- Spending on AI in agriculture is expected to grow from $1.7 billion in 2023 to $4.7 billion in 2028, at a CAGR of 23.1%, according to Research and Markets.
- According to Allied Market Research, the global market size for IoT in agriculture was valued at $27.1 billion in 2021 and is projected to reach $84.5 billion by 2031.
These are just some of the statistics I found with a quick Google search for “Global Digital Agriculture Market”. We don't know if these numbers are accurate, but what is clear from these and many other studied statistics is that various sensors (IoT) and artificial intelligence (which can interpret this data into actionable recommendations) The AI) or machine learning (ML) systems required to change are large and constantly increasing.
Agriculture is literally one of the best industries for these technologies to grow because the process of growing crops and raising livestock involves a huge number of different variables. It’s easy to see where IoT monitoring, AI, and ML are already having an impact. However, with the rapid development and integration of AI into daily life through ChatGPT and other language model-based chatbots, it stands to reason that the scope and scale of AI in agriculture will rapidly expand. Below are the five ways AI will most likely continue to improve agriculture in his 2024.
1. Prioritize standardized data collection to improve AI technology.
Powering language models such as ChatGPT and other AI-based technologies requires large, standardized data sets. For example, with the proliferation of IoT devices, the number of variables required as input to AI applications continues to increase, so standardization of data collected from these devices and other data sources is important.
While most GIS software providers, such as ESRI, already offer their clients the option to use AI in their applications, they still need data to feed their models. Structured and standardized data is used in AI applications as the basis for prediction and decision-making, and can also be used to train AI models and improve their performance and accuracy. Continuous improvements in performance and accuracy are key to further increasing the adoption of AI in agriculture. As such, collecting standardized data will be his priority in 2024 (and beyond).
2. AI will be used to improve the data collection process
As mentioned earlier, collecting standardized data is important to powering AI applications. However, a significant portion of agricultural data is still collected manually (e.g. written) and has not yet been digitized, structured and standardized. AI can help transform non-digital and unstructured data into structured digital data that can be further leveraged rather than simply stored (in a filing cabinet). Between OCR (optical character recognition) software and AI models, the technology to make this happen already exists. Agritech companies are beginning to realize that it is not easy to convince farmers to use specific apps for data entry, and that it is better to use technology that allows farmers to create standardized data without changing their habits. I am. This will become clearer in the future. In 2024.
3. The pursuit of agricultural sustainability will be accelerated by AI
Sustainable agriculture revolves around protecting the environment, supporting and expanding natural resources, and making the best use of non-renewable resources. What this actually means is accuracy. The focus is on getting the input usage and farming methods right and producing the highest possible yield from the inputs used. So instead of just focusing on the highest yield per acre, focus on the highest yield per gallon of water, pound of nitrogen, or input that is the most limiting factor. To achieve the highest possible level of accuracy, and therefore sustainability, vast amounts of data need to be collected, processed, and turned into actionable insights. That's where AI comes in. ” takes that element out of the equation and provides data-driven insights. This trend will continue to grow in 2024.
4. AI will continue to improve the performance of agricultural equipment
From spraying to weed control and many other in-crop applications, AI is transforming the way the world farms. Powered by John Deere's AI, his See & Spray technology recognizes the difference between cultivated plants and weeds, so it can treat individual plants to reduce pesticide use. Stout's Smart Cultivator functions as an AI-powered in-row weeder, using mechanical actuation to remove weeds without chemicals or the need for large field crews. Masu. New AI-powered equipment is introduced every year, and 2024 will be no exception. This sector of the agricultural industry is rapidly revolutionizing.
5. Adoption of AI and ML-based robotics is here to stay
Robots have already become commonplace on many farms, and this trend will continue in 2024. The increasing sophistication of AI and ML models opens the door to further automation and robotics on farms, helping farmers combat farm labor shortages and lower operating costs. . Many crops are already being grown with AI and ML-powered robots involved in certain parts of the process, from self-driving tractors to fully automated swarms of drones tending fields. This will quickly become commonplace.
This article was originally published on WithLeaf.io.