According to Inc, executives from 70 Fortune 100 companies are now focused on integrating AI agents into teams rather than debating whether to adopt them. Henry Finkelstein, who manages a hybrid team of 86 humans and AI agents generating millions in incremental revenue, identifies five specific roles where AI excels: orchestrating collaboration, continuous improvement, coaching with candor, elevating recognition, and rigorous workflow management. One coached startup saw sprint planning time drop from four hours to fifteen minutes with improved estimate accuracy. The approach emphasizes building specialized agents that do one thing well rather than Swiss Army knife solutions. Seventy-nine percent of people leaving jobs cite lack of recognition as a key factor, which AI addresses by tracking appreciation patterns and prompting genuine celebrations.
The AI orchestrator advantage
Here’s the thing about meetings and decisions – they’re fundamentally broken in most organizations. AI isn’t just making them slightly better; it’s completely reengineering how collaboration happens. The examples of AI drafting agendas from async inputs and monitoring whose voices aren’t being heard? That’s not incremental improvement – that’s changing the game entirely. I’ve sat through enough poorly run meetings to know that the “remembering to be inclusive” burden is real, and it’s exhausting for human leaders. But is there a risk we become too dependent on AI for basic social dynamics? Probably. The key insight is that AI handles the systematic tracking while humans focus on relational work that builds trust. That’s the sweet spot.
Why specialized agents win
The Swiss Army knife approach to AI is basically doomed to fail. Every company I talk with wants that one magical AI that does everything, but the reality is much more practical. Building individual agents that excel at specific tasks – then creating an orchestrator that knows when to deploy them – that’s where the real power lies. Think about it: would you rather have one mediocre generalist or a team of world-class specialists? The numbers don’t lie – that startup cutting sprint planning from four hours to fifteen minutes while improving accuracy is staggering. But here’s my concern: are we just creating another layer of complexity that requires its own management? And what happens when these specialized agents need to talk to each other?
The human connection paradox
Seventy-nine percent of people leave jobs due to lack of recognition – that number from O.C. Tanner’s research should terrify every manager. But here’s where AI gets really interesting – it doesn’t need recognition itself, but it can systematically ensure humans get the appreciation they need. The “remembering to celebrate” problem disappearing? That’s huge. Most managers I know are so buried in work that genuine recognition falls through the cracks. Now imagine AI tracking who hasn’t been appreciated and prompting gratitude circles at the right moments. It’s almost ironic that we’re using machines to become more human with each other.
The implementation reality check
Let’s be honest – there’s a massive gap between this visionary thinking and what most companies are actually doing. The learning curve is real, and the fear of job displacement at every level isn’t going away. But the hybrid approach Finkelstein describes – where AI handles the systematic, repetitive work while humans focus on creativity and intuition – that’s the sustainable path forward. The “Power of 3+1” concept with AI trained for candor is particularly fascinating. Getting genuine challenge in organizations is brutally hard, and if AI can help surface what’s not being said without the political consequences? That’s transformative. The companies that figure this out first will have a staggering advantage, while those stuck in either pure-human or pure-AI thinking will get left behind.
