Artificial intelligence (AI) is significantly transforming the biotechnology sector, particularly in the realms of agriculture and bioprocessing. A recent bibliometric study conducted by Niketan Deshmukh, PhD, director of the LJ School of Applied Sciences in Ahmedabad, India, and Reshma Talkal, PhD, deputy manager at Sundyota Numandis, analyzed global publication trends in this field from 2000 to 2025. Their research utilized AI tools to gather and assess data, revealing a notable increase in AI-related publications in biotechnology.
The study’s data collection relied on the Dimensions.ai database, which enhances natural language searches and summarizes articles using AI. Through their analysis, Deshmukh and Talkal identified a total of 5,422 articles related to AI in biotechnology. They noted a dramatic shift in publication frequency, with fewer than 50 articles per year from 2000 to 2015. However, this figure surged to 230 publications in 2018, reaching 622 in 2021 and projected to exceed 1,163 by 2024.
Growth and Trends in AI Utilization
Deshmukh and Talkal’s bibliometric analysis highlights a remarkable escalation in research activity within biotechnology, particularly post-2015. They observed that the early years exhibited a steady, moderate output, while a surge in interest and investment in AI technologies catalyzed significant advancements from 2016 onwards. Among the emerging trends, the researchers emphasize the importance of sustainable bioprocessing and the integration of AI into bioprocess automation.
The growth of AI applications in biotechnology can be attributed to several factors, including advancements in computational power, improved machine learning algorithms, and increased interdisciplinary collaboration. As Mike Bernhardt, a strategy expert with extensive experience in the high-performance computing ecosystem, noted: “At the core of a thriving scientific software ecosystem are the cross-disciplinary professionals who develop, maintain, and scale a growing suite of tools and applications.”
Despite the predominance of AI-related publications in the United States, which accounted for 30% of the total articles, Deshmukh and Talkal caution that maintaining this leadership position requires ongoing commitment. Bernhardt stresses that “scientific software is far more than an academic concern—it’s a foundational driver of national competitiveness.” He underscores the necessity of skilled human resources trained in AI applications for the biotechnology sector.
Investment Perspectives on AI’s Future
The significance of AI in biotechnology is also reflected in the views of venture capitalists. Thomas Thurston, chief technologist at Ducera Growth Ventures in Auckland, New Zealand, shared insights on the transformative potential of AI when effectively integrated with human expertise. He noted that the trends identified by Deshmukh and Talkal resonate with the investment patterns tracked by Ducera.
Thurston highlighted successful AI ventures in agriculture that bridge traditionally separate disciplines. For instance, one of Ducera’s portfolio companies collaborates computational biologists with entomologists to create peptide-based bioinsecticides, utilizing machine learning to optimize naturally occurring molecules targeting specific pests while preserving beneficial insects. Another company combines microbiome scientists with data engineers to analyze soil microbial communities, applying AI to understand complex interactions among microorganisms and develop targeted solutions for crop resilience.
Thurston pointed out that the rapid adoption of AI after 2015 can be attributed to the technology’s maturation, making it accessible to domain experts in the agricultural sciences who recognized AI’s potential for addressing long-standing challenges.
As the field of biotechnology continues to evolve, the success of AI applications will depend on fostering collaborations across disciplines. “Supporting these collaborative teams through targeted investment and mentorship creates the conditions for breakthrough innovations in sustainable agriculture,” Thurston concluded. This collaborative approach is anticipated to enhance the application of AI in sustainable bioprocessing as well, paving the way for a future where biotechnology can fully leverage the capabilities of artificial intelligence.
