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I heard a phrase during a Rosh Hashanah sermon that sounded surprisingly familiar.

The Talmud teaches, "O chevruta o mituta," roughly, "companionship or death."

The phrase comes from a story nearly 1,700 years old, but over time it has also become associated with chavruta, the Jewish tradition of studying a text with a partner. Two people sit together. They read. They question. They interpret. They disagree. And, through that exchange, they often discover meaning that neither would have reached alone.

That sounds remarkably contemporary.

There is also an important distinction within Jewish thought between studying and learning. We can study to acquire information, facts, interpretations, knowledge that exists outside ourselves. But learning, particularly in the Jewish tradition, can mean something more. It is a lifelong practice intended not simply to increase what we know, but to influence who we become and deepen our relationship with God, our community, and one another.

In other words, the objective isn't simply to understand the text. The experience of learning should have the potential to change the learner.

We can certainly read and study by ourselves. But something different happens when we reflect on what we've read with another person. They notice something we missed. They interpret a character differently. They challenge an assumption. Their own experience causes them to hear the same words differently.

The text hasn't changed. Our understanding of it has. And sometimes, as a result, we change too.

This ancient practice is remarkably consistent with what ITT Media founder Ginger Malin has explored in her own research and work with groups: reading can be an individual experience, but reflection and meaning-making become something different when they are shared.

And the idea extends well beyond religious study.

Think about the issues organizations struggle with every day: communication, leadership, change, trust, resilience, relationships. These aren't simply subjects to be taught. They're human experiences. A story about change can lead two colleagues to very different conclusions about how people respond to uncertainty. A story about communication can expose assumptions neither realized they were making.

The purpose isn't necessarily to agree. In fact, disagreement may be part of the learning. The objective isn't simply to finish a story knowing something we didn't know before. It's to leave the conversation thinking, seeing, or perhaps acting differently.

For centuries, people have sat across from one another with a text between them and discovered that reading something together can become a way of understanding the text, one another, and sometimes themselves.

Maybe the technology of meaningful conversation isn't particularly new after all.

We built ITT around a simple belief: a story can open something in a person that a slide deck never will. The reflection that follows is personal. The conversation is human. The decision about what to carry forward belongs to each participant. So when people ask me where AI fits into all of this, my answer starts there, with what we refuse to let it touch.

The story is human. The reflection is human. The conversation is human. The choice about what matters is human. AI works behind the scenes, and only where it helps people and organizations make more of what they've already created.

Consider what happens when someone finishes an ITT Experience. They've sat with a story, answered a few reflection prompts in their own words, and chosen something to carry forward. We can use AI to bring those responses together into a concise personal summary, not to interpret the person, not to tell them what to think, and certainly not to diagnose them. The participant creates the meaning. AI simply reflects it back in a way that's easier to revisit, keep, and return to.

Now imagine that same experience across an annual conference: hundreds of participants, dozens of group conversations, hundreds of commitments to carry forward, and weeks later, follow-up reports on what actually happened. Without AI, making sense of that volume of open-ended response would take enormous staff time. Important patterns would be missed. And too often, rich answers would get reduced to simple counts simply because counts are easier to analyze than language.

That's where AI changes what's possible for us. It helps us synthesize large volumes of participant-created response and surface recurring patterns: what captured people's attention, what they kept returning to, what they realized, why the conversations mattered, what they chose to carry forward, and, later, what they reported happening.

We use it to create, on demand, an end-to-end loop: from the story a person reads, to the reflection they write, to the conversation their group has, to the intention they set, to the follow-up they complete weeks later, and finally to a report an organizer can actually use. Each step is created by people. AI helps the steps connect into something a whole organization can learn from.

Organizations already collect enormous amounts of data — surveys, assessments, attendance, performance measures. AI gives us a way to work with a different kind of information: the words people use when they describe what they noticed, the ideas that stayed with them, the questions they're still thinking about, the actions they chose for themselves. At scale, those responses become a richer picture of what's happening across an experience.

The boundaries matter to us. AI doesn't decide what a participant should believe. It doesn't replace reflection or conversation. It doesn't determine whether someone succeeded or failed. It doesn't manufacture consensus or turn individual responses into certainty about an entire organization. The original, participant-created response is always the foundation. AI supports interpretation and synthesis within defined limits, to help people see more clearly, not to overstate what the information can prove.

We believe the future isn't human experience or artificial intelligence. It's learning to use AI in ways that make human experiences more valuable. Stories create recognition. Reflection creates understanding. Conversation creates perspective. People decide what matters. AI helps make sense of what emerges.

Keep the meaning human. That's the principle. AI does the rest, where it adds real value.

He was called stupid by his family. She studied by candlelight while ducking from gunfire in her home country. He was once forced to eat ketchup on his hot dog.

What?

That was my recent experience sitting through an executive training session intended to build trust. Each executive was asked to share deeply personal experiences from their background. Tears flowed. Hugs ensued. But when it was over, I wasn't sure what we had actually accomplished.

To me, something felt wrong about requiring personal disclosure in the name of building trust. Sitting among colleagues who had experienced childhood trauma and profound hardship, I found myself searching my own history for something suitably revealing. I offered that my childhood had included meeting a serial killer. (Yes, really.)

But does connection require confession?

What if, instead, we began with a purposeful short story and reflected together on experiences and challenges we've faced—on our own terms, and without being asked to tell our life stories?

A good story can open a conversation about communication, trust, resilience, teamwork, loss, or perseverance. We can disagree about what it means. We can recognize ourselves in a character. We can share something personal—or simply listen.

Trust can grow through honest conversation and shared reflection without requiring people to expose the most difficult parts of their histories in the name of transparency.

Sometimes the story can do the opening for us.

It turned out that Susan used some of her commission checks to buy food for vulnerable neighbors. Angela spent weekends crossing the state to drive her boys to baseball tournaments. Deepak moved across the country to help care for his aging parents.

How did I know?

Because I asked.

Our company was predominantly remote, and in those few sometimes-awkward minutes at the beginning of calls, I tried to check in. Over time, those conversations told me far more about the people I worked with than any formal team-building exercise ever did.

Like many remote organizations, we tried the usual things: gift cards for overtime, online parties, virtual gifting (woo hoo), and exercises designed to tell us our respective personality colors.

They had their place. But they weren't the same as knowing one another.

What if, once a month, we reserved part of a meeting to read a carefully selected short story and make meaning from it together?

A story might lead us into conversations about loss, communication, ambition, resilience, success, failure, or missed opportunities. Nobody has to disclose something intensely personal. The story gives us common ground, and each person decides how far onto that ground they want to walk.

We learn from one another. We discover perspectives we didn't know were there. And, over time, we begin to understand the people behind the screens.

For teams whose members may see one another in person only once a year, that matters.

Strong teams aren't built because everyone knows everyone else's personality color. They're built when people know something about the people beside them—and have learned how to listen to one another.

Sometimes all it takes to start is a good story.

It was icy outside but warm in the room at a public safety conference in Niagara, Canada.

The speaker—a former dispatcher who had become an executive—spoke openly about her struggles with anxiety and mental health despite professional success and a wonderful family. The audience was moved. Several people joined the conversation.

What made the session powerful wasn't that she had all the answers. She didn't pretend to. Instead, her story created an opportunity for people in the room to recognize something in themselves and one another—to find some common humanity in shared experience.

Then the conference ended.

That's the problem with many of these extraordinary conversations: they're extraordinary. We experience them at a conference, retreat, or annual meeting and then return to work.

How do we create opportunities for conversations like these more regularly?

A story group offers one way. Read something meaningful together. Reflect on it. Talk about the issues it raises and the experiences it brings to mind. Some people may want to share deeply. Others may contribute an observation. And someone else may simply want to listen.

Then take something with you.

We call it Carry It Forward: one thought, behavior, conversation, or action inspired by the experience that a participant can try afterward.

A great speaker can move us to think differently for an hour. A continuing practice of reading, reflecting, and talking together can do something more: help us understand ourselves and one another over time.

Stories give us a place to begin.