Terminology Management Meets AI : The ISO / TC 37/ SC 3/ WG 6 Initiative (2025)

Abstract: The integration of artificial intelligence (AI) with terminology management (TM) has opened new avenues for enhancing efficiency and precision in both fields, necessitating standardized approaches to ensure interoperability and ethical application. The newly formed ISO/TC 37/SC 3/WG 6 represents the first dedicated initiative to study the standardization of the mutual improvements of AI and TM. This group aims to develop standardized frameworks and guidelines that optimize the interaction between AI technologies and terminology resources, benefiting professionals, systems, and practices in both domains. This article presents the state-of-the-art in the mutual relationship between AI and TM, highlighting opportunities for bidirectional advancements. It also addresses limitations and challenges from a standardization perspective. By tackling these issues, ISO/TC 37/SC 3/WG 6 seeks to establish principles that ensure scalability, precision, and ethical considerations, shaping future standards to support global communication and knowledge exchange.

## introduction tm is critical to global communication by supporting the common understanding and exchange of specialized knowledge across languages and cultures. within iso's technical committee 37 "language and terminology" (iso/tc 37) 1 , subcommittee 3 (sc 3) 2 "management of terminology resources" has played a pivotal role in formulating general principles, recommendations, and best practices for implementing effective, interoperable, and machine-readable tm systems. these systems support various computer language related processes, such as computer-assisted translation (cat), controlled authoring, search engine optimization, and machine learning. this bidirectional relationship, where ai functions both as a support technology for tm and as a domain requiring terminological data for improvement, is the focus of iso/tc 37/sc 3/wg 6 "terminology management and artificial intelligence". this working group (wg) aims to develop standards that facilitate both the successful and ethical integration of ai into tm systems and the effective use of terminology resources to improve ai solutions. this paper discusses the challenges of standardizing this relationship within an unprecedented, rapidly evolving technological landscape. ## iso/tc 37/sc 3/wg 6: a strategic player in bridging terminology management and ai 4.1 positioning the new wg in the global standardization and regulatory landscape iso/tc 37 develops international standards that support the language industry, emphasizing interoperability, consistency, and quality in multilingual content management. within this structure, sc 3 focuses on standards for computer-assisted processes for managing terminological data. it is responsible for key infrastructural standards such as iso 5078:2025, iso 12620-1:2022, iso 12620-2:2022, iso 30042:2019, and iso16642:2017. in early 2024, iso/tc 37/sc 3 initiated ad hoc group 1 (ahg 1) to explore the growing synergies of tm and ai, ultimately leading to the formal establishment of wg 6 "terminology management and artificial intelligence" in 2025. wg 6 occupies a unique niche within the broader standards ecosystem. while important ai and nlp developments are underway in iso/iec jtc 1/sc 42-especially through its joint working group 5 (jwg 5) on nlp-these initiatives often treat linguistic resources at a high level of abstraction and do not sufficiently address the specificities of controlled vocabularies and terminological data. in contrast, wg 6 focuses specifically on integrating tm with ai systems, with attention to multilingual and domain-specific precision. wg 6's relevance extends beyond iso's internal architecture. the adoption of the european union's artificial intelligence act (ai act) (parliamant and council, 2024) provides an external regulatory catalyst for wg 6's mission. as the ai act introduces legally binding requirements for transparency, traceability, and documented safety in ai systems-especially in high-risk domains such as medicine, law, and finance-terminological precision emerges as a crucial safeguard. misuse or absence of validated domain-specific terminology in such contexts can result in legal liability, safety hazards, and public mistrust. against this backdrop, wg 6 not only contributes to iso's standardization efforts but also functions as a strategic actor helping stakeholders operationalize the ai act's compliance requirements. by aligning semantic resources with ethical, legal, and technical expectations, wg 6 enables ai systems to meet the regulatory demand for explainability, contextual accuracy, and trustworthy outputs. for example, the output created by ai systems needs to reflect best practices of data modelling and conform to relevant data categories (iso 12620-1:2022 and iso 12620-2:2022). ## conclusion and outlook in conclusion, the integration of ai with tm marks a transformative step toward enhancing efficiency, precision, and global communication in both fields. the establishment of iso/tc 37/sc 3/wg 6 represents a pioneering effort to standardize the symbiotic advancements of ai and tm, fostering interoperable, scalable, and ethically sound frameworks. by addressing the challenges of aligning traditional standardization processes with the rapid evolution of ai technologies, wg 6 introduces innovative methodologies that balance stability with adaptability. this strategic approach ensures that emerging standards remain rigorous yet agile, enabling public and private stakeholders to responsibly leverage ai in complex, multilingual knowledge environments. through these efforts, wg 6 is poised to shape future standards that support seamless knowledge exchange and drive ethical, effective applications of ai and tm worldwide.