More agricultural workers were expanding their budgets into AI than robotics. Credit: Suwin66/shutterstock

An AgTech Findings survey conducted by crop management company The Yield Technology Solutions has found that there has been a staggering rise in demand for AI and data analysis solutions within the agriculture industry. 

Out of over 800 US agricultural workers surveyed, more respondents felt as though AI was a greater investment priority than robotics. 

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Around 90% of respondents answered that they felt as though AI and data analytics would drastically disrupt their job in the agriculture industry within the next five years. In contrast only 54% of workers stated that they planned to invest in on-farm robotics in the next year. 

This could be because over 90% of the survey’s respondents answered that they found it hard to improve their workflows based on data they currently have at their disposal.  

AI tools such as large language models (LLMs) can summarise large amounts of data and generate responses to advise its user based on that data.  

Within the next year, around 60% of agricultural businesses surveyed stated that they planned to increase their AgTech budgets, with 90% of respondents expressing a need for data apps and platforms. 

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An urgency for data collection and analysis may stem from an increasingly unpredictable climate amidst global warming. 

Climate change remains a top concern for agricultural workers, with over 80% of respondents naming it as their top business worry. 

In its thematic intelligence report into ESG 2.0, research company GlobalData warns that companies unprepared for climate change face higher costs and less sales. 

The agriculture industry faces a unique challenge. 

Whilst most industries can focus on reducing their carbon footprint and investing in clean technologies, agriculture has a huge dependence on weather and climate. 

Using AI to better understand data could help the industry predict weather patterns and events more accurately, as well as give them a better understanding of their own impact on the landscape.