How does your organization balance using AI to make entry-level jobs more efficient with the need to maintain a robust talent pipeline? Are there specific roles you're purposely shielding from automation to retain pathways for employee development?

Understanding that killing the entry level roles will back fire in the long run we enable our interns and young entrances to use AI to augment their work, not replace it.

I don’t believe we need to balance AI efficiency with maintaining a talent pipeline in the traditional sense. The nature of work is evolving — and so too must the pipeline. As AI becomes more integrated into entry-level roles, the skills required to succeed will shift, and academia and workforce development programs will adapt accordingly to remain relevant.
Rather than shielding roles from automation, we should embrace it across the board. Every role has the potential to benefit from AI augmentation. What becomes increasingly valuable is the human touch — not as a fallback, but as a critical layer of verification, judgment, and creativity. Humans will orchestrate digital agents much like we coordinate with coworkers today.
That said, foundational training remains essential. New employees and contractors must be equipped with solid domain knowledge and to collaborate effectively with digital agents. This includes shared vernacular, process understanding, and the ability to interpret and guide AI outputs. The goal isn’t to preserve outdated pathways — it’s to build new ones that reflect the reality of a digitally-augmented workplace.