In the heart of Somerset, a small monitor is revolutionizing dairy farming. Fixed to a cattle chute at Agri-EPI’s South West Dairy Development Centre, this ‘hoof monitor’ uses AI and thermal imaging to detect lameness in cows weeks before a farmer might notice. This early intervention doesn’t just save farmers around £300 per cow in treatment costs, reduced yield, and extended lifespan; it also enhances animal welfare and reduces carbon emissions per litre of milk produced. This is just one example of how AI is making waves in agriculture, with sensors detecting livestock diseases, autonomous robots surveilling crops, and monitors tracking bee wingbeats.
AI’s role in agriculture has evolved significantly since the 1980s when rudimentary sensors were used for climate control and detecting reproductive readiness in livestock. Today, AI’s ability to collect, analyze, and make recommendations based on vast amounts of data has unlocked new potential applications and benefits. McKinsey estimates that AI could eventually contribute $250bn to global agriculture through cost savings, improved yield, and additional sales.
The applications of AI in agriculture can be broadly divided into three core pillars: mitigating risk, driving efficiencies, and creating additional revenue streams. Sophisticated monitoring tools like the hoof monitor fall into the first category, detecting diseases in crops or livestock, or forecasting climate events. Precision farming bots and autonomous tractors, which speed up production or reduce error, fall into the second category. The third category includes tools that do a bit of both, such as Treefera’s AI-enabled platform, which collates data from producers and exchanges it for carbon credits.
The potential benefits of AI in agriculture are vast. It’s thought AI has the potential to reduce annual agricultural operating costs by more than a fifth (22%). AI can help farmers make smarter, data-driven decisions, optimise resource use, improve yield quality, and increase profitability and sustainability. As farmers increasingly integrate AI into their operations, they can improve distribution, reduce waste, and ensure that consumer demand is met.
The benefits of sourcing from AI-equipped farms span the entire supply chain. Retailers and suppliers can reap the rewards of higher yields, lower costs, and better-quality food on supermarket shelves. Moreover, AI equips farms with real-time data on animal welfare and environmental conditions, providing substantial evidence to verify and support on-pack welfare claims. This is crucial at a time when consumers are increasingly concerned about ‘welfare washing’ and suppliers face growing regulatory pressure to track and report on sustainability metrics.
However, despite these benefits, the industry is not rushing to adopt AI. For some established technologies, like sensors on livestock, adoption is pretty widespread. But when it comes to the type of AI being splashed across headlines, there’s greater hesitation. Much of it isn’t commercially available yet, and the price tag can be prohibitive. Historically, AI has been developed by tech providers and academics with little input from farms, and the costs of hiring AI scientists, data scientists, and engineers to build and train models can run into millions. However, these costs are coming down as companies provide AI models as a service, making it more accessible to farms.
Several UK schemes are designed to boost AI in agriculture. Adopt, a farmer-focused initiative funded by Defra and delivered by Innovate UK, will provide farmer-led, smaller-scale innovation grants for farmers, growers, and farm businesses to trial new technology and methods on their farms. BridgeAI, launched in 2023, creates a £100m fund to drive AI innovation and encourage competitiveness in the UK, with a focus on agriculture among other sectors. The Farming Innovation Programme, also overseen by Defra and Innovate UK, makes funds available to farmers, growers, and foresters who want to develop and use new, innovative methods and technologies, including AI.
As AI continues to evolve, its potential to transform agriculture is immense. From detecting diseases early to optimising resource use and improving yield quality, AI is set to revolutionise the way we farm. However, for this to happen, there needs to be greater collaboration between tech providers, academics, and farmers, and the costs of adopting AI need to come down. With the right support and investment, AI could help farmers make smarter, data-driven decisions, increase profitability and sustainability, and meet the growing demand for food in a changing climate.
