially when older machinery lacks digital connectivity or standardized output formats.”
Izquierdo said companies’ workforce may need buy-in, especially from older and long-term employees. AI distrust is a prominent concern in these demographics, which suggests AI should “augment a workforce” instead of replacing corporate-sponsored training. Pilot projects, he said, can be the best way to introduce these tools without creating too much downtime.
