An increasing population, political pressures, and severe weather events are all putting global food production at risk. The use of AI in agriculture could help farmers and agricultural decision makers to access more accurate data to improve productivity and sustainability. In this article, from our publication On Resilience, Professor Bruce Grieve explores the future of AI and smart technology to support sustainable farming.

• Our worldwide population is expected to increase from 8 billion to over 10 billion by 2100, increasing global demand for food.
• Electronic systems with embedded ‘smart technologies’, such as microprocessors and Graphic Processing Units (GPUs), offer an opportunity to revolutionise agriculture.
• The emergence of mass, low-cost, reliable, and accessible smart technology has the potential to be part of the solution to threats to global food supplies.

There is a clear and present threat to global food supplies from the perfect storm that is hitting international agriculture. Our worldwide population is expected to increase from 8 billion to over 10 billion by 2100. At the same time as global demand for food increases, an increasingly wealthy middle class – particularly in emerging economies – are driving global changes in dietary choices from vegetarian diets to the comparative luxury of more resource-intensive meat-based ones. Poultry and cattle-based diets are just 40% and 3% as efficient respectively on land usage as the equivalent vegetarian diet. But there are also political pressures, including cross-border migration, population shifts from rural to urban areas, the increase in average age in farming communities, and severe weather events due to climate change, all putting global food production at risk.

The increased tolerance of pests, pathogens and weeds to crop protection products, alongside the lack of new active ingredients coming from the agri-industry pipeline, pose a threat to global food supplies. As a result, there are strong political drivers to minimise chemical usage and environmental impact, matched to policy decision making. For example, since January 2014, the EU’s ‘Sustainable Use of Pesticides‘ directive has required non-chemical pest control methods to be prioritised wherever possible. All EU law pertaining to the regulation of plant protection products has been retained in UK law following Brexit.

Electronic systems with embedded ‘smart technologies’, such as microprocessors and Graphic Processing Units (GPUs), offer an opportunity to revolutionise agriculture. These technologies can rapidly reduce costs and dramatically increase efficiency.

Potential impact of AI on global agriculture

For arable agriculture, the adoption of these smart technologies is starting to gather speed in sectors where labour costs dominate, particularly for crops which traditionally need individuals tending to them, such as horticulture or soft fruit production. These sectors are early adopters of smart systems, in many cases, because of the sheer lack of labour needed for harvest. Already established machinery is being retrofitted to fulfil these duties, but new technologies are emerging.

For agriculture, AI is still in its infancy. The full scope of its impact and potential is yet to be determined. AI is often reported as automation, robotics, and big data, so the specific contribution of smart technology is, as of yet, unclear. Research indicates that potential profits for AI in agriculture are estimated to be as high as $120 billion per annum, broadly similar to the impact in media and entertainment. Deployment of AI in the agricultural sector faces unique challenges due to diverse factors, such as the climate, alongside economic and biological influences. However, AI could better account for variables compared to traditional technologies, for example with how fertilisers and pesticides interact with soil and location.

Futureproofing farmers

The use of AI in agriculture could help farmers and agricultural decision makers to access more accurate data to improve productivity and sustainability. This is particularly important for farming in the developing world where industry estimates suggest that AI tools can impact 70 million farmers by 2020 in India and add $9 billion to farmers’ incomes.

In the developing world, there are fewer barriers for the uptake of AI in agriculture. The capital costs associated with acquiring technology from countries like the UK are comparatively low, for example, when compared to costs associated with large-scale mechanised farming, traditionally central to farming in the developed world. The greater number of smallholder farmers in developing nations creates a significant mass market for smart technology, which could drive its adoption.

However, the value of AI and smart technology in agriculture often fails to focus on the value to the farmer. Innovation in agriculture tends to be driven by productivity and competitiveness in global markets. Although food production yields are shown to have increased, some farmers remain reluctant to adopt new technology. To overcome this, the rollout of new AI technology needs to ensure the motivations, sensibilities, priorities and mindset of farmers are appropriately integrated through dialogue and consultation.

AI-enabled smart technologies could deliver a paradigm change to current agricultural practices and influence positive progress. Smart technologies and robotics may help to identify diseases or infestations in crops, and enable selective crop protection actions, like spraying, to be formulated and applied earlier than is currently achievable.

An agricultural revolution

A growing number of sectors including manufacturing, housing, health, transportation and logistics have already adopted Industry 4.0 – known as the fourth industrial revolution – and there is potential for agriculture to follow. To support this, future modelling and research can establish where, how quickly, and how practically AI can impact the industry. Now policymakers must rise to the challenge of understanding that agriculture is not only a matter of productivity and profitability. Future policy should also focus on the impact agriculture can have on health through diet, labour, and on the environment, building resilience and protecting food-producing ecosystems well into the future.

For AI-enabled smart technologies to impact global agriculture, the agri-food sector must adopt a new mindset towards technology, and enact major changes to infrastructure to accommodate progress. Delivering that culture change means tackling interlinked challenges with policy interventions.

Policy recommendations

There is still a long way to go for AI technology to manage the speed and volume of data processing for mainstream crop productions. Policymakers should look at joined-up investment that supports emerging AI and agri-technologies, from research through to commercial production. This can establish the UK as a global leader in smart agriculture, creating a future export potential, as well as supporting the resilience of UK farming with home-grown technologies.

Partnerships between regulatory and accreditation bodies must be established from the outset to maximise the positive impact of smart technology and AI on agriculture. Commercially damaging delays to uptake can be prevented with a comprehensive national framework of regulation to support the adoption of this technology once it is ready for the commercial market – and this could also give the UK a global edge.

There is a need for a national and international standard for intelligent, autonomous agri-sensing and robotic systems. New agri-technology has the potential to operate safely 24/7 without human supervision. The standard would set out necessary guidelines; for example, requiring that the area where autonomous machinery operates is restricted to prevent human interference. This regulatory change could support mass uptake of the technology. Existing UK working groups exploring regulatory change are already lagging behind the pace of development in new technology. However, policymakers can apply the force of regulation to accelerate the process across the breadth of the agri-technology industry.

The emergence of mass, low-cost, reliable, and accessible smart technology has the potential to be part of the solution to threats to global food supplies. Policymakers and regulators have a significant role to play in bringing this technology to fruition. By implementing these recommendations, decision makers could enable investment in agri-technologies, increase efficiency in agriculture, and reap the benefits of positioning the UK as a global leader in AI and cutting-edge technology.