Artificial intelligence is rapidly shedding its identity as a tool exclusive to the tech industry and emerging as a strategic asset in agribusiness. From document management to the automation of administrative and operational processes, AI is advancing across the entire agri-food value chain. According to Rodny A. Coronel, Regional Manager at ELO Digital Office España, the sector is now entering a critical phase: the “Second Wave” of AI.
“Agribusiness can no longer approach AI as an isolated experiment. Competitive advantage will depend on how effectively it is integrated into core business processes,” Coronel said in an interview ahead of ELO Horizons Barcelona 2026.
From Digitalization to Operational Intelligence
Across Europe, AI adoption is accelerating. In Spain, more than 23 per cent of SMEs already use AI technologies, while 21.1 per cent of large enterprises have embedded them into production processes. In the agro-industrial context, this is translating into a quiet yet profound transformation: digitalization of agricultural contracts, automation of purchase orders, document traceability, and predictive analytics applied to management.
The most common applications—such as natural language processing (44.7 per cent) and workflow automation (39 per cent)—are directly impacting critical areas of the sector, including compliance, supplier management, certification processes, and quality control.
“In agribusiness, information is highly fragmented—from contracts with producers to logistics and regulatory records. AI enables companies to unify and activate that knowledge,” Coronel explained.
Brazil Signals the Future of Ibero-American Agribusiness
Developments in Brazil reinforce this trajectory. With AI adoption at around 40 per cent—a level close to Europe—the country is already seeing tangible results: 95 per cent of companies report revenue growth, and 96 per cent report productivity gains.
In agro-industry, these improvements are evident in more efficient administrative management, optimized commercialization processes, and enhanced responsiveness to regulatory and market demands.
“Brazilian agribusiness is showing what will happen in Europe in the coming years: AI as the central axis of competitiveness,” Coronel noted.
Europe: Progress with Structural Gaps
Despite steady progress, Europe still faces significant disparities. Northern countries lead adoption rates, while markets such as Portugal lag behind, with an adoption rate of just 11.54 per cent. The primary barrier is not technological but organizational—over 74 per cent of companies cite a lack of internal expertise.
For agribusiness, this challenge is particularly acute. AI adoption requires not only investment but also workforce training to integrate these technologies into complex processes that combine production, logistics, regulation, and commercialization.
The Second Wave: End-to-End Automation
The concept of the “Second Wave” marks a fundamental shift. While the first phase focused on isolated tools—such as AI assistants or pilot generative AI projects—the new phase is defined by full business process automation.
In agribusiness, this means embedding AI across the entire document chain: from raw material intake to export operations, including certifications, invoicing, logistics, and regulatory compliance.
“The key is no longer automating tasks, but orchestrating complete processes,” Coronel summarized.
This shift addresses a global challenge: although 88 per cent of companies use AI in some capacity, only a minority achieve significant financial impact. Those that do are organizations that redesign workflows holistically.
Intelligent Document Management at the Core
In this context, platforms like ELO ECM Suite 25 are gaining prominence by positioning document management at the center of digital transformation in agribusiness.
The solution enables automated document capture, AI-driven metadata extraction, adaptive workflow management, and natural language search across enterprise information. The result is a dramatic reduction in processing time—tasks that once took days can now be completed in hours, with full traceability.
For agro-industrial companies, the implications are direct: Streamlined contract management with producers and distributors; Enhanced control over certifications and international regulations
Integration with ERP and CRM syste, ms; Optimization of procurement and sales processes; Reduced errors and operational risks
Regulation, Infrastructure, and Hybrid Models
Europe’s regulatory environment adds another layer of complexity. Approximately 42 per cent of AI investment is tied to compliance requirements, driving the adoption of hybrid models that combine cloud infrastructure with on-premise systems.
In agribusiness—where traceability and data security are critical—this flexibility is essential. “This is not just a technological decision; it is a risk management strategy,” Coronel emphasized.
Barcelona as a Strategic Hub for Digital Agriculture
The choice of Barcelona as the host city for ELO Horizons 2026 is strategic. The city is home to initiatives such as AI Factory, aimed at democratizing access to advanced AI infrastructure and accelerating innovation in key sectors, including agri-food.
The event, open to the public and free of charge, will take place on April 29 at Tech Barcelona.
With an investment of approximately €198 million, AI Factory is expected to enable companies to develop solutions in areas such as climatology, biotechnology, and data analytics—fields that are critical to the future of agribusiness.
A Moment of Decision
The message is clear: the time for experimentation has passed. “2026 will be the year of real implementation,” Coronel stated.
In a sector where margins are tightening and regulatory pressure is increasing, operational efficiency and adaptability will be decisive. For agribusiness, the “Second Wave” of AI is not merely a technological evolution—it represents a redefinition of the business model.
Companies that integrate AI into the core of their operations will be able to scale, optimize, and compete in an increasingly demanding global market. Those that do not risk being left behind, constrained by slow, fragmented, and less profitable processes.
Agriculture is already changing—and this time, the decisive factor will not be land or climate, but the intelligence with which data is managed.
