Artificial intelligence (AI) is significantly transforming the field of biotechnology, particularly in bioprocessing. A recent study conducted by Niketan Deshmukh, PhD, director of the LJ School of Applied Sciences in Ahmedabad, India, alongside Reshma Talkal, PhD, deputy manager at Sundyota Numandis, highlights the growing impact of AI in this sector. Their bibliometric analysis examines global publication trends from 2000 to 2025, revealing a marked increase in research activity.
Deshmukh and Talkal employed AI tools to gather data from the Dimensions.ai database, which enhances natural language searches and article summaries. Using R programming and the VOSviewer software for data visualization, they identified a total of 5,422 articles related to AI in biotechnology. The findings indicate that from 2000 to 2015, fewer than 50 articles were published annually. This trend experienced a dramatic shift starting around 2016, with publications rising from 230 in 2018 to 1,163 in 2024.
The researchers note, “The bibliometric analysis of AI applications in biotechnology highlights a remarkable growth in research activity over the past two decades, particularly after 2015.” The data reveals that while the years leading up to 2015 were characterized by steady yet modest output, the subsequent years showcased exponential growth, particularly in sustainable bioprocessing and bioprocess automation.
Collaboration Drives AI Integration
Deshmukh and Talkal attribute the acceleration of AI applications in biotechnology to advancements in computational power, sophisticated machine learning algorithms, and increased cross-disciplinary collaboration. Highlighting the importance of human involvement, Mike Bernhardt, a strategy expert in the high-performance computing ecosystem, stated, “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.”
The study reveals that the United States currently leads in publications applying AI to biotechnology, accounting for approximately 30% of the relevant journal articles. However, maintaining this lead is not guaranteed. Bernhardt emphasizes the need for continued focus on scientific software development, noting its critical role in national competitiveness and its potential impact on sectors such as clean energy, materials science, and agriculture.
Despite its potential, AI faces challenges in fully realizing its benefits in biotechnology. Bernhardt remarks, “AI, for the foreseeable future, is not self-evolving in any form that will benefit biotechnology without proper guidance.” He stresses the necessity of a skilled human workforce adept in AI applications within this essential research field.
Venture Capital Insights
The perspective of venture capitalists often reflects the perceived significance of emerging technologies. Thomas Thurston, chief technologist at Ducera Growth Ventures in Auckland, New Zealand, provides insights into AI’s transformative role in biotechnology. He states, “Through our work supporting agricultural innovation ecosystems, we witness firsthand how AI transforms biotechnology when properly integrated with human expertise.”
Thurston notes that the bibliometric trends identified by Deshmukh and Talkal align with investment patterns observed in the sector. Successful AI ventures in agriculture often connect traditionally separate disciplines. For example, Ducera Growth Ventures supports companies where computational biologists collaborate with entomologists to develop peptide-based bioinsecticides, utilizing machine learning to enhance pest management while safeguarding beneficial insects.
Another illustrative case involves a portfolio company that merges microbiome scientists with data engineers to analyze soil microbial communities. This interdisciplinary approach has been pivotal in accelerating AI adoption post-2015, as the technology became accessible to domain experts ready to tackle complex agricultural challenges.
Collaboration remains key across various fields, from agriculture to healthcare. Thurston emphasizes that fostering these collaborative teams through targeted investment and mentorship is essential for unlocking breakthroughs in sustainable agriculture. Similar approaches are expected to yield significant benefits in sustainable bioprocessing and beyond.
The study by Deshmukh and Talkal underscores the pivotal role of AI in biotechnology’s evolution. As the landscape continues to evolve, the integration of AI into bioprocessing and other areas promises to drive innovation, enhance efficiency, and address global challenges in sustainability.
