Ontology development is a complex sociotechnological process involving consensus-generation among experts, deep subject matter research, logical representation and reasoning, and rigorous application of engineering principles. It is also highly resource-intensive. So there is naturally interest in applying a variety of AI techniques, from good-old-fashioned AI symbolic methods, to newer large language model (LLM) approaches. After the release of ChatGPT there was an explosion of activity applying LLMs for ontology generation tasks, but these did not translate into meaningful applications in complex domains like the life sciences and biomedicine. This can be explained by a mixture of a lack of trust in generative AI coupled with a misalignment of requirements and capabilities. A newer paradigm of multi-agentic AI offers a more powerful approach that equips the AI with a team of specialists cooperating and using tools to solve complex tasks. For ontology development, these tools include reasoners, literature search tools, ontology exploration and engineering tools, and the ability to communicate through social coding mechanisms such as GitHub. In this talk I will describe experiences in deploying agentic AI systems at scale over a variety of ontology and semantic artefact projects, outlining opportunities and challenges in building, evaluating, and socially integrating agents into ontology development, with a perspective on the future of ontology development in the face of rapid AI developments. https://cbp1012.github.io/JOWO-ONTOLLM/