Reflecting on 2024’s progress, Ron Baruchi, CEO of Agmatix, explores how these advancements shape the future of global agricultural innovation, turning potential into practical, impactful change.
This past year has tested the agricultural technology sector and growers alike, with rising costs, climate challenges, and persistent uncertainties pushing many to embrace a “do more with less” mindset under tight deadlines. While AgTech has continued to revolutionize traditional practices, the challenges of the past year have tempered its speed and impact. My 2024 predictions highlighted the sector’s readiness for transformation, but the year’s realities underscored the resilience required to overcome these hurdles.
As we reflect on how technologies evolved in 2024 to support these realities, we explore what they mean for the future of agricultural innovation on a global scale - turning potential into practical, scalable solutions to meet the demands of a changing world.
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1 Data-Driven Regenerative Agriculture
Regenerative agriculture is transforming global farming by improving soil health, biodiversity, and sustainable crop production. AI has empowered farmers to adopt these methods more effectively by tailoring decisions to local conditions and ecological needs. Going into 2024, I anticipated increased adoption of regenerative practices, supported by advanced analytics.
Outcome:
Adoption indeed accelerated, but with a broader focus than expected. The McKinsey Global Farmer Insights 2024 survey revealed that 68% of farmers adopted crop rotations, 56% implemented reduced or no tillage, and 40% used variable rate spraying or fertilization[1]. However, motivations varied regionally, yield improvement was key in India, Latin America, and North America, while European farmers prioritized additional revenue streams.
Looking Ahead:
The “nature positive” movement, which emphasizes net gains in biodiversity and ecosystem health, is gaining traction. 2025 will likely see metrics expand beyond carbon to include soil quality, biodiversity levels, and forest conservation, enabling farmers to meet regional specific ecological requirements. This evolution supports practical ways to measure and assess the impact of regenerative agriculture, thereby enhancing the resilience and sustainability of agricultural systems.
2 Generative AI: Unlocking New Data Potential
Generative AI is revolutionizing agriculture by transforming vast datasets into actionable insights, empowering farmers, agronomists, and researchers to optimize productivity and sustainability. As we approach 2025, I expect AI to play an increasingly critical role in data analysis and decision-making.
Outcome:
AI integration in agriculture progressed faster than anticipated, evolving from simple chatbots to sophisticated AI agents powered by Large Language Models (LLMs). These agents now engage in conversations, complete tasks, and show some degree of autonomous behavior, fundamentally reshaping farm data analysis and decision making.
Looking Ahead:
In 2025, Generative AI is set to become a cornerstone for agricultural companies. Advanced platforms using AI already exist, unlocking real-time insights from vast datasets, empowering agronomists and researchers to optimize product performance and accelerate decision-making. Adoption of these tools will help to validate the efficacy of solutions like biologicals, which play a critical part in advancing sustainability.
3 Data-Driven Product Development for Grower Success
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Data-centric technologies are optimizing field trial outcomes, enhancing decision-making and driving innovation in agricultural practices. Beyond streamlining operations, these technologies were expected to enable breakthroughs across the agricultural value chain in 2024, accelerating the pace of innovation.
Outcome:
Over the past 12 months, we witnessed a growing focus on using data to meet growers’ evolving needs, setting the stage for further integration and innovation in 2025. The adoption of digital tools varied significantly across regions and farm sizes. In North America, 61% of farmers used digital agronomy tools, 51% adopted precision agriculture hardware, and 38% used remote sensing technologies[1]. However, uptake was lower in other regions and among smaller farms.
Looking Ahead:
In 2025, I expect data-driven solutions to become integral to efficiency across the agricultural value chain. From accelerating product trials to optimizing precision crop nutrition protocols, these tools will deliver actionable insights, enhancing productivity and supporting regenerative practices in real-time. As biodiversity becomes a priority, data tools will measure the impact of farming practices on local ecosystems, helping companies achieve sustainability and productivity goals.
4 Meeting Resource Constraints with AI and Machine Learning
To meet the needs of a growing global population, amid finite resources and rising costs, agriculture must embrace innovations like biosolutions, AI, and machine learning. These technologies improve productivity while reducing environmental impact. In 2024, we expected an increased focus on innovations to address resource constraints, particularly with the use of biosolutions.
Outcome:
Biosolutions development and adoption progressed, with Brazilian farmers leading the way (64% adoption rate) due to government support and high fertilizer costs[1]. While this did happen in 2024, adoption rates varied significantly across regions.
Looking Ahead:
In 2025, as more companies adopt “nature positive” targets, real-world pilots and trials will increase to validate new biosolutions and other innovative products. These trials will be crucial in assessing the impacts of specific crop varieties, products, or practices on yield and the environment, ensuring solutions effectively tackle climate change, resource constraints, and growing global food demands.
5 Digital Twins: The Untapped Frontier in Agriculture
Digital twins are virtual replicas of real-world systems, enabling simulation and prediction without physical testing. Although widespread in healthcare and manufacturing, they are underused in agriculture, despite its potential to improve precision and cut costs in field trials. We predicted that 2024 would see an increase in the use of digital twins.
Outcome:
In 2024, agriculture lagged behind other industries in adopting digital twins and synthetic data, hindered by challenges like limited data integration, slower technology adoption rates, and the complexity of replicating dynamic environmental variables in virtual models. However, interest in digital twins has grown, setting the stage for future advancements.
Looking Ahead:
In 2025, digital twins will gain traction in agriculture, being the ideal time for its adoption and scaling. By enabling virtual testing of variables like soil types and weather conditions, they will reduce time and costs in product testing and support more precise innovation in agricultural practices. Integrating synthetic data will further improve field trial efficiency, accuracy, and safety. This combination allows researchers and agronomists to model scenarios that were previously impractical, supporting smarter resource use and adaptive management strategies. These models will help us to better understand and manage the ecological impact of various practices, paving the way for a more resilient and sustainable agricultural future.
Building a Sustainable Future for Agriculture
Reflecting on 2024 and looking forward to 2025, it’s clear that the agricultural sector is rapidly evolving. And while many of my 2024 predictions were on point, the pace and direction of change was surprisingly slow.
So, in 2025, I anticipate even more advancements in data-driven agriculture, as well machine learning and other innovative solutions to allow us to tackle resource constraints. And I expect this to be in combination with the adoption of disruptive technologies like digital twins. It’s also clear to me that the impact of artificial intelligence in agriculture, will continue to be a key driver in shaping a regenerative agricultural future.
In conclusion, to fully leverage these advancements in 2025, agricultural stakeholders should:
1. Prioritize data integration and interoperability
2. Focus on developing user-friendly solutions
3. Emphasize education and support for new technologies
4. Foster collaboration between technology providers, research institutions, and agricultural stakeholders
5. Adapt solutions to regional needs and farm sizes
By embracing these trends and focusing on practical implementation, agriculture can build a more resilient, productive, and sustainable future for food production. The commitment to biodiversity and nature-positive practices, alongside technology-driven advancements, will be key in shaping a truly sustainable agricultural future.
