Dr Abdul Rahman Hamdan
rahman@might.org.my
Malaysia’s agriculture sector, a long-standing traditional sector that has continuously contributed significantly to the livelihoods of Malaysian farmers for hundreds of years, is on the brink of a significant technological transformation over the next decade. As digital infrastructure continues to improve and expand across the country, the agricultural sector in Malaysia is expected to undergo a substantial increase in productivity and efficiency. The integration of digitalisation and key technology such as artificial intelligence (AI) will prove to be one of the most powerful and transformative tools that has ever been implemented in the sector. The AI technology would undoubtedly revolutionise the sector, making it more impactful and improving the livelihoods and incomes of farmers in the country. With increased government commitment to AI, supported by close public-private partnerships, an emerging AI ecosystem for agriculture is expected to develop in Malaysia, as the country lays the groundwork for a smart agriculture revolution in the near future. Malaysia’s agricultural Gross Domestic Product (GDP) rose from 1.7% to 7.2% in the second quarter of 2024, reflecting the sector’s momentum in digital transformation (Arc-group, 2024; World Bank, 2024). The economic impact of AI in agriculture is undeniably significant. In Malaysia, AI is projected to contribute up to USD 115 billion to the country’s GDP by 2030 (Bernama, 2025; Chambers & Partners, 2025).
The agriculture sector remains a vital pillar of our national economy and rural livelihoods. We have witnessed encouraging progress in integrating AI to boost productivity, sustainability and market competitiveness. From the results of a focus group discussion with Malaysia’s AI stakeholders in Agriculture, Figure 1 below illustrates AI’s strengths and opportunities.
Global Overview
On the regional front, Thailand has been notably active in integrating AI into its agricultural sector. Through its National AI Strategy roadmap, Thailand is promoting innovation in its digital farming practices and processes. Several notable Thailand agritech startups, such as Ricult, offer AI-based farm analytics which leverage satellite imagery, agronomic models and weather data to support Thai farmers in decision-making and risk reduction (Sojitz, 2021), and another startup, Easyrice provides AI-powered rice quality inspection that reduces inspection time from 15-20 minutes to just 3-5 minutes per sample, cutting cost and time by up 30 percent while covering 25 Thai rice quality standards (Royal Thai Embassy, Washington, D.C., 2023).
These innovative efforts have propelled the Thai AI-in-agriculture market to USD 80.33 million in 2023, with projections to reach USD 113.96 million by 2029 (ResearchAndMarkets.com, 2025).
Another country worth mentioning in terms of implementing AI in its agricultural sector is Australia. Australia has emerged as a global leader in applying AI to solve complex agricultural and environmental challenges. The Sensing+ system developed by The Yield is now deployed in berry farms to optimise microclimate predictions and yield forecasting. Companies like FarmLab are also integrating satellite imagery and AI to manage soil carbon levels and facilitate carbon credit markets (FarmLab, n.d). All these AI innovations could contribute up to AUD 315 billion to Australia’s GDP by 2030, highlighting their strategic economic importance (Australian Government PM&C, 2023; CSIRO Data61, 2021)
Malaysia AI Use Case Studies
The implementation of AI in the nation’s agriculture aligns with the strategic goals of the Malaysia National AI Roadmap (2021-2025), which prioritises agriculture as a key focus area for AI development and adoption. All the strategic initiatives and figures emphasise the value of investing in AI-driven agricultural innovation, not only as a means of economic growth but also as a pathway toward environmental sustainability, food security and rural development. Figure 2 below shows some examples of Malaysia’s AI used case studies in the agricultural sector. These case studies highlight the importance of strategic partnerships in AI, demonstrating how collaboration can lead to significant advancements the agricultural sector
Conclusion
Malaysia can continue to enhance its AI capabilities through stronger collaboration among the government, academia, industry and farmers. Furthermore, the growth of the Agri-tech ecosystem fosters job creation in rural areas, spurs entrepreneurship, and contributes to Malaysia’s broader digital economy. By reducing crop losses and improving yield forecasting, AI also strengthens Malaysia’s food supply chain resilience and supports national GDP growth in the agriculture sector. By fostering inclusive innovation and scaling AI applications that address real-world agricultural needs, we can shape a smarter, greener and more resilient future for agriculture in Malaysia through collaborative partnerships with other countries, such as the UK government, industries and key stakeholders.
Funding Statement
This work was supported by the United Kingdom Foreign, Commonwealth and Development Office (FCDO) and the British High Commission of Kuala Lumpur. The activities were conducted under the auspices of the Malaysian Industry-Government Group for High Technology (MIGHT), in partnership with Universiti Teknologi MARA (UiTM), Malaysia, and Leeds Beckett University, United Kingdom.
References
1. MRANTI. (2022, March 5). My say: Growing through innovation in agriculture. https://mranti.my/happenings/blog/my-say-growing-through-innovation-in-agriculture
2. MRANTI. (2022, March 26). How Malaysia’s AI Park is driving innovations in agriculture and health. https://mranti.my/happenings/news/how-malaysias-ai-park-is-driving-innovations-in-agriculture-and-health
3. MRANTI. (2023, December 26). Pioneering sustainable agriculture with probiotic innovation. https://mranti.my/happenings/news/pioneering-sustainable-agriculture-with-probiotic-innovation
4. Arc Group. (2024, September 9). Malaysia Economic Update Report, Q2 2024 [Report]. ARC Group. https://arc-group.com/report/malaysia-economic-update-report-q2-2024/
5. World Bank. (2024, October). Malaysia Economic Monitor: Farming the Future—Harvesting Malaysia’s agricultural resilience through digital technologies. Malaysia Economic Monitor. Washington, DC: World Bank. https://documents1.worldbank.org/curated/en/099100924041013169/pdf/P506961%E2%80%91791497d1%E2%80%915a2e%E2%80%914455%E2%80%918d2e%E2%80%9155d032837a3f.pdf
6. Sidhu, S. S., Dhillon, M. K., & Bernard, S. A. M. (2025, May 22). Artificial Intelligence 2025 – Malaysia: Trends and developments. In Artificial Intelligence 2025: Global Practice Guides. Chambers and Partners.
7. https://practiceguides.chambers.com/practice-guides/artificial-intelligence-2025/malaysia/trends-and-developments
8. Sojitz Corporation. (2021, May 13). Sojitz invests in Ricult Inc., a U.S. agritech startup – Effecting synergy within new and existing business fields to raise farming efficiency [Press release]. Sojitz Corporation https://www.sojitz.com/en/news/article/20210513.htm
9. Royal Thai Embassy, Washington, D.C. (2023, September 5). Thai startup using AI to boost rice quality [Press release]. Royal Thai Embassy, Washington, D.C. https://washingtondc.thaiembassy.org/en/content/thai-startup-using-ai-to-boost-rice-quality
10. ResearchAndMarkets.com. (2025, January 14). Thailand AI in agriculture market competition, forecast & opportunities, 2029: Availability of affordable AI-based agri-tech solutions and increasing demand for precision farming [Press release]. GlobeNewswire. https://www.globenewswire.com/news-release/2025/01/14/3009508/28124/en/Thailand-AI-in-Agriculture-Market-Competition-Forecast-Opportunities-2029-Availability-of-Affordable-AI-Based-Agri-Tech-Solutions-and-Increasing-Demand-for-Precision-Farming.html
11. Australian Government Department of the Prime Minister and Cabinet. (2023, October 27). Long-term insights briefing: How might artificial intelligence affect trust and public service delivery? Retrieved from PM&C website https://www.pmc.gov.au/resources/long-term-insights-briefings/how-might-ai-affect-trust-public-service-delivery/landscape
12. CSIRO Data61. (2021). Artificial Intelligence Roadmap [PDF]. CSIRO. Retrieved from CSIRO website https://www.csiro.au/-/media/D61/Reports/AI-Roadmap/19-00346_DATA61_REPORT_AI-Roadmap-7.pdf
