If AI does the entry-level work, who becomes the next expert?

About the episode

AI can make people productive before it makes them experienced. That creates a new problem for leaders: if junior employees stop doing the work that once taught judgment, where will the next generation of experts come from?

Elizabeth Maxson, CMO of Contentful, joins Rachel Truair to explore what her team calls “judgment debt”—the long-term cost of automating away the experiences people use to build instinct, context and expertise. They discuss why Elizabeth still requires humans to write the brief, why knowing when AI is wrong may become more valuable than knowing how to use it, and why she believes leaders need a “human on the hook,” not simply a human in the loop.

The conversation ultimately asks whether businesses can capture AI’s efficiency without accidentally dismantling the apprenticeship system that creates their future leaders.

From the conversation

• Why automating entry-level work could create a long-term shortage of judgment, skills and institutional knowledge, even if nothing appears broken today.
• How Elizabeth separates work AI should accelerate, such as analyzing large data sets and creating a “crappy first draft,” from the strategy, curiosity and accountability she believes should remain human.
• Why Contentful still requires humans to build detailed briefs, and why Elizabeth believes some organizations may need to “go slow to go fast” instead of treating speed as the objective.
• What “judgment debt” looks like when people rely on AI before they have enough experience to recognize when its answers are wrong, and why mentorship and human relationships still matter.
• How hiring may change when candidates use AI to produce excellent work: Elizabeth argues leaders should test the thinking, response to feedback and decision-making behind the output rather than simply banning the technology.