For the past two years, many conversations about AI in the workplace have revolved around productivity. How do we get more output? How do we automate tasks? How do we reduce cost?
All important questions. But they’re still focused on efficiency while the real performance breakthroughs in organizations don’t come from speed alone. They come from how well teams think through hard problems and decide together.
That’s the work we’ve been focused on for years: helping teams collaborate in ways that are more candid, more inclusive, and ultimately more effective. Long before AI, we were studying how modern teams work differently, from early research on hybrid collaboration to the rise of shared digital documents that let more voices shape the outcome. AI is the next leap in that evolution.
My real “aha” moment with AI didn’t come from watching it write a memo or summarize a report. It came when I saw what it could do for teams. Specifically, how it can radically improve the way humans co-create together and land the plane faster. How to upgrade how groups surface insight, align, and make decisions.
Two recent transformations made this clear to me.
My colleague, Geoff Woods who authored the AI-Driven Leader, was working with the executive and operational leaders of a major global airline during a period of intense operational strain. Weather disruptions, staffing challenges, and cascading delays were putting enormous pressure on cross-functional teams.
Different teams (operations, crew scheduling, customer experience, maintenance) were each seeing part of the system. Everyone had ideas. Everyone had concerns. But those insights lived in separate meetings, inboxes, and chat threads.
So he ran a series of structured, AI-driven collaboration sessions. Here’s what changed:
Instead of relying only on live discussion (where airtime is always uneven), we collected structured input from dozens of leaders and frontline managers, simultaneously:
AI was used to synthesize this input before the group discussion. Not to decide. But to surface patterns.
Within minutes, leaders could see:
Instead of starting the meeting with opinions, we started with shared visibility. And this allowed the team to achieve in two hours what would have taken them six months in the past. Think of how much time this gives back to executives.
As Woods observed, “When you use AI as a thought partner, you are able to unlock the collective intelligence of a team in minutes instead of months. One thing that has surprised me doing this work is how people share far more with AI than they would normally out loud because they do not have to spend the political capital to say what needs to be said. This is truly driving alignment without politics and transforms how organizations achieve speed to value”
By the time the group began their live discussion, they weren’t using half the meeting to “get aligned on what’s going on.” They were debating tradeoffs. Pressure-testing decisions. Making calls.
AI didn’t replace collaboration. It removed the friction that usually keeps teams stuck in information overload and misalignment. That was the first moment I thought: We are looking at a new operating layer for teamwork.
The second breakthrough came in a completely different context: executive team pressure testing at a large retailer navigating AI-driven transformation, supply chain volatility, and margin pressure.
We were helping them run a practice we’ve used with executive teams for years called stress testing. In a traditional Ferrazzi Greenlight stress test, the kind I describe in Never Lead Alone, one leader steps forward and lays out their real work in progress: what they’ve done so far, where they’re stuck, and where they need help. Then the rest of the team leans in.
Their role isn’t to be polite or just say “looks good.” It’s to challenge and support at the same time. They surface risks the leader may be underestimating. They point out missed opportunities or alternative approaches. They offer connections, resources, or hands-on help.
That process is powerful. But it’s still limited by how much the group can absorb in the moment and by what actually gets captured versus what gets lost once the conversation moves on.
So we tried something new.
Before the live session, each executive submitted written responses to prompts like:
AI synthesized the responses and within minutes we could see:
When we walked into the room, the team wasn’t starting from a blank slate. They were starting from a map of their collective thinking.
The real power showed up when we made disagreement visible in a very specific, grounded way. Instead of vague statements like “we’re not aligned,” the patterns looked more like this:
Because this was surfaced as a pattern across the team’s input, it didn’t feel like one person attacking another. It felt like the team looking in a mirror together.
The conversation shifted from: “I disagree with you.” to: “We’re operating from different assumptions here. Let’s slow down and understand why.”
That’s a very different emotional experience. And a much more productive one.
The biggest win wasn’t just better dialogue. It was what the team walked out with.
By the end of the session, they had built a clear three-month turnaround plan that they genuinely stood behind. Not because everyone suddenly thought the same way, but because they understood exactly where they differed and made conscious choices about which risks they were willing to take.
They left with:
That’s the difference between surface alignment and real alignment. That’s when it hit me: AI is a collaboration amplifier.
What struck me in these moments wasn’t that AI was impressive. It was how it changed the experience of working as a team. This is where AI changes the game.
It dramatically broadens reach: you hear from everyone, not just the most vocal. And it speeds up understanding. What used to take days of post-meeting synthesis now happens fast enough that the team walks into the room already seeing a picture of its own thinking.
There’s another, more human difference. When conversations get distilled into tidy meeting notes, you lose texture and candor. The hesitation. The half-formed worry. But when AI works from real input and transcripts of actual conversations, it keeps more of that texture. The uncertainty. The places where people are uneasy but not yet fully articulate.
For the first time, teams can look at a shared, living record of how they actually think, not just what got polished for the slide deck.
Now the questions change:
AI doesn’t replace judgment. It makes the team’s thinking visible fast enough, and honestly enough, that better judgment becomes possible.
That’s when it clicked for me: this isn’t just about smarter tools. It’s about teams working in a fundamentally better way. And most organizations haven’t even started to ask the obvious question yet: How could AI upgrade the way our teams actually collaborate?
You don’t need a massive transformation to begin. Start small and focused.
We are still early in this shift. But I’m convinced of this: The next frontier of AI at work isn’t just smarter tools. It’s smarter teams.
Originally published at Forbes