Syngenta streamlines sustainable crop protection R&D with data-driven innovation
Syngenta, a leader in agricultural innovation, faced accelerating demand for eco-friendly crop protection and biological fertilizers. Using Microsoft Azure AI services—including Azure OpenAI Service, Azure Machine Learning, and Microsoft Copilot—Syngenta transformed its global research and development. By embedding AI and machine learning across all research projects, Syngenta identifies novel bioactive ingredients for soil health and sustainable crop protection, significantly reducing reliance on traditional chemicals. Azure AI automated the design and experimentation process, allowing Syngenta to rapidly test and innovate with data-driven precision. Copilot aids in literature review and knowledge synthesis, letting teams discern opportunities fast. This real-world deployment enabled Syngenta to accelerate the creation of environmentally responsible products, foster rapid R&D cycles, and deliver on ambitious sustainability goals. The transformation allowed Syngenta to better respond to farmers, speed up delivery of new products, and support greener agriculture practices, especially in markets like Spain.
- Organization
- Syngenta
- Industry
- Agriculture
- Location
- Spain
- Published
- March 2025
Reported outcomes
Strategic outcomes
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Syngenta
- Provider
- Microsoft
- Maturity
- Production
- Linked source
Improved operational efficiency by automating experimentation and literature review
Primary read
Use case focus
Showing 3 of 3
- 1biological fertilizer design
- 2crop protection R&D acceleration
- 3AI-driven ingredient discovery
- Syngenta needed to accelerate development of eco-friendly crop protection and biological fertilizers.
- Traditional R&D methods were slow, costly, and relied on chemical solutions harmful to the environment.
- Sustainability targets and regulatory pressures demanded faster, data-driven innovation cycles.
- Complexity of scientific research required improved knowledge synthesis and efficient data analysis.
- Syngenta embedded Azure AI and Azure OpenAI Service across R&D projects.
- Microsoft Copilot streamlined literature synthesis and experiment design.
- AI-driven predictive modeling and generative design accelerated discovery of novel active ingredients.
- Automated workflows reduced manual testing and optimized research processes.
- Reduced R&D cycles significantly and shortened time-to-market for safer crop solutions.
- Accelerated identification of sustainable bioactive ingredients to replace harsh chemicals.
- Improved operational efficiency by automating experimentation and literature review.
- Enhanced sustainability by increasing availability of eco-friendly products for farmers.
Sources & evidence1
- Customer explicitly identified
- Deployment status explicitly supported
- Technical implementation details available
- Recent evidence check available
- Last evidence check: Jul 22, 2026.
The case's original source is still reachable.
- Cited source last checked Jun 12, 2026 — ok (0/1 broken).
Measures whether this deployment's public evidence persists — not whether the system is still in production.
AI-generated summary. Verify important details with the linked sources before relying on this case.
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