Mehta et al. (2026) Navigating the agricultural landscape: Artificial intelligence and industry 5.0 insights

Identification

• Journal: Elsevier eBooks
• Year: 2026
• Date: 2026-01-01
• Authors: Pradnya Mehta, Sanved Narwadkar
• DOI: 10.1016/b978-0-443-32878-7.00011-0

Research Groups

• Department of Computer Science Engineering- Artificial Intelligence, Vishwakarma Institute of Technology, Pune, Maharashtra, India
• Vishwakarma Institute of Information Technology, Pune, Maharashtra, India

Short Summary

This chapter reviews the transformative role of Artificial Intelligence in agriculture, highlighting its applications in enhancing productivity, environmental sustainability, and overall efficiency through data-driven insights and automation.

Objective

• To explore and synthesize the diverse applications and transformative potential of Artificial Intelligence in modern agriculture, focusing on its impact on productivity, environmental sustainability, and efficiency.

Study Configuration

• Spatial Scale: Global (conceptual review of applications)
• Temporal Scale: Current and prospective (conceptual review of trends and future potential)

Methodology and Data

• Models used: Not applicable (conceptual review discussing AI applications)
• Data sources: Existing scientific literature and conceptual analysis

Main Results

• Artificial Intelligence (AI) is revolutionizing agriculture by enabling data-driven decision-making, improving resource management, and enhancing overall efficiency.
• Key applications include precision farming, where AI combined with remote sensing customizes strategies for individual crops, reducing waste of resources like herbicides, fertilizers, and water, and increasing yields.
• AI significantly contributes to livestock welfare through sensor improvements and monitoring, ensuring ethical and sustainable animal agriculture.
• Autonomous farming, utilizing AI-powered vehicles and robots for tasks such as planting, harvesting, and weeding, leads to lower labor expenses, improved output, and continuous operation.
• Overall, AI empowers farmers with information-driven knowledge, shifting agricultural practices from intuition-based to data-driven, thereby improving productivity, environmental sustainability, and competitiveness.

Contributions

• Provides a comprehensive synthesis of the wide range of applications and transformative potential of AI in the agricultural sector.
• Highlights specific areas where AI significantly impacts, such as precision farming, livestock welfare, and autonomous farming.
• Articulates how AI contributes to making agriculture more productive, environmentally sustainable, and efficient by facilitating data-driven decision-making.

Funding

• Not specified in the provided text.

Citation

@article{Mehta2026Navigating,
  author = {Mehta, Pradnya and Narwadkar, Sanved},
  title = {Navigating the agricultural landscape: Artificial intelligence and industry 5.0 insights},
  journal = {Elsevier eBooks},
  year = {2026},
  doi = {10.1016/b978-0-443-32878-7.00011-0},
  url = {https://doi.org/10.1016/b978-0-443-32878-7.00011-0}
}