Artificial Intelligence in Agriculture and Industry
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| Format: | Recurso digital |
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2026
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| _version_ | 1866901730233417728 |
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| author | K., Sangeetha Mudakappa |
| author_facet | K., Sangeetha Mudakappa |
| contents | <p><strong><em><span>Abstract</span></em></strong></p> <p><em><span>Artificial Intelligence (AI) has emerged as a transformative technology influencing agriculture and industry, particularly in developing economies like India. This study examines the role, impact, and challenges of AI adoption in the Malnad region of Karnataka. The research is based on both primary data collected through surveys and interviews with farmers and industrial stakeholders, and secondary data from reports, journals, and policy documents. The study adopts descriptive and analytical methods to evaluate the effect of AI on productivity, efficiency, and economic development. The findings reveal that AI-based technologies such as precision farming, weather forecasting tools, pest detection systems, smart irrigation, automation, predictive maintenance, and intelligent supply chain management significantly enhance agricultural productivity and industrial efficiency. Farmers adopting AI experienced improved crop yields, better resource management, and reduced input costs. Similarly, industries integrating AI systems reported reduced machine downtime, improved quality control, and cost optimization. The results support the hypothesis that AI positively contributes to productivity growth and operational efficiency.However, the study also identifies key challenges including high initial investment costs, inadequate digital infrastructure, limited internet connectivity, shortage of technical skills, data privacy concerns, and resistance to technological change. These barriers restrict inclusive adoption and may widen the digital divide between large and small stakeholders. The study concludes that while AI holds immense potential for sustainable and inclusive economic development, effective policy support, infrastructure development, digital literacy, and capacity-building initiatives are essential for ensuring equitable integration of AI in agriculture and industry.</span></em></p> <p> </p> <p> </p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18742113 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Artificial Intelligence in Agriculture and Industry K., Sangeetha Mudakappa Key Words: Artificial Intelligence, Agriculture, Industry, Precision Farming, Automation, Productivity, Digital Infrastructure, Malnad Region, Economic Development. <p><strong><em><span>Abstract</span></em></strong></p> <p><em><span>Artificial Intelligence (AI) has emerged as a transformative technology influencing agriculture and industry, particularly in developing economies like India. This study examines the role, impact, and challenges of AI adoption in the Malnad region of Karnataka. The research is based on both primary data collected through surveys and interviews with farmers and industrial stakeholders, and secondary data from reports, journals, and policy documents. The study adopts descriptive and analytical methods to evaluate the effect of AI on productivity, efficiency, and economic development. The findings reveal that AI-based technologies such as precision farming, weather forecasting tools, pest detection systems, smart irrigation, automation, predictive maintenance, and intelligent supply chain management significantly enhance agricultural productivity and industrial efficiency. Farmers adopting AI experienced improved crop yields, better resource management, and reduced input costs. Similarly, industries integrating AI systems reported reduced machine downtime, improved quality control, and cost optimization. The results support the hypothesis that AI positively contributes to productivity growth and operational efficiency.However, the study also identifies key challenges including high initial investment costs, inadequate digital infrastructure, limited internet connectivity, shortage of technical skills, data privacy concerns, and resistance to technological change. These barriers restrict inclusive adoption and may widen the digital divide between large and small stakeholders. The study concludes that while AI holds immense potential for sustainable and inclusive economic development, effective policy support, infrastructure development, digital literacy, and capacity-building initiatives are essential for ensuring equitable integration of AI in agriculture and industry.</span></em></p> <p> </p> <p> </p> |
| title | Artificial Intelligence in Agriculture and Industry |
| topic | Key Words: Artificial Intelligence, Agriculture, Industry, Precision Farming, Automation, Productivity, Digital Infrastructure, Malnad Region, Economic Development. |
| url | https://doi.org/10.5281/zenodo.18742113 |