Shaping the Deep Tech Revolution in Agriculture 2025
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Deep tech in agriculture has five main characteristics.2.1 Understanding deep tech in agriculture
Five characteristics of deep tech – and their agricultural relevance TABLE 1
Characteristics Relevance for the agriculture sector
1
Science and engineering-backed
innovationAgri deep tech delivers use cases rooted in cutting-edge science and engineering, such as AI,
remote sensing and robotics, addressing complex agricultural challenges with precision.
2
Use cases rely on technology
convergenceAgri deep-tech use cases bring together multiple technology domains, delivering impact beyond
what can be delivered by a single domain in isolation.
3
Significantly capital-intensive, with
uncertain time horizons for maturity Agri deep-tech use cases require years of research and development (R&D) and there is
uncertainty about the time horizons for maturity. Before deployment, these technologies require
testing across multiple seasons/locations. Their development demands high upfront investment,
creating barriers to entry.
4
High risksAgri deep-tech use cases are high-risk investments during the development phase. Investors
therefore need to underwrite a complex technology risk. Even after development, using agri
deep tech can carry risks that may be social (e.g. displacement of farm workers), ethical (e.g.
misuse of farmer data and biases), environmental (e.g. high associated emissions) or regulatory
(e.g. challenges with commercialization due to delayed approvals). Further, the margin for error
with agri deep-tech use cases must be close to zero before deployment, because failures in
tech can directly affect farmer livelihoods and food security.
5
Able to solve complex challenges in the
agricultural sector Agri deep-tech use cases are purposely built to address systemic challenges. Besides being
effective at the farm level, most use cases have the capacity to alter the economics of an entire
supply chain, shifting food production towards systemic sustainability, inclusivity and efficiency.
Shaping the Deep-Tech Revolution in Agriculture
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