Generative AI for Climate-Smart Horticulture in Latin America

Across Latin America, horticulture is far more than a productive sector. It is a foundation of rural livelihoods, local food security, cultural continuity and biodiversity. Yet growers and community organizations across the region are operating in increasingly complex conditions. A single country can contain humid tropics, high-altitude valleys, semi-arid zones and temperate growing regions. From Mexico to Argentina, the combination of microclimates, soil diversity, shifting pest pressure and water stress means that generalized advice is rarely enough.

This is where generative AI can create real value. When trained on validated horticultural knowledge and combined with local weather patterns, soil conditions and region-specific pest signals, generative AI can help deliver hyperlocal recommendations that are more practical, more timely and more resilient. For growers, cooperatives and community organizations, that means better support for day-to-day decisions such as what to plant, when to irrigate, how to protect crops sustainably and how to adapt to changing climate conditions without losing sight of long-term ecological health.

Latin America cannot be treated as a single horticultural environment. Conditions vary dramatically not only between countries, but often within the same state, province or valley. Soil composition, altitude, rainfall, temperature swings and biodiversity all shape what can be grown successfully and sustainably. In this context, climate-smart horticulture depends on moving beyond static guidance toward recommendations that reflect the reality of each location.

Generative AI makes that shift possible by turning complex data into accessible, contextual advice. By integrating real-time weather data, seasonal forecasts, historical climate records and locally relevant horticultural expertise, AI can help identify better planting windows, irrigation timing and harvest strategies. When soil characteristics are also considered, the result is guidance that is better aligned to local growing conditions rather than broad regional averages. This is especially important in environments where small differences in elevation, rainfall or soil structure can significantly affect crop performance.

The value of generative AI in horticulture is not simply automation. Its real strength lies in making trusted knowledge easier to access and easier to apply. A digital assistant built on validated horticultural information can help translate technical guidance into usable recommendations for different audiences, from individual growers to cooperative leaders and community advisors.

For example, a grower could ask which crop varieties are better suited to current moisture conditions, which irrigation schedule may reduce water waste during a hotter-than-normal period, or which ecological interventions may help address a local pest outbreak. A cooperative could use the same platform to support many growers across a wider territory, identifying patterns in soil health, pest pressure or seasonal variability and sharing coordinated guidance at scale. Community organizations could use AI-enabled platforms to extend agronomic knowledge into schools, urban gardens and local food networks, helping more people participate in sustainable production.

Water efficiency is one of the most urgent priorities for climate-smart horticulture across Latin America. In many parts of the region, growers must manage increasingly irregular rainfall, longer dry periods and greater competition for water resources. Generative AI can support smarter water use by combining weather updates, historical conditions and crop-specific requirements to recommend irrigation practices that fit local circumstances.

This kind of precision matters for both sustainability and economic resilience. More targeted guidance can help reduce overwatering, minimize input waste and improve the use of fertilizers and other resources. For small and midsize producers, these efficiencies can lower costs while also reducing environmental impact. For communities managing shared water constraints, digital recommendations can support more informed planning and stronger stewardship of scarce resources.

In Latin America, horticulture exists alongside some of the world’s richest ecosystems. Climate-smart production therefore cannot focus only on yield. It must also protect pollinators, native species and the long-term health of local landscapes. Generative AI can support this balance by recommending native or climate-adapted species, crop associations and rotation strategies that strengthen soil health and encourage beneficial biodiversity.

These capabilities are particularly relevant in regions facing land degradation or rising ecological stress. By helping growers select crops and practices that are better suited to local ecosystems, AI can support regenerative approaches rather than input-heavy models. It can also help identify lower-impact responses to pests and diseases, reducing reliance on agrochemicals and encouraging more integrated, ecological interventions. That creates value not only for production, but for the wider environment that production depends on.

Climate change is already disrupting established horticultural rhythms. Growing seasons are shifting, extreme weather events are becoming more frequent and pest and disease patterns are becoming less predictable. In this context, static guidance loses relevance quickly. Generative AI offers a more adaptive model.

Because AI systems can be updated with new scientific findings, local observations and emerging environmental signals, recommendations can evolve as conditions change. That gives growers and organizations a better way to respond to uncertainty. It also opens the door to scenario planning: exploring how a different rainfall pattern, a hotter season or an increase in pest pressure might affect crop choices and management decisions. For a region as environmentally diverse as Latin America, this ability to adjust continuously is essential to resilience.

The opportunity is not limited to one-to-one advice. Digital platforms can strengthen the social side of horticulture as well. Across Latin America, cooperatives, producer groups and community organizations play a critical role in sharing knowledge, seeds, techniques and local experience. AI-powered platforms can make that exchange more visible, searchable and useful.

When community knowledge is combined with validated horticultural expertise and live environmental data, a stronger feedback loop emerges. Growers can learn from one another’s observations. Cooperatives can identify common issues earlier. Community groups can extend support to underserved populations through mobile-first, accessible tools. In this way, digital platforms do not replace local expertise; they amplify it.

This matters for resilient local food systems. More connected communities are better equipped to respond to shocks, preserve local growing knowledge and spread sustainable practices across different environments. Whether in peri-urban gardens, rural cooperatives or regional producer networks, digital access to timely, climate-aware guidance can help communities make better decisions together.

The future of horticulture in Latin America will be shaped by adaptation, not standardization. Success will depend on giving growers and communities access to tools that reflect the realities of their own climates, soils and ecosystems. Generative AI can help meet that need by democratizing access to trusted horticultural knowledge and translating complexity into practical action.

For Publicis Sapient, this is where digital transformation and environmental resilience intersect. The same capabilities that make generative AI powerful in horticulture—data, experience design, engineering and intelligent platforms—can help organizations create more accessible, adaptive and community-centered solutions. In Latin America, that means building systems that respect regional diversity, support sustainable practices and strengthen the local networks that make food systems more resilient.

From Mexico to Argentina, the opportunity is clear: use generative AI not to flatten difference, but to work with it. By combining validated horticultural knowledge with hyperlocal environmental insight, Latin America can advance a more climate-smart, biodiversity-conscious and digitally connected model of horticulture—one that helps communities grow with greater confidence in a changing world.

Relevant Links

• Our Locations
• From Inspiration to Implementation: How Generative AI Makes Sustainability Actionable in Horticulture
• What Nonprofits and Membership Organizations Can Learn from the RHS Chatbotanist
• De l’inspiration à l’exécution : comment l’IA générative rend la durabilité actionnable dans l’horticulture européenne (Europe)
• IA generativa para una horticultura climáticamente inteligente en México (LATAM)
• FAQ (FAQ)
• FAQ (FAQ)
• Our Locations
• What to Know About Generative AI in Horticulture: 10 Key Facts for Climate-Smart, Hyperlocal Guidance (LIST)
• 10 Things Buyers Should Know About Generative AI for Climate-Smart Horticulture (LIST)