Criticism, Credibility and AI in the Workplace

03-26-2026

If he ever wrote a book, Dan Elmhurst told the Daniels School’s Executive Forum recently, it would be about the difference between “feedback” and criticism. Elmhurst describes feedback as low‑stakes, tactical input: things like “show up to meetings on time” or “your summary minutes are a little too wordy.” These are concrete, easy‑to‑fix adjustments that don’t usually touch a person’s professional identity.

Criticism, in contrast, is what people are afraid to tell someone else because it carries an emotional charge and often hits at how a person sees themself. Elmhurst says that criticism has three key traits:

• It’s emotionally loaded for both giver and receiver.
• People often avoid giving it, even when offering it would help a person.
• It usually contains a core of truth you ignore at your own peril.

As an example, Elmhurst recalls a senior Intel fellow telling him, “You are too strategic. You are not in the details,” a message he heard as an engineer’s worst insult. That criticism didn’t stay private; it was repeated to his boss and his boss’s peers, directly affecting how others viewed his readiness for promotion. But he learned to welcome criticism as a result.

By deliberately inviting criticism and filtering out the noise, he can change his behavior based on the truth inside it. And, he learned, that stance transformed a harsh critic into one of his strongest advocates.

Learning to take feedback and criticism are just one of several lessons Elmhurst shared with emerging professionals about moving beyond a role as an individual contributor during the Forum. Not only did he encourage the audience to build a strong core skill set and excel in their role, but also to take opportunities to learn. Of particular salience in the moment was his advice regarding AI and being perceived as a fraud for using it.

AI, authenticity, and the “fraud” fear

Elmhurst tackled his fear that using AI tools makes professionals look like imposters. A year or two ago, he notes, leaders might see something polished and say, “That looks like AI helped you,” and “ding you for that.” Now he expects the perception to flip: using AI will be seen as smart because it builds a foundation faster and prevents professionals from wasting time.

For him, the real risk is not that AI use will make a person seem fake today, but that not using it will make them look like an imposter in the future:

• Credibility is “built on your skill,” and in this generation, one core skill is knowing how to wield AI as a productivity tool.
• He urges students to treat AI like a craftsman’s tool — important enough to buy their own subscription and practice with every day.
• In his own work, he now does in a day the competitive research that used to take a month by pairing his domain expertise with tools like ChatGPT.

The fraud line, in Elmhurst’s view, isn’t “you used AI, so you’re a fake.” It’s “you used AI and tried to pass off its output as your own thinking.” He insists professionals must always “add your own intelligence on top of it,” use AI as an accelerant rather than the answer, and rigorously fact‑check anything that shows up as a number because data errors destroy credibility fastest.

Listen to the full talk here: