Shaping the Deep Tech Revolution in Agriculture 2025

Addressing the pressures on agriculture necessitates the convergence of multiple technological domains, often including a complex web of interconnections. Figure 16 identifies a few breakthrough agri deep-tech use cases with the objective of illustrating the complexity of convergences. Complex convergences that underlie agri deep-tech use cases FIGURE 16 Source: World Economic Forum analysis Deep-tech use cases ar e power ed by a complex convergence of technology domains. The map above is illustrative, as ther e are many potential combinations and each new convergence can unlock a unique value pr oposition, even within the same use case.ChallengesTo addr ess challenges, use cases mustUse cases Tech domains Shifting workfor ce dynamics resulting in lower human capital for agricultur e— Supplement labour with automation — Increase r esour ce-use efficiencyTask-specific swarm roboticsGenerative AI Computer vision Edge IoT Satellite-enabled remote sensing Robotics (including dr ones) CRISPR NanotechnologyAgentic AI systems Precision irrigation/ fertilization Climate-r esilient crop varieties Contr olled envir onment cultivation Agricultural digital twins Macr o crop planning Supply chain risk dashboar dsOthers (natural language processing, blockchain, machine lear ning, etc.)Nano inputsCarbon monitoring, reporting and verification (MRV) systems— Predict climate risks — Enable r esilience in agricultural pr oduction — Improve r esour ce-use efficiency — Regenerate natural resour ces — Predict food demand — Improve r esour ce-use efficiency — Increase pr oductivity — Build transpar ent supply chains — Build transpar ent supply chains — Optimize pr oduction locallyClimate change and intensifying weather extr emes Natural r esour ce degradation (soil and water) Rising food demand and demand–supply mismatch Geopolitical instability and friction Shaping the Deep-Tech Revolution in Agriculture 25