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Dissertation 4.4

Artificial Intelligence for Agritech Startups: Interoperability | 2020–2026 Trends

31
Pages
IEEE
Style
~ 32–47 mins
Reading Time
Public Policy Education NLP
Abstract

This dissertation investigates “Artificial Intelligence for Agritech Startups: Interoperability | 2020–2026 Trends” using a event study methodology. Through a economic lens, the analysis integrates multi-source data to derive a practical decision framework for researchers and practitioners.

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Artificial Intelligence for Agritech Startups: Interoperability | 2020–2026 Trends

ABSTRACT
Artificial Intelligence for Agritech Startups: Interoperability | 2020–2026 Trends is unpacked across themes: benefits, change enablement, governance, and interoperability. Limitations and future research paths are noted.
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