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The Age of Artificial Intelligence (AI) is upon us – driven by unprecedented rates of innovation and adoption. Interest in AI has exploded as ChatGPT continues to capture the imaginations of the world.

This AI technology – able to perform a wide range of language tasks at accuracies not seen before – was touted as the next frontier of AI capabilities until being achieved by OpenAI’s GPT4 model. This step-change in the capability and accessibility of technology is the latest in a growing trend over the last century.

In the early 1900s, the innovation and adoption of advanced agronomic practices and technologies such as high yield seed varieties, chemical inputs and mechanization led to the green revolution. The rapid growth in the capabilities of AI over the past decade is creating a new revolution in how every industry and sector around the world operates and is structured, and agriculture is no exception.

Small Scale Producers are Central Players

This revolution occurs at a time when the demands of the 21st century require a step change in agri-food system capabilities.

The United Nations estimates that the global population will reach almost 10 billion people by 2050, with the majority living in LMICs in Africa and Asia. This anticipated population boom will require a 60-70% increase in global food production by 2050. The pressure on agri-food systems to produce more food to meet growing demand is compounded by the significant risks that climate change imposes on farming systems, particularly through changes in temperature and rainfall, extreme weather events and the increase in the number of pests.

Smallholder farmers and small scale producers (SSPs) in low and middle-income countries (LMICs), and their engagement with technology, are at the heart of whether and how this step change can occur. Although SSPs generate around one third of the world’s food, they provide the vast majority of food consumed in sub-Saharan Africa and Asia – the regions where the bulk of the world’s growing population will reside.

SSPs in LMICs are also among the poorest people in the world, with many living on less than $2 per day. Even if larger, commercially oriented farmers alone were able to meet rising demand for food by adopting smart technology solutions, this would serve to further disenfranchise SSPs and the rural communities that depend on them. Enhancing the ability of SSPs to become more productive and resilient is therefore crucial, not only to global food security but to the economic and social development of LMICs.

Artificial Intelligence Agri-Tech Opportunity

AI and automation technologies have potential to deliver this step change due to significant advancements in their capabilities and a reduction in their costs. Foundational digital applications in agriculture are already demonstrating impact among SSPs. These include:

• Advisory services delivered through ICT rather than in-person,
• Digital value chain payments creating an electronic record of income to better access financial services,
• E-commerce platforms to procure inputs and sell products, among many others.

Rapid advancements over the last decade in the capabilities of AI and digital automation technologies, with lowering barriers to entry and use, can build off this base to deliver greater value to SSPs at a much larger scale.

AI Can Help or Hurt in Multiple Ways

Despite their potential contribution, the impact that these advanced technologies among SSPs in LMICs will have is unclear. Whether they will help SSPs to improve their productivity and resilience to the extent that is required depends greatly on:

• Which value chain players the solutions are designed for;
• The accuracy and relevance of the solutions for SSPs;
• The accessibility and affordability of AI and automation and the underlying technologies;
• The commercial viability of the solution providers.

As with any new technologies, there are likely to be unintended consequences and risks that may limit this impact agri-food value chains are disrupted.
The full study aims to provide a compass to stakeholders navigating the complexities of these issues. As the application of these technologies among SSPs is still in the early stages, it is difficult to predict what their net impact will be, and almost impossible to do this quantitatively without significant investment in primary impact data collection.

Can AI Inclusively Advance Agri-food Systems? makes the case that AI and automation will be hugely transformative for small-scale producers in low and middle income countries. It lays out the landscape of use cases, underlying technologies and delivery models of AI and automation solutions in agri-food systems.

An excerpt from the Can AI Inclusively Advance Agri-food Systems? report by Genesis Analytics