If AI can teach people almost anything, what is the role of mentoring now?

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

AI and mentoring

Are Books Dead? Or Are We (Finally) Rethinking How Humans Learn?

When I asked Ori Brafman, professor at UC Berkeley’s Haas School of Business, what questions he had been wrestling with lately, he wondered aloud about the future of books in a world where learning is increasingly interactive and relational.

The inquiry stopped me cold. Because I love books.

Fiction and nonfiction. Memoir, business, romance, historical novels. I surround myself with them. I read them, recommend them, and keep stacks within reach. Even unread books bring me comfort. They represent possibility and ideas waiting to be explored.

It prompted my reflection on a deeper question: Does the architecture of learning that books represent still match how people learn today?

Many of the learning formats we rely on were designed for a different era. Long readings, lectures, and traditional training modules often fail to engage modern learners. This shows up in classrooms and workplaces alike. Organizations invest heavily in training content, yet participation and retention remain stubbornly low.

Shrinking attention spans and digital distraction are common explanations. Those factors play a role. But they miss the deeper issue. The challenge is how we design learning.

Many learning systems still prioritize the transfer of information. The modern workplace increasingly demands something more: discernment, perspective, and judgment.

The challenge is no longer access to knowledge. It is making sense of it. When learning systems fail to support that work, organizations face a costly consequence: human potential that remains underdeveloped and underutilized.

For much of the last century, formal learning followed a familiar pattern: read the material, listen to the lecture, absorb the framework. The learner sits outside the knowledge, looking in.

Historically, humans learned differently. Learning happened through apprenticeship, storytelling, observation, experimentation, and conversation. Knowledge was experienced in context rather than delivered at a distance.

Learning was immersive.

This insight aligns with decades of research on adult learning. Malcolm Knowles argued that adults learn most effectively when learning is self-directed, relevant to real problems, and immediately applicable (Knowles, Holton & Swanson, 2015). David Kolb’s experiential learning model similarly emphasizes cycles of experience, reflection, and experimentation (Kolb, 1984).

Yet many modern learning environments continue to rely on lectures, readings, and static content. Traditional formats often conflict with what research shows about how adults learn.

Relationships create immersion every day.

In my work helping organizations design mentoring and learning ecosystems, mentoring is frequently misunderstood as advice or knowledge transfer. A more experienced professional shares what they know, and the mentee applies it.

But mentoring at its best does something deeper. It allows people to step inside another person’s thinking, experience, and judgment.

Knowledge transfer builds knowledge. Development builds discernment.

That distinction matters more than ever because information is abundant. Books, courses, podcasts, and digital tools can deliver knowledge instantly.

The harder task is interpretation.

The current debate about artificial intelligence often centers on whether technology weakens our ability to think. A more productive question is how these tools might deepen thinking. AI can surface perspectives, questions, and patterns we might not encounter on our own. The interpretation and judgment that follow remain fundamentally human work.

That work happens best through conversation and connection.

Generational shifts make this even more visible. Younger professionals have grown up in environments shaped by interaction, rapid feedback, and social learning. Dialogue and collaboration are natural modes of learning.

Yet many organizations still rely on static learning models designed for a different era.
If learning is going to engage people, the answer is not simply more content.

The answer is better-designed learning ecosystems.

In those ecosystems, content provides ideas. Technology expands exploration. Relationships create the space where ideas become insight.

Developmental networks – the constellation of people who challenge us, support us, and expand our perspective – become the engine of learning.

Here is where I’ve landed on Ori’s provocative question:

  • Books still matter – but learning systems built around content alone cannot produce the kind of growth and transformation organizations need.
  • The future of learning must be more immersive, more relational, and more intentionally designed.
  • In our modern era, books spark ideas. They fuel curiosity. They introduce us to new ways of seeing the world.

Learning takes hold somewhere else.

It happens in relationships. Through action. Through the messy work of testing ideas, applying them, and rolling up our sleeves to engage with them in practice.
That is where discernment develops and where growth happens.

That’s why the future of learning will belong to organizations that intentionally design environments where people can engage with ideas together.

 

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

Civility