Beyond general policies, legislation and investments, policymakers need to target the agriculture sector to support automation more directly. Governments can use a range of policies, legislation, investments and other interventions to target the sector, especially small-scale producers, to support adoption of automation technologies. These include land tenure policies, investments in capacity building, legislation on quality assurance, applied research, and targeted finance. The specific priority ranking of such actions largely depends on context, including the overall development level of a country or region and the agroclimatic and topographic characteristics of agriculture. National strategies for agricultural automation are needed to guide more specific actions, policies and investments. This is essential in areas where automation is either lacking or in the early stages. Such national strategies should be based on surveys and field studies that take account of the experiences of researchers, agricultural producers, service providers and manufacturers. The basis for producers adopting specific machinery and digital equipment must be their conditions and needs, which vary within and between countries. In Africa, where agricultural automation is still limited, governments have come together to accelerate adoption, recognizing the advantages of the digital revolution (see Box 27).
BOX 27National strategies for a stronger adoption of digital tools in African agriculture
The African Union (AU) and several African governments are accelerating efforts towards an enabling environment for the effective use of digital tools to transform agrifood systems. A key recent step is the AU Digital Agriculture Strategy, under the leadership of the African Union Commission Department of Rural Economy and Agriculture. This is a follow-up to the Digital Transformation Strategy for Africa (2020-2030), which includes agriculture.16 The Digital Agriculture Strategy, yet to be officially adopted, encourages governments to better leverage the power of digital innovations to boost the performance, inclusiveness and sustainability of agriculture and other rural sectors, calling for digital agriculture strategies and the use of digitalization to strengthen mechanization services.
In addition, Smart Africa, an intergovernmental agency created by African heads of state and governments, has developed the AgriTech Blueprint for Africa,17 while some years earlier, FAO and the International Telecommunication Union proposed to governments a guide for their digital agriculture strategies.18 Building on these various efforts, many agriculture ministries in Africa are designing new policies to better seize the opportunities offered by digitalization.
The following sections present possible policies, investments and legislation that governments can focus on, based on the conditions and needs of producers, to harness the potential of automation technologies and establish a business case for the widest possible range of producers.
Improving access to automation technologies, especially for small-scale producers
As previously stated, the functioning of credit markets has important implications for access to finance to adopt costly technologies such as automation. Farmers can use their savings to purchase machinery, but when savings are limited, they resort to credit. Governments can influence this process through credit policies that directly target agricultural automation. Investment loans are the most common solution for financing automation, but they can be undermined by lack of security or have high costs. Contract-based securities, loan guarantee schemes, joint liability groups, and leasing are all potential options. With leasing, various incentives may be applied, for example, matching grants or providing “smart” subsidies (i.e. subsidies that do not distort markets).26 Such tools are used in some Asian countries to enhance farmers’ access to credit.13 Other options for moving forwards include value chain finance, cooperative credit (as seen in India27), and savings and insurance products, especially for larger equipment.26 In addition to producers and service providers, local manufacturers and maintenance and repair shops may also need loans.5, 22
Evidence from the 27 case studies discussed in Chapter 3 shows that when agricultural producers – especially small-scale farmers – lack financial capacity, service providers can seek alternative business models to make their solutions profitable. In some cases, services are tied to credit, insurance or farming contracts, such as contract farming agreements that guarantee offtake and a fixed price for raw materials. This helps reduce production risks, improves investment capacity, and leads to higher yields and better quality outputs. In the absence of contract farming or supply chain legislation that improves small-scale producers’ contractual capacity, such business models may create technological lock-ins (i.e. requiring farmers to use specific services), or unwanted dependencies and power asymmetries, with unintended socioeconomic consequences. These solutions may also coerce farmers, buyers and service providers to follow certain behaviour patterns and agronomic practices desired by more powerful market actors. At the same time, these solutions embed farmers in a closed, proprietary system.25 More organized, formal services help reduce production risks, but can also restrict a farmer’s options. Legislation is needed to protect small-scale producers from falling into coercive contracts.
Another policy area where governments can facilitate access to finance is land tenure. Insecure tenure creates disincentives for agricultural producers to invest in agricultural technologies – and in their farms generally – because it causes great uncertainty about whether farmers can ever reap the benefits of their investments. It restricts access to credit, as they cannot use land titles as collateral. This is particularly a problem when the investment is costly and takes several years to repay, as in the case of motorized machinery. Better land tenure security facilitates credit access, especially for small-scale producers, and incentivizes machinery investment. In Myanmar, for example, land tenure reforms have significantly increased the likelihood of being granted a bank loan to purchase agricultural machines.23 Farmers can use this credit to purchase inputs such as fertilizers and improved seeds; the synergies between these inputs and use of machinery and digital equipment contribute to raising productivity and resource-use efficiency. Credit for automation should be led by market actors and guided by commercial viability. Public efforts to directly finance agricultural automation have often come up against considerable governance challenges.26, 28
Trade policies can play a role in accessing agricultural automation technologies. The supply of agricultural automation can be affected by high import duties, lengthy customs procedures and non-tariff barriers to trade, such as sanitary measures. In Asia, the removal of import restrictions greatly contributed to mechanization,13 while in Africa, machinery is now exempt from import duties in many countries, although some remain in place.12, 13 In other countries where machinery is mostly exempt, spare parts often attract high duties, undermining the sustainability of mechanization. Reduction of duties on machinery, digital equipment and spare parts, together with improvement of customs procedures, can help lower transaction costs of automation technologies and spur uptake. Governments should give priority to duty and tax exemptions for machinery and equipment that best fit local conditions and address the main challenges relative to national objectives for improved productivity, enhanced sustainability and stronger resilience.
Building knowledge and skills
Manufacturers, owners, operators and machinery technicians, as well as agricultural producers, all need to acquire knowledge and skills on how to create, manage, operate, maintain and repair agricultural automation equipment. Lack of this specific expertise can undermine the profitability and sustainability of automation technologies; despite this, they are often poorly promoted.5 A case in point is Ghana, where 86 percent of tractors have frequent and long-lasting breakdowns due to poor maintenance and a shortage of skilled operators and mechanics.19 Public efforts to build knowledge and skills have played a key role throughout the history of mechanization across the world.20 Vocational training centres, combining applied and theoretical training, may be particularly adapted to provide the necessary knowledge and skills. Training is also essential for human supervisors of digital automation. In Australia, the code of practice specifically prepared for users of machines with autonomous functions places great emphasis on how to alert supervisors and how they should report incidents.21
Digital illiteracy, as well as lack of skills to supervise, maintain and repair automation technologies, is another major barrier to adoption of digital automation worldwide, especially for small-scale producers (see Chapter 3). Human capital development is essential and a capacity-building agenda is required, including investments to scale digital skills. This agenda should not only target agricultural producers, but also other actors in the agricultural value chains, covering all stages, from input and service provision to further downstream (e.g. processing and trading). Such an agenda is essential to support the transition of workers from low- to high-skilled jobs, and it is particularly important for youth – often perceived as key drivers of the transformation of family farming towards agricultural automation, as they tend to embrace it more than their parents. Government policies and investments should therefore target young rural workers.
Investing in applied research and development
Private research and development largely drive automation technologies. Governments can provide general support through relevant institutions and can conduct or fund research on technical, agronomic and economic solutions for locally adapted and sustainable automation. The research agenda should also cover studies on the impact of specific precision agriculture solutions for profitability, environmental sustainability (including carbon, water and energy footprints), labour safety, and inclusion of women, youth and other vulnerable groups. Another relevant area concerns different types of farming in protected and controlled environments (e.g. vertical agriculture or greenhouses), not always perceived positively by consumers and policymakers. It is also essential to develop and validate specific agronomic models for a better understanding of crop responses to specific precision agriculture technologies, such as variable rate technology (VRT). Governments can support national research and innovation systems – private or public – to adapt and upgrade existing machinery and digital equipment, tailoring them to the needs of producers as farming systems evolve.
Research is needed on the use of big agricultural data and analytics as a public good capable of offering free advisory services to small-scale producers. Applied research is also recommended to explore the adaption of automated solutions to different regions, countries, agroecological conditions, production orientations and farm types (see Box 28). Ideas that have worked in one place may not be suitable elsewhere. To encourage the development of relevant autonomous agriculture, research and development frameworks need to bring innovators together with farmers to design and scale solutions. One example from the United Kingdom is a scheme by Innovate UK called Science and Technology into Practice. The programme is publicly funded and requires innovators to work with end users throughout the project, hold demonstration events, and gather and act on feedback from farmers.
BOX 28Adapting digital automation to various contexts: evidence from 27 case studies
The 27 case studies in this report illustrate how to adapt digital automation to local needs across production systems, countries and farm types. For example, in crop production there is evidence of low-income countries developing small automated machinery – for example, tea leaf pickers in Uganda, and automated cotton harvesting machines (a difficult operation to automate, as mentioned in Chapter 3) in India and Western Africa. These technologies are currently available to medium- and large-scale producers, and their use is expected to become more widespread, managed by producer organizations through hiring centres.
In precision livestock farming, the business and service models for milking robots provide valuable lessons in terms of application of technologies to different farm types. While milking robots are mainly adopted by medium- to large-scale farms in high-income countries, there are other technologies adapted to small-scale indoor farms, as well as pasture-based free cow movement installations in middle-income countries.
Finally, with regard to agriculture in controlled environments, greenhouses are increasingly common in high- and middle-income countries where there is a certain level of automation (e.g. for climate control). These solutions are appearing in countries across the globe, for example, Chile, Mexico and Saudi Arabia. Controlled agriculture, and in particular greenhouses, represent an important opportunity for robotics with artificial intelligence (AI).
SOURCE: Ceccarelli et al., 2022.25
A final research area is that of the emerging power dynamics in low- and middle-income countries as a result of increasing reliance on digitalization and automation technologies. It is necessary to understand the commercial interests of big players in technology development and service provision, and the potential impacts on small-scale producers, particularly in terms of concentration of power, redistribution of land and wealth, and loss or creation of knowledge and skills, as well as the implications for labour and employment.
Quality assurance and developing safety standards
A lack of quality assurance in the form of testing and certification of machinery, equipment and spare parts can undermine the uptake of various agricultural automation technologies as it increases the uncertainty and risks associated with their purchase.13 For example, in Ghana a locally produced maize sheller that can be attached to a tractor costs less than an imported one, but the quality is difficult to assess prior to purchase due to a lack of standards or certification schemes. Many farmers thus opt for foreign brands.5 Testing may not actually be feasible for small- and medium-scale manufacturers without assembly lines; what is more, they lack incentive if local markets do not require formal certification. However, public, market and third sector organizations can organize testing to effectively mitigate information asymmetries without substantially raising machinery costs. The presence of a public validation service that appraises the cost-efficiency, effectiveness and user-friendliness of technologies could have a positive impact on uptake. Likewise, strengthening the institutions that set standards can support the manufacturing and trade of automation technologies.22
Policymakers need to ensure safe agricultural automation through a balanced package of laws and regulations. Such rules should cover all aspects, whether positive or negative, and be based on an inclusive consultation, interacting with all stakeholders both before and after application of the regulations. In the United Kingdom, for example, the Government has severely restricted the use of drones in input application on safety grounds, despite the significant benefits for the environment and human safety. The legislation also requires 100 percent on-site human supervision of autonomous machines to ensure they do not cause accidents. Analysis found that such legislation wipes out the economic benefits of autonomous equipment for small- and medium-scale producers and increases economies of scale, making them profitable only for larger farms.24 When policymaking is transparent and inclusive, such findings may lead to a revision of policy.
To guarantee safety, governments should adopt transparent frameworks. Essential elements are inspections to verify user compliance, standards to provide guidance, and mechanisms to enable self-regulation through, for example, assurance schemes (voluntary schemes that establish production standards covering food safety, animal welfare and environmental protection). Standards could be legally binding or not. In Australia, a code of practice has been adopted to guide the use of autonomous machines in agriculture.21 It gives growers the confidence to adopt autonomous solutions, while giving manufacturers the confidence to scale them. It aims to standardize the approach to machinery automation. The code of practice covers several areas, including general hazard controls and emergency preparedness, vehicle transport between fields, maintenance and repair requirements, emergency management, and legislative provisions and standards. Similar work is being undertaken in the United Kingdom for robots including those used in agriculture.9
Harnessing the potential of low-cost agricultural automation technologies
When the business case for investing in larger machinery is lacking due to financial constraints, or because the machinery is not suited to local topographic conditions (e.g. hilly terrain) or farm sizes (e.g. very small, fragmented plots), small machinery can provide great benefits to crop producers, especially those operating small plots in relatively marginal areas. Such machinery and equipment include two-wheel tractors or power tillers, drum seeders, rotary dibbers and power weeders.29 There is evidence of the business case for adopting small machinery (see Box 17). Indeed, these simple technologies can lead to a significant reduction in drudgery, as well as savings in time and inputs, leading to improved productivity and enhanced resilience through timely performance of operations. They are also more environmentally friendly as they require little or no fossil fuel to operate, and many of them are suitable for agroecological approaches, such as rice–fish systems and alternate wetting and drying (where farmers apply water-saving technologies to reduce water consumption in rice fields without affecting yield). In some contexts, they allow for greater inclusion of women, who may be excluded from mechanization due to cultural norms and traditions.29, 30
Technologies such as IVR, USSD and SMS, in addition to call centres, are available in most low- and middle-income countries and are therefore the most common – if not the only – solutions for small-scale producers, especially in sub-Saharan Africa. They give access to bundled services, since they can reach farmers (regardless of the devices they use and their digital skills), are low cost and require little maintenance. Bundled services often combine various subservices (e.g. provision of information on markets, climate and weather, and real-time farm monitoring data), and also link actors. These technologies have the potential to limit digital divides thanks to their high accessibility. They are less sensitive to infrastructural failures as they require less energy and simpler data infrastructure compared with advanced data-driven technologies, and generate the highest return on investment. It is important, however, that the solutions offered not only meet local needs but also provide reliable advice.25
