Artificial Intelligence and the Future of Work in Agriculture

October 2, 2017

Agriculture is undergoing a digital revolution, and the huge potential of Artificial Intelligence (AI) will accelerate the pace of disruption and rapidly change how our food gets from paddock to plate.

AI, with applications ranging from image processing algorithms, to cloud biology, to on-farm sensors, could have a positive impact on the economic and environmental sustainability of agriculture. As we understand more about the complex natural systems in which our crops grow, and have access to highly practical recommendations from agronomist-trained algorithms, farmers will use fewer chemicals and pesticides. And as we digitize the agricultural supply chain, we will reduce the amount of food we waste, improve our ability to respond quickly to consumer needs, and more toward seed-to-stomach transparency at the swipe of a finger. AI will eliminate inefficiencies, bring convenience to consumers, and helps farmers capture a larger percentage of each dollar we spend.

But the disruptive potential of AI raises a critical question about the future of agriculture that has investors excited, and rural communities uneasy: will AI replace jobs?

Even experts disagree on what AI will mean for the future of work in agriculture. Will technology create jobs and enable a world of abundance, of cause mass unemployment, social inequality, and unrest? Will it take years for AI to master the extreme complexity of soil and weather, or can an injection of capital make it happen quickly?

For Australian agricultural jobs in particular, understanding the role of AI and its impact on the future of work is critical. The agricultural industry provides over 1.6 million jobs to the Australian economy, and is responsible for around 12% (155 billion) of GDP, according to the National Farmers Federation. Hundreds of thousands of immigrants come to Australia each year, increasingly settling (and working) outside urban areas where they help to make rural and regional economies more productive.

I believe AI will accelerate these productivity gains, continuing to bring positive impacts to agriculture and agricultural jobs.

Bye Bye Dull, Dangerous, and Dirty Jobs

I recently had the opportunity to tour an abattoir, and there’s nothing like an assembly line of blood and knives to make it clear that many of the jobs in agriculture are dull, dirty, and dangerous. Fortunately, machines are much better at these jobs than humans, and can free up humans to do higher value tasks that are not only safer, but also much more enjoyable.

Consider how much more helpful, engaging, and productive a checkout person can be when a machine handles the nitty gritty of the transaction, freeing up the person to focus on customer experience. This is not just theoretical: research from the Massachusetts Institute of Technology (MIT) highlights how companies and workers can both win when they invest in good jobs that leverage the very skills that make us human and complement them with the latest technologies. We can expect companies that invest in both technology and people to reap the same benefits in agriculture.

More Efficient Agribusinesses Can Create Better Jobs

As digital technologies continue to penetrate agriculture, the least digitized industry according to McKinsey, inefficiencies within business operations and along the supply chain will be eliminated. The coupling of algorithms, data from multiple sources (think satellites, drones, and airplanes), and sensors (think automated irrigation systems) will improve decision making for farmers and agronomists.

At an even more basic level, though, technologies like machine learning will enable businesses to do scenario planning. Imagine asking your tablet whether it makes more sense (i.e., profit) to hire a contractor for a task, or to buy the machine outright and complete it yourself. The same goes for financial decisions around working capital, contracts, and tax optimization. And just as Xero has become a tool for accountants and not an accountant itself, so too will agribusiness analysis tools augment the capabilities of financial controllers and CFOs.

With better decisions and increased efficiencies, business will save money that can be reinvested to train employees to do higher level tasks and create more value for customers. Improving customer experience, as well as creating value-added, higher-margin products, helps differentiate the business and ensure longevity. And better jobs mean happier employees and reduced turnover.

Not sold yet on jobs getting better with AI? California-based agtech company Food-Origins illustrates how this is already happening. They used their data collection systems to capture geospatial harvest activities of workers, including their walking and harvesting activity, for a week. They then used their equipment to analyze and optimize worker activity, and had the same workers harvest again with the Food-Origins recommendations. The technology helped the workers to earn 25% more, while saving the farmer 10% per unit, because AI helped the workers harvest more systematically, rather than chasing the “low hanging fruit.”

New Industries Will Create New Jobs

AI will unlock potential in new areas of agriculture, and these new businesses will need employees. Controlled farming of existing products like leafy greens, and new products, like insects, is increasingly possible and cost competitive with AI.

As these industries mature, new jobs in agriculture are being created. Urban farming supply chains already require dedicated software and hardware providers (e.g., LEDs), and container-based farms are creating new opportunities for aspiring farmers without access to land.

Similarly, as the insect supply chain matures to service food, feed, and other future industries, jobs will be created to haul and manage food waste, research new uses and the potential of new insects, and market and sell products.

There’s undeniably still a lot of work to be done to harvest the full potential of AI in agriculture. There are also ethical (e.g., responsible governance of gene editing techs), social (e.g., global GMO acceptance), and technical (e.g., extent to which data is open source and/or standardized) questions to be answered.

But with this digital agricultural revolution already on our doorstep, I am extremely positive about both the power of emerging technologies, as well as the jobs they will replace, change, and create.

A version of this article was published on Australian Farmers on September 19, 2017.