In this session we will look at several examples of use of AI and predictive modeling applied to the natural world – and enabling trust and collaboration within the value chain that supports our food industry. We’ll look at how TheoryMesh is enabling data analysis from crop farming through food processing, and on to consumers, and at other use cases of the use of AI in anticipating climate change for woodland creation and conservation, and soil protection, leveraging LIDAR and other public data.

The end goal is to find the balance between current insights and future trends – both social and natural – to increase and preserve quality and yields, drive circularity and better serve our changing needs. Soils and forests evolve slowly, which is in itself a challenge when it comes to future predictions, as we are building on data lacking long enough time series. However, the analysis can allow short term decision making in terms of sourcing, use and optimization of resources, land management and stakeholder engagement.

The impact on future generations as well as on short term business cases is well worth the work.