Gartner’s recent survey of nearly 500 chief data and analytics officers (CDAOs) highlights a shortage of skilled staffing for Generative AI (GenAI). Over half of the CDAOs are at least piloting GenAI; it’s accordingly crucial to hire new talent.

Knowledge representation is increasingly important for GenAI. Ontologies and knowledge graphs are particularly vital given how they embed formal relationships across data, helping the organization make better decisions and understand business processes.

I cannot help but worry, however, that the market demand for knowledge representation will continue to outstrip the supply, so that companies will do what they’ve done in the past: hire just anyone who claims to understand knowledge graphs. The concern here is that hiring unqualified individuals will lead to unsatisfying deliverables, which will in turn lead to complaints that knowledge representation is the problem, rather than the lack of talent.

We are training new ontologists here at the University at Buffalo, as quickly as we can. I hope those sympathetic to the promise of semantic interoperability are doing the same.