Imagine a new hire, fresh from college, top talent recruited for a high-performing team. We can call her Whitney.

Whitney is six months into her role. She is bright, capable, and resourceful. When she gets stuck, she opens an AI tool.

She asks it to explain the new market she is working in. She asks it to draft an email to a senior stakeholder. She asks it to summarize notes from a meeting she barely understood. It does all these things, well and quickly.

In many ways, Whitney is moving faster than she could have a few years ago. She is not waiting for someone to teach her the basics or wondering where to start.

Her company sees this as a win. They are so pleased with the efficiencies of AI that, instead of investing in mentoring, they have invested in AI coaching as their primary development tool. The message, though no one says it quite this plainly, is: Why build mentoring when people can get answers instantly?

For Whitney, something is missing.

AI can’t identify which stakeholder really needs to be consulted before the proposal goes forward. AI can’t help her understand why one very influential leader nodded enthusiastically in the meeting but sent a skeptical email afterward. It can’t help her discern whether her colleague’s stony reaction is par for the course or a sign of misalignment. It can’t teach her, in context, how to raise a concern without sounding difficult, or how to tell whether silence in the room means agreement, resistance, or fatigue.

She feels disconnected from context and isolated by her independence. AI cannot help her with that.

Whitney’s manager holds her accountable for performance: the report, the deck, the deadline, the client response. But no one is holding her accountable for her growth. No one is asking what she is learning, where she is stretching, what patterns she is noticing, or what kind of judgment she is developing.

Whitney’s work looks good enough that everyone assumes she is fine.

She isn’t fine. Her skills are underutilized. She is producing without developing. She is answering questions without building confidence. She is surrounded by tools and still has nowhere to turn.

Eventually, Whitney realizes she needs more than answers. She needs people.

She reaches out to someone in another department whose judgment she admires. Not with a grand request to “be my mentor forever,” but with a specific invitation: “I’m trying to get better at reading stakeholder dynamics. Would you be willing to talk with me once a month for the next few months?”

That relationship changes something.

Her mentor does not simply give her advice. She provides context. She helps Whitney see the organization more clearly. She challenges Whitney’s assumptions, shares her own mistakes, and points out patterns Whitney had missed.

Over time, Whitney begins to use AI differently too.

Instead of asking AI for the answer, she asks it to help her prepare: What questions should I bring? What assumptions might I be making? How can I reflect on what I heard? Where do I need more context from a human being?

AI becomes a tool for preparation and reflection. The relationship becomes the place where judgment is built.

This is where the question gets real: If AI can teach people almost anything, what is the role of mentoring now?

The answer is that mentoring was never just about teaching.

At its best, mentoring is about development. It is about connection, reciprocal learning, shared sense-making, feedback, encouragement, perspective, accountability, and access. It is not merely the transfer of knowledge. It is a relationship that helps people interpret experience, build judgment, navigate complexity, and become more capable than they would be on their own.

In an AI-shaped workplace, that role becomes more important, not less.

This relationship is just a starting point for Whitney. She does not need one all-knowing mentor to hand her every answer. She needs a developmental network: a mentor who can help her make sense of experience, a connector who can help her understand the unwritten rules, a challenger who will sharpen her thinking, a sponsor who will say her name in rooms she is not yet in, a peer who will compare notes honestly, and a manager who sees development as more than task completion.

Organizations need this too. They cannot simply give people AI tools and assume growth will follow. Output is not the same as development. Efficiency is not the same as judgment. Access to information is not the same as access to wisdom.

AI does not replace the human relationships that help us make meaning, build courage, exercise judgment, and contribute fully.

AI hasn’t made mentoring obsolete. It has made human intelligence and connection even more essential to ensuring talent is fully realized.

For more information and resources, visit:  www.centerformentoring.com or www.lisazfain.com