Artificial intelligence and new business models in agriculture: a structured literature review and future research agenda

Abstract

PurposeArtificial Intelligence (AI) is a growing technology impacting several business fields. The agricultural sector is facing several challenges, which may be supported by the use of such a new advanced technology. The aim of the paper is to map the state-of-the-art of AI applications in agriculture, their advantages, barriers, implications and the ability to lead to new business models, depicting a future research agenda.Design/methodology/approachA structured literature review has been conducted, and 37 contributions have been analyzed and coded using a detailed research framework.FindingsFindings underline the multiple uses and advantages of AI in agriculture and the potential impacts for farmers and entrepreneurs, even from a sustainability perspective. Several applications and algorithms are being developed and tested, but many barriers arise, starting from the lack of understanding by farmers and the need for global investments. A collaboration between scholars and practitioners is advocated to share best practices and lead to practical solutions and policies. The promising topic of new business models is still under-investigated and deserves more attention from scholars and practitioners.Originality/valueThe paper reports the state-of-the-art of AI in agriculture and its impact on the development of new business models. Several new research avenues have been identified.

Análisis de los sistemas de costos aplicados a las empresas agrícolas: un estudio de revisión sistemática

“…Arthur Young notó la ausencia de registros contables de costos, que permitirían a los agricultores determinar el costo de los cultivos, los animales y los diferentes modos de cultivo. Sin embargo, en el siglo XVIII, la práctica de la contabilidad agrícola estaba en una etapa incipiente (Cavazza et al, 2023).…”

“…Por tanto, la meticulosa recopilación y análisis de datos que demanda el sistema puede sobrepasar rápidamente la capacidad administrativa de dicho sector cuyas operaciones están intrínsecamente complicadas por la estacionalidad ambiental. Tal punto es corroborado por Cavazza et al (2023), quien subraya que las exigencias de dicha herramienta en términos de procesamiento de información pueden resultar abrumadoras para las empresas que ya enfrentan la incertidumbre de los ciclos naturales y de los mercados fluctuantes.…”

Precision Beekeeping Systems: State of the Art, Pros and Cons, and Their Application as Tools for Advancing the Beekeeping Sector

“…A remote monitoring system for their hives would be highly advantageous. However, these beekeepers frequently relocate their hives to remote or wooded areas, where both power supply limitations and signal strength can hinder data transmission [ 25 , 112 , 113 ]. Another critical issue is the beekeeper’s preparedness for the proficient use of these technological tools.…”

Business Intelligence Transformation Through Ai and Data Analytics

“…This is consistent with the observations in the current study, where AI-driven analytics have been identified as crucial for understanding consumer behavior and predicting market trends in real-time, thereby offering businesses a competitive edge. Cavazza et al (2023) explored AI's role in agriculture, presenting new business models that leverage AI for increased efficiency and sustainability. This research complements the findings of the present study by demonstrating AI's versatility and its capacity to drive innovation across different sectors, including agriculture.…”

“…In agriculture, the practical applications of AI range from crop monitoring to predictive analysis of weather patterns, as discussed by Cavazza et al (2023). This not only improves crop yields but also contributes to sustainable farming practices, reflecting AI's potential to address global challenges such as food security and environmental sustainability.…”