AI-Powered Farming: The Future of Agriculture in Croatia
How Autonomous Drones and Robots Can Solve the Labor Shortage in Agriculture
Croatia is a country of immense natural beauty, with fertile land stretching from the Pannonian plains to the Dalmatian coast. Yet, despite this agricultural potential, a pressing problem threatens its future: a shrinking and aging workforce.
Rural depopulation has left vast tracts of farmland underutilized, while younger generations migrate to urban areas or abroad in search of better economic opportunities (Euractiv).
I can personally attest to all this, since I am not only a dual citizen with a Croatian passport, but I also own unused farmland in the country.
As a technologist, every time visit the farm, I wonder:
What if the solution wasn’t finding more workers—but eliminating the need for them? In this case, we are not talking about taking away jobs, but filling the void.
Artificial intelligence (AI), robotics, and autonomous drones are transforming farming, making it possible to cultivate vast areas with minimal human intervention. By leveraging cutting-edge technology, Croatia can not only revitalize its agricultural sector but also become a leader in AI-driven farming in Europe.
The Problem: Not Enough Farmers, Too Much Land
Croatia’s agricultural workforce is aging and shrinking at an alarming rate. As of 2018, only 13% of Croatian farmers were under the age of 40, while over 50% were over 60 years old (Euractiv). The younger workforce is steadily declining as well; from 2008 to 2021, approximately 128,000 individuals under the age of 35 left the Croatian labor market, reducing their representation to just a third of the total workforce (N1 Info).
This labor shortage has had a direct impact on agriculture, leading to vast areas of fertile land being left uncultivated. Meanwhile, Croatia remains a net food importer, relying on foreign produce despite having the natural resources to produce much more domestically. In 2022, Croatia had a trade deficit of $19 billion, with imports totaling $44.3 billion while exports were only $25.3 billion (Lloyds Bank). Increasing domestic agricultural production through AI-driven automation could help reduce this dependency and improve food security.
The AI Farming Revolution: How It Works
Imagine a farm where:
AI-powered drones scan fields for pests and diseases before they spread.
Autonomous tractors and robots plant, weed, and harvest crops without human operators.
IoT sensors in the soil monitor moisture and nutrients, ensuring efficient irrigation.
AI-driven analytics predict the best planting and harvesting times, maximizing yields.
This isn’t science fiction—it’s already happening in parts of the world, and Croatia has the perfect conditions to adopt it (AgFunderNews).
Building an Autonomous, AI-Driven Farm in Croatia
Step 1: Deploy Autonomous Drones for Crop Monitoring
Traditional farming relies on human observation, but AI-driven imaging drones can do the job faster and more accurately.
Example: The DJI Matrice 300 RTK, equipped with the MicaSense RedEdge-P multispectral sensor, can scan entire fields and detect early signs of disease, drought stress, or pest infestations—allowing farmers to take action before crop damage occurs (DJI).
Cost: $20,000+ for a fully equipped drone system.
Benefit for Croatia: A single AI-powered drone can monitor hundreds of hectares daily, eliminating the need for large labor forces while preventing crop losses.
Step 2: Introduce Autonomous Weeding & Spraying Robots
AI-driven weeding robots, like Naïo Oz, eliminate the need for expensive herbicides by precisely identifying and removing weeds without chemicals (Naïo Technologies).
For spraying, autonomous drones like the DJI Agras T40 can apply pesticides and fertilizers only where needed, reducing waste and environmental damage.
Cost: ~$30,000 for an autonomous weeding robot; $20,000 for a spraying drone.
Savings: Up to 90% reduction in pesticide usage, lowering costs while making farming more sustainable (PrecisionAg).
Step 3: Implement AI-Powered Irrigation & Soil Monitoring
Water is one of Croatia’s most valuable resources, and traditional irrigation methods often waste vast amounts of it. AI-powered irrigation systems, using IoT sensors and machine learning, optimize water use by monitoring real-time soil moisture and weather data.
Example: The Arable Mark 2 sensor can measure soil conditions, humidity, and even plant health, adjusting irrigation accordingly (Arable).
Cost: $2,000 per unit, with 5–10 units needed per farm.
Water savings: Up to 50% less water wasted compared to traditional irrigation (FAO).
Step 4: Fully Autonomous Harvesting
AI-driven harvesting robots, such as FFRobotics’ fruit-picking robots, can harvest crops like apples, grapes, and strawberries without human hands (FFRobotics).
Cost: $100,000–$200,000 per robot.
Potential savings: A robot can replace a team of seasonal workers, ensuring faster, 24/7 harvesting with no labor shortages.
Implications for the Workforce: New Jobs & Operational Needs
While AI farming reduces the need for traditional manual labor, it creates new job opportunities in technology and operations:
AI & Robotics Maintenance Technicians – Skilled workers to service autonomous tractors, drones, and sensors.
Data Analysts & Agritech Specialists – Experts who interpret AI-driven farm analytics to optimize yields.
Farm Operations Managers – Professionals who oversee automated farming systems and integrate AI solutions.
Software Engineers & IoT Experts – Developers who design and maintain farm management platforms.
Logistics & Supply Chain Coordinators – Workers ensuring AI-optimized supply chains efficiently distribute produce.
AI Trainers & Agricultural AI Specialists – Professionals fine-tuning AI models to adapt to local farming conditions.
Currently, Croatia’s labor market for AI and machine learning professionals is growing. As of March 2025, there were 30 active job openings for Machine Learning Engineers, with 87% based in Zagreb (LinkedIn Jobs). The demand is primarily for mid-senior level professionals, making up 53% of roles.
To support this shift, Croatia can source talent from institutions like:
University of Zagreb Faculty of Agriculture – Offers a course in Agrorobotics.
University of Zagreb Faculty of Electrical Engineering and Computing – Provides a program in Intelligent Field Robotic Systems.
Algebra University – Offers AI and Data Science degrees.
Josip Juraj Strossmayer University of Osijek – Introduced a Digital Agriculture program.
The Future: Croatia as Europe’s AI Farming Leader?
AI-driven farms are not just a fix for labor shortages—they represent a new era of agriculture where food production is smarter, more efficient, and sustainable. With vast arable land but a limited workforce, Croatia has the potential to become a global leader in AI-powered farming and an exporter of high-tech, AI-optimized agricultural products.
By leveraging robotic automation, data-driven precision farming, and AI-driven supply chains, Croatia could significantly increase food exports, reduce reliance on imports, and establish itself as an agricultural powerhouse in Europe (World Economic Forum).
The country could become a key supplier of high-quality, sustainably grown produce to the EU and beyond, improving economic resilience and strengthening rural communities.
But Croatia is just one example. Other small nations with great agricultural potential—such as Hungary, Serbia, and the Baltic states—could follow the same model. By integrating AI-driven farming solutions, these countries can overcome workforce shortages, boost productivity, and enhance food security while positioning themselves as leaders in next-generation agriculture.
As great as this sounds, there are undeniable challenges and hurdles to any individual or group trying to establish an “Autonomous AI Farm”, whether in Croatia or anywhere else.
In a follow-up article, I will examine these challenges, so stay tuned.