This article was written by Keith Ferrazzi and Henry Finkelstein, a Stanford GSB Sloan Fellow who works at the intersection of Transformational AI and Go To Market (GTM). Finkelstein works with senior leadership to implement agentic strategies for marketing, sales, customer success, and operations. He currently manages a hybrid team of 86 humans and AI agents that earn millions of incremental revenue and cost savings. Below, they share how AI empowers hybrid teamship.
I’ve spent the past decade inside the guts of elite teams, from Fortune 100 giants to scrappy startups. Here’s the truth: teamship still rules. But the rules are changing. Co-elevation, my term for teammates lifting each other higher, is still the engine of breakthrough performance. But now we’re building that engine with AI.
Recently, I hosted a dinner in New York City for 70 of the top CIO and CHRO executives from Fortune 100 companies. The question that dominated our conversation wasn’t whether to adopt AI agents. It was how to integrate them into teams without losing the human connection that drives innovation. Over the past year, working with companies from coaching startups at a venture capital firm to partnering with the executive team at Anthropic, I’ve discovered that AI isn’t replacing human teamship. It’s amplifying it.
Think of AI as a force multiplier for human intuition, creativity, and capacity. The challenge: we can’t treat AI agents like human teammates. They don’t need recognition, career growth, or emotional support. Instead, they show up in five specific roles that make hybrid teams more effective than either humans or AI could achieve alone.
Here is how AI empowers hybrid teamship:
The Facilitator
Your meetings are too long. Your decisions are too slow. AI fixes that. AI excels at orchestrating collaboration in ways that would overwhelm even the most organized leader. It drafts agendas by synthesizing async inputs, prompts conversations at the right cadence, and flags disconnection before they become crises. In our diversity and inclusion work with executive teams, we’ve seen how AI can quietly monitor whose voices are heard, then prompt async input so all perspectives surface. It removes the “remembering to be inclusive” burden, letting humans focus on the relational work that builds trust.
The Reviewer
Think of this role as your continuous improvement engine running 24/7. AI watches meeting transcripts, tracks project management tools, and monitors relationship quality scores. When I work with startups at venture capital firms, this reviewer function often becomes the first integration point because the ROI is immediate.
At household name unicorns, we’ve explored how AI manages relationships across five concentric circles: from exec team to clients to entrepreneurs. AI tracks hundreds of connections systematically, delivering insights like “Your client relationships are averaging 2.3, down from 3.1 last quarter.” It surfaces patterns before they become crises. The alignment systems we’ve built, including accountability grids and commitment tracking, benefit from this longitudinal perspective.
Stop guessing where you’re off-track. Start letting AI show you.
The Coach
Coaching turns out to be a perfect AI use case. AI operates at multiple levels: aggregating 360 feedback, facilitating empathetic conversations when properly designed, organizing input from many peers into actionable insights, and briefing managers with synthesized information.
For team resilience, AI prompts systematic check-ins and identifies patterns over time, so no one falls through the cracks. Humans still do the emotional lifting. However, now they’ve got backup.
The candor work shifts in interesting ways. Our “Power of Three” practice becomes “Power of 3+1” in hybrid teams: three humans plus one AI agent explicitly trained for candor. You have to actively prompt out sycophancy to get a genuine challenge. But once you do, AI identifies “what’s not being said” in ways that ensure peers have access to the best opinions, human and AI alike.
The Cheerleader
Seventy-nine percent of people who leave jobs cite lack of recognition as a key factor. AI doesn’t need celebration itself. Frankly, celebrating AI is a waste of tokens, energy, and water. But AI elevates human recognition in powerful ways. It tracks who hasn’t been appreciated, identifies under-voiced contributions from transcripts, and prompts managers to surface celebrations at the right moment.
AI can prompt gratitude circles and peer celebrations with predetermined regularity, surfacing specific appreciation opportunities that would otherwise stay invisible. The “remembering to celebrate” problem disappears, freeing humans for genuine appreciation.
The Contributor
In rigorous workflows, AI truly shines. Our agile methodology becomes dramatically more powerful with AI contribution. AI handles task decomposition, creates estimates, conducts stress-test reviews before human meetings, and tracks progress to flag delays before they cascade.
One startup I’m coaching saw sprint planning time drop from four hours to fifteen minutes while estimate accuracy improved. Caution: Avoid “falling asleep at the wheel” through over-reliance on AI thinking. AI should remove the friction that prevents creative and strategic thinking, not replace it.
Building your ecosystem
Here’s what the top 70 CIOs and CHROs told me in New York: the AI moonshot is a myth. You win by deploying sniper-focused agents, not Swiss Army knives. You can’t build one super-agent that does everything. The teams seeing real results build individual agents that do one thing extremely well, then create an orchestrator agent that knows when to invoke specific sub-agents.
Yes, there’s a learning curve utilizing AI to empower teamship. Yes, there is fear of displaced jobs at every level. Many executives worry about AI’s impact on company culture. Those fears are understandable. But what we’re seeing in practice tells a different story: AI serves as a force multiplier for human capacity, not a replacement for creativity and intuition.
Teamship still matters. The “what” and “why” remain, but the how is evolving as teams blend new tools with human strengths. The teams that lean into this modern way of working are moving faster, making better decisions, and unlocking levels of performance they simply couldn’t reach before.
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Keith Ferrazzi
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