Upskilling Farmers and Farmworkers
How might Washington update the education and job training infrastructure for farmers and farmworkers to adapt in the age of AI?
Washington agriculture faces a growing workforce challenge including a shrinking labor supply, an aging producer population, and rising labor costs. As a major producer of labor-intensive specialty crops, Washington requires more agricultural labor than most states. Yet that labor is becoming harder to find. Fewer domestic workers are interested in seasonal farm work, resulting in a 465% increase in Washington’s reliance on the H-2A guestworker program, the federal program for temporary agricultural workers, since 2013. The producers who run these farms are also aging, averaging 59.3 years of age. At the same time, labor has become the largest production expense for Washington farms, with costs rising 117% between 2016 and 2024, more than double the national average.
The current workforce needs support to adapt to a changing industry, improve efficiency and safety, and retain experienced knowledge. Producers, farmworkers, and extension agents need opportunities to build familiarity with emerging technologies such as AI, understand their limitations, and develop the skills necessary to use them. Most farmers do not have the time or support to incorporate AI into their operations while also keeping their operations running. Farmers need help understanding what problems are ripe for AI solutions, a better sense of the tools out there, and solutions that fit their budget. Trusted intermediaries like agriculture extension agents can be helpful, but may lack the digital knowledge needed to effectively bridge that gap.
Opportunity Areas
The opportunity areas below are meant to inspire, not prescribe. The best ideas may come from directions we haven’t anticipated. We welcome ideas that address one area or span several.
How might we build a scalable support system that accompanies farmers and farmworkers through the adoption of AI tools without disrupting ongoing farm operations?
It is difficult to make a digital transition while keeping operations running. A key barrier is not just awareness of tools but the ability to configure and use them most effectively for a specific farm’s context.
Ideas might include:
- Trained adoption agents working directly with farms across the state, extending what Extension can offer
- Tools that help farmers configure AI systems for their specific operation so they get useful outputs from day one (e.g., digital twins)
How might we create a trusted space for Washington farmers and farmworkers to share what works, so that knowledge spreads across farms and regions rather than staying siloed?
Many farms are starting to experiment with and integrate AI tools, but currently everyone is figuring it out on their own. There is no trusted infrastructure to aggregate and share it. Farmers are more likely to trust outcomes reported by peers than by vendors or researchers.
Ideas might include:
- Benchmarking tools that let farmers see how peers are using technology and what results they are getting
- Peer networks where early adopters share what is working and build collective confidence in new tools
- Methods to capture practical on-farm knowledge and make it accessible across the sector
How might AI tools help farmers transfer knowledge to their workers in the flow of everyday farm operations?
Today, worker training on farms is largely informal, time-consuming, and hard to scale. The most promising tools will connect farm-specific knowledge to structured training, so that a farmer and experienced farmworkers can generate and contribute to farm-specific training materials.
Ideas might include:
- AI tools that generate worker training modules from farm-specific data across tasks such as pruning, irrigation, or pest management
- Digital assistants that guide workers through a task in real time
- Tools that make compliance and safety training easier to deliver and track across a seasonal workforce
- Approaches that incentivize and reward sharing of tacit or place-based knowledge to develop AI tools that benefit current and future workers
