One of the most forward-looking discussions at the 59th CETAF General Assembly (CETAF59) was a panel organised by the CETAF Scientific Research Working Group (SciReg), which explored how taxonomy is evolving in an increasingly digital, data-rich and technology-driven research landscape.
Moderated by Emily Hartop (NTNU University Museum) and Eva van der Veer (Naturalis Biodiversity Center), the panel brought together perspectives from molecular taxonomy, scientific publishing, artificial intelligence, collection management, training and research infrastructures to discuss the opportunities and challenges facing the discipline.
Under the title Integrative Taxonomy: Revolution, Automation or Preservation?, the discussion examined how new technologies and data-driven approaches are reshaping species delimitation, knowledge production and expertise, while also raising important questions about openness, reproducibility and the future role of taxonomists.
Integrative taxonomy remains central
One of the strongest themes emerging from the discussion was that technological innovation should complement, rather than replace, integrative approaches to taxonomy.
Nicolas Puillandre (Muséum National d’Histoire Naturelle, Paris) argued that taxonomy is fundamentally a science of hypotheses. While molecular approaches have transformed species delimitation and discovery, relying on a single source of evidence can reduce the robustness of taxonomic conclusions. Instead, he emphasised the importance of combining multiple lines of evidence whenever possible, including morphology, genetics, ecology and other relevant data sources.
The discussion also highlighted practical challenges. While some participants argued for wider adoption of molecular approaches, others noted that access to advanced technologies remains uneven across institutions and regions. Collaboration, rather than standardisation alone, emerged as a recurring theme for addressing these differences.
Automation without replacing expertise
Artificial intelligence and automation featured prominently throughout the panel. However, speakers generally rejected the idea that automation and traditional taxonomy represent opposing approaches.
David Williamson (NTNU University Museum) described machine learning, computer vision and automation as tools that can help researchers process large volumes of information more efficiently while still relying on expert validation and interpretation. Automation may assist with tasks such as specimen identification, image analysis and information extraction, but the expertise required to interpret results and formulate taxonomic hypotheses remains essential.
Similarly, discussions around automation focused not only on accelerating workflows, but also on ensuring transparency, reliability and reproducibility as new technologies become more widely integrated into taxonomic research.
Collections and data in a digital age
From a collections perspective, Eva van der Veer highlighted both the opportunities and challenges associated with large-scale digitisation. Digital collections increase accessibility and enable new forms of research, but physical voucher specimens remain the foundation of taxonomy and biodiversity science.
The panel also addressed the growing importance of open science and data infrastructures. Dimitris Koureas (Naturalis Biodiversity Center / DiSSCo) argued that the conversation is increasingly moving beyond access to data alone and towards access to the tools, infrastructures and services required to interpret and use that data effectively. In a world characterised by growing volumes of biodiversity information, making data available is only one part of the challenge.
Laurence Bénichou (Muséum National d’Histoire Naturelle and European Journal of Taxonomy) emphasised the role of scientific publishing in supporting data mobilisation and interoperability. Discussions highlighted the importance of connecting publications, specimens and digital infrastructures in ways that prevent the creation of future “legacy data” problems and improve long-term accessibility and reuse.
Preparing the next generation of taxonomists
A final theme concerned the skills and expertise that future taxonomists will need.
Drawing on her experience leading CETAF’s Training and E-learning Working Group, Iasmi Stathi (Natural History Museum of Crete-University of Crete NHMC-UoC) highlighted the importance of maintaining strong foundations in organismal biology and morphology while also embracing molecular methods, biodiversity informatics, artificial intelligence, scientific communication and interdisciplinary collaboration. She stressed that no individual researcher can master every aspect of modern taxonomy, making cooperation and knowledge exchange increasingly important.
Several panellists also noted that attracting and supporting the next generation of taxonomists will require not only training opportunities but also sustainable career pathways and institutional investment.
Continuing the conversation
The panel did not seek to provide definitive answers about the future of taxonomy. Instead, it offered a space to reflect on how the discipline is evolving as new technologies, infrastructures and forms of collaboration emerge.
While views differed on specific questions, participants broadly agreed that the future of taxonomy is unlikely to be defined by automation, molecular approaches or traditional practices alone. Rather, it will depend on the continued integration of diverse sources of evidence, open and connected data infrastructures, and the expertise of the people who interpret and apply them.
As the discussion concluded, one message stood out clearly: technological innovation may transform how taxonomy is practiced, but the need for collaboration, critical thinking and scientific expertise remains as important as ever.
This article is part of CETAF’s coverage of the 59th General Assembly (CETAF59) held in Florence, Italy. Explore related articles on CETAF’s newest members, the 2026 e-SCoRe Award, and key discussions on integrative taxonomy and colonial collections.