Video Credits: Vitibot (France), Abelio (France), Tevel (Israel), FarmBot (USA), Energid (USA), Naïo Technologies (France), Inaho, Inc. (Japan), Case UH (USA), Carbon Robotics (USA), Small Robot Company (UK), Burro (USA).

Welcome to GPAI AI in Agriculture and Livestock Farming portal

Artificial Intelligence has been creating value and optimisation of agricultural practices around the world, offering solutions that address the specific localized problems of crops and animal farming across all economic regions, from large exploitations of land to arable acres managed by small farming co-operatives. This portal offers access to AI-driven practices across continents and to the AI solutions providers that are helping farmers yield better from their crops and look after their livestock with sustainable and humane practices, all thanks to the incredible powers of artificial intelligence in minimizing efforts, optimizing practices by reducing errors and providing access to crucial data.

The agriculture sector deals with issues that affect humankind’s survival. A top priority is the optimization of natural resources such as water, and the preservation of arable land, which is crucial to sustainable practices. There is also undeniable evidence of the direct connection between the destiny of Nature and the animal kingdoms and our own survival. Agriculture today is not just about “feeding” the human race, but about managing Earth’s resources for an economic prosperity based on sustainable practices where artificial intelligence will help us achieve and deliver to the world.

Digital technologies and AI tools have transformed rural communities to gain better quality of life and become more prosperous. At government level, the AgriTech sector is seen as the path to enable science-based policies and the re-population with technology workers of rural areas suffering from negative net migration.

The GPAI AI in Agriculture portal showcases the two main challenges that affect agriculture in the 21st century:

(1)the need to standardise AI practices deployed within the sector;

(2)the need to improve current business models, respond to market competitive dynamics, and address consumer expectations in the human food supply.

How AI and Technology have created the agriculture of the future
The success of precision agriculture and robotics in the Netherlands, Japan and Israel has created a strong and future-ready agricultural ecosystem that is challenging the agricultural exports of traditional agricultural exporters while ensuring that farming becomes a real livery for agricultural communities.
Netherlands
Netherlands
Japan
Japan
Israel
Israel
Addressing the big challenges in agriculture
Technology and AI have come to solve many of the ever emerging problems of procuring food for the world. Farming communities are still addressing old challenges such as land erosion and water resources while dealing with new ones such as diminishing labour resources, increased competitive markets, better livestock welfare and demand for more sustainable practices.
Arable
Arable land erosion
Water resources
Water resources
Weeding
Weeding
Pesto
Pest control
Crop monitoring
Crop monitoring
Carbon trading
Carbon trading
Harvesting for higher yields
Harvesting for higher yields
Livestock welfare
Livestock welfare
Adopting AI-driven Technologies in the agriculture commodity countries
Agricultural commodities such as grains, oilseeds, livestock, meat, dairy, cotton, sugar, coffee and cocoa and their demand or financial hedge against them will define much of and how fast AI-driven technologies will be adopted amongst the nations that import and export them. When G7 and BRIC nations are the de facto granaries of the world, agriculture becomes a highly competitive attribute. If technology and AI-driven solutions can play a role in innovating agriculture, the transformative changes will have to centre around how these markets adapt to the nuances of AI, that uses robots instead of cheap manual labour, and leverages from sensor-based equipment that is costly, pushing greenhouse controlled agriculture as the future most high-yielding environment for crops and pressures farmers to abandon cheap methods that worked in the 20th century, such as chemical fertilizers, in exchange for sustainable approaches.

Price fluctuations in commodity markets can create uncertainty for farmers who are beginning to realise that the use of predictive analytics and precision agriculture help them mitigate risks by optimizing yields and reducing costs. Global demand for specific commodities can drive technological innovation in crops that become favoured by consumers for a variety of reasons beyond eating habits, and growingly associated with choices around their organic or sustainable provenance. Efficient supply chains in a world that today trades agricultural produce of all kinds across vast geographies to respond to out of season food demands are positioning blockchain architectures, logistical modelling and IoT devices as technologies that can improve traceability and reduce waste. As climate change impacts agricultural production, the growing need to bring technologies in support of farmers to deal with extreme weather conditions and reduce their environmental impact is no longer an action that should be contained in government funded agricultural labs, but put in the hands and within the economic reach of farming communities.
USA
United States
Canada
Canada
Brazil
Brazil
India
India
Australia
Australia