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THE CARIBBEAN & LATIN AMERICA ADRIAN DUNKLEY ↗
Sector

Agriculture

Farm record keeping, draft communications and questions for qualified local advisers.

Banana plantation, Saint Lucia
Banana plantation, Saint Lucia — Brian Snelson, CC BY 2.0, via Wikimedia Commons. Date: 2006-10-18. Licence terms. Original and source record. Displayed proportionally without cropping or alteration. Historical documentary context, not evidence of AI use or endorsement.
Practical guide

Farm sizes, crops and connectivity vary across the region. Test assistance against local needs.

Start with field records, planning calendars and export-document checklists. Qualified local advisers must validate agronomic and regulatory decisions.

Where AI fits

Workflows to test.

  • Pest and disease diagnosis

    Organise field observations for a qualified agronomist; do not diagnose or apply treatment from a chatbot alone

  • Planting and harvest calendars

    Region-specific calendars adjusted for actual local weather, not generic averages

  • Export compliance documentation

    Draft supporting records for broker review; only authorised bodies can issue official certificates

  • Market price intelligence

    Weekly briefings on regional commodity prices for cocoa, coffee, bananas, and sugar

Where AI fails

Failure modes to plan for.

  • Connectivity in fields

    A cloud-only diagnosis tool fails where farmers actually work. Always have offline-capable fallback

  • Generic recommendations

    A model trained on US Midwest corn does not know about Caribbean root crops. Local data matters

  • Insurance triggers

    AI yield predictions used for parametric insurance must be auditable and contestable

Start here

Plan a measured pilot.

  1. 1 Pilot the LATAM Farmer skill with five farmers in one cooperative for one growing season
  2. 2 Build a Knowledge Base with local crops, pest history, and export destinations
  3. 3 Have a qualified local agronomist validate all agronomic advice before action and measure trial outcomes
Reference

In depth: AI use cases for Agriculture.

AI in Agriculture: Caribbean & Latin America

Before using these prompts

These are proposed workflows, not reports of measured results or guaranteed savings. Country examples are suggestions to investigate, not official rankings or evidence of local deployment. Start with one task, record the existing time, cost and error rate, then compare a reviewed pilot against that baseline.

Use synthetic or anonymised examples. Do not paste personal, customer, patient, pupil or employee records into a public chatbot. Use only an organisation-approved service with an appropriate lawful basis and data safeguards. Ask for dated primary-source links for laws, prices, statistics and local services; independently open and check them. If a source or input is missing, leave it unknown. A generated answer does not establish legal compliance. A responsible person must approve consequential decisions and external communications.

Tool names are examples, not endorsements. Check current vendor terms, pricing, country availability and suitability before use.

Use AI to organise field observations and questions for an agronomist. Do not apply pesticide, fertiliser or irrigation changes from a chatbot alone. A qualified local adviser must validate the diagnosis, product registration, label instructions, rates and environmental risks. Export checklists require the destination authority and a qualified broker; AI cannot issue certificates or guarantee market access.

Transforming Food Systems Across the Region

Created by Adrian Dunkley | maestroailabs.com | ceo@maestrosai.com


Why Agriculture AI Matters in Our Region

  • Brazil, Argentina, and Mexico are global agricultural giants
  • Climate change threatens regional food security

Universal Agriculture AI Use Cases

1. Crop Disease Diagnosis

AI Tool: Claude, Plantix (free mobile app), ChatGPT Prompt:

I am a farmer in [country], [region/department/parish].
I grow [crop] on [X] hectares/acres.
My plants are showing these symptoms: [describe: yellowing leaves/
spots/wilting/stunted growth/unusual coloration].
Affected percentage: [X]%.
Recent weather: [dry/wet/temperature extremes].
Soil type: [clay/sandy/loamy].

Organise the observations into a checklist for a local agronomist.
List possible explanations and missing evidence without diagnosing or
recommending treatment. Do not invent yield effects or registered products.

2. Precision Fertilization Plan

AI Tool: Claude, ChatGPT Prompt:

Create a fertilization plan for [crop] in [country].
Soil test results: pH [X], N [X], P [X], K [X], Organic Matter [X]%.
Crop growth stage: [stage].
Target yield: [X tonnes/hectares].
Available fertilizers in my area: [list].
Budget: [amount in local currency].
Water availability: [irrigated/rain-fed].
Prepare questions for an agronomist about nutrient needs and soil-test limitations.
Do not prescribe application rates. Compare costs only from supplied quotes;
leave yield improvement unknown until measured in a validated trial.

3. Climate-Smart Farming Calendar

Countries: All | AI Tool: Claude, ChatGPT Prompt:

Create a 12-month farming calendar for [crop type] in [country], [region].
Climate type: [tropical/subtropical/highland/coastal].
Rainfall pattern: [wet season months / dry season months].
Common climate risks: [hurricanes/drought/flooding/frost].
Land size: [X hectares/acres].
Market target: [local/export/processing].
Include: planting dates, irrigation schedule, fertilization calendar,
pest/disease monitoring timeline, harvest schedule,
post-harvest activities, and climate risk mitigation actions.

4. Agricultural Export Documentation

AI Tool: Claude, ChatGPT Prompt:

I want to export [product] from [country] to [destination market: US/EU/UK/Japan].
My product: [description, organic/conventional, volume].
Help me: identify phytosanitary requirements,
packaging and labeling specifications for [market],
required certifications (GlobalGAP, organic, fair trade),
documentation checklist for customs,
common compliance failures and how to avoid them,
and national export support programs available in [country].

5. Farm Business Plan

AI Tool: Claude, ChatGPT Prompt:

Create a [1-year/3-year/5-year] business plan for a [crop/livestock] farm in [country].
Farm size: [X hectares/acres] in [region/department].
Current production: [description or "starting from scratch"].
Available investment: [amount in local currency].
Market target: [local market/export/agro-processing].
Water resources: [description].
Create: production plan, investment schedule, revenue projections,
break-even analysis, risk assessment with mitigation,
available government subsidies and programs in [country],
and market access strategy.

Country-Specific Agriculture AI Applications

Caribbean Agriculture

Key Opportunity: Investigate locally viable production and post-harvest improvements

Jamaica: Blue Mountain Coffee AI grading → pilot grading consistency; price effect unmeasured Trinidad: Cocoa traceability → records for expert review against applicable EU rules Barbados: Greenhouse agriculture → year-round food production Dominican Republic: Cacao/avocado export optimization → EU/US market access Guyana: Rice precision agriculture → pilot field monitoring; yield effect unmeasured

Latin America Agriculture

Key Opportunity: Lead global sustainable food supply

Brazil: Soy/beef deforestation monitoring → records for destination-authority review Colombia: Coffee quality grading AI → specialty premium pricing Mexico: Avocado supply chain tracking → records for US import-rule review Peru: Quinoa/cacao traceability → fair trade premium Chile: Precision viticulture → wine quality optimization Argentina: Variable rate application → pilot input planning; cost effect unmeasured Ecuador: Banana disease monitoring → reduced fungicide use


Agricultural AI Tools: Regional Availability

ToolUse CaseCostAvailability
PlantixPlant disease diagnosisFreeCheck current official platform and country support
ClaudeAll agricultural tasksFree/ProCheck vendor eligibility
ChatGPTAll agricultural tasksFree/PlusCheck vendor eligibility
CropinFarm managementPaidLatin America
AgriForceCrop analyticsPaidLatin America
FarmosOpen source farm managementFreeCheck vendor eligibility
AgromonitoringSatellite field monitoringFreemiumCheck vendor eligibility

What to measure in a pilot

WorkflowBaseline and outcome to record
Field observationsTime to qualified assessment; missed or incorrect alerts
Nutrient planningApproved input cost and measured yield against a comparable plot
Export documentationPreparation time, corrections and rejected submissions
Business planningStaff time and forecast error against actual results
Market researchVerified prices, research time and realised selling price

No improvement percentage is established by these examples.


Created by Adrian Dunkley | MaestrosAI | maestroailabs.com | ceo@maestrosai.com

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Cite this page

Dunkley, Adrian. “Agriculture.” LAC AI Playbook. https://aiplaybooklac.netlify.app/sectors/agriculture/. Include your access date when citing this changing resource.

Geographic coverage: Latin America and the Caribbean. This describes the subject of the guidance, not the author's location or a service address.

Credit Adrian Dunkley when quoting or adapting the playbook. Cite the original research for its findings. Third-party text, photographs and other materials retain their own rights; citation alone does not grant permission to reproduce them.