Ever wonder if AI could actually function like a team member rather than just another tool?

A fascinating new study out of Harvard has some interesting insights.

Researchers at Harvard Business School just released findings from a field experiment with 776 Procter & Gamble professionals working on real product innovation challenges.

What they discovered might change how you think about implementing AI in your organization.

#1. Juniors Performing Like Seniors?
It's Happening.

The most eye-opening finding for me: less-experienced professionals using AI performed nearly as well as veteran teams working without it.

Think about that for a second.

How many times have you thought, "This project really needs our senior people, but they're already overloaded"?

Quick Win: Identify one knowledge-intensive process where experience creates bottlenecks.

Give your less-experienced team members AI access and clear guidance, then measure the results.

Several leaders I've spoken with started with report writing or data analysis, both showed immediate gains.

#2. Silos Breaking Down Without Forced Team Building

Here's something remarkable: Without AI, technical folks created technical solutions and commercial folks created commercial solutions (shocker, I know).

But with AI?

Both groups suddenly produced more balanced proposals that considered multiple perspectives.

No mandatory cross-functional workshops required (to start anyways).

Try This Now: Before your next siloed project, give team members access to AI tools with prompts that specifically ask for cross-functional perspectives.

"How would marketing/engineering/operations approach this problem?" can yield surprising insights without adding headcount.

#3. The Team Size Question

This finding has huge implications for resource allocation:

• Individuals with AI matched the performance of two-person teams

• BUT teams with AI were 3x more likely to produce truly exceptional solutions

So which approach is right for your projects?

Smart Strategy: Map your projects on a simple 2x2 grid: routine vs. innovative on one axis, and acceptable vs. exceptional required outcomes on the other.

Use individuals+AI for routine projects where consistent quality is sufficient.

Reserve teams+AI for innovation projects where breakthrough results justify the investment.

#4. The Surprising Emotional Upside

Against conventional wisdom that technology creates workplace stress, participants using AI reported:

• More positive emotions (excitement, enthusiasm)

• Fewer negative emotions (anxiety, frustration)

Who'd have thought that AI would make people feel better about their work?

Leadership Opportunity: When introducing AI tools, focus first on positive user experiences rather than immediate productivity gains.

The research suggests emotional acceptance drives sustained adoption. Create space for experimentation and celebrate early wins, however small.

Where to Start Tomorrow

Don't overthink this.

Pick one area where:

1. The stakes aren't too high

2. A process relies heavily on specialized knowledge

3. You have curious team members willing to experiment

Give them appropriate AI tools, clear guidance, and permission to learn through trial and error.

Then just watch what happens.

The Bottom Line

The researchers call AI a "cybernetic teammate", which sounds like sci-fi but captures something important.

This isn't just another productivity tool.

It's potentially reshaping how organizations structure teams, distribute expertise, and approach collaboration itself.

The question isn't whether AI will change how your teams work, it's whether you'll shape that change intentionally or react to it after the fact.

What's your organization's experience been with AI and collaboration?

I'd love to hear your thoughts.

Keep Innovating,

Ben S. Cooper

P.S. The full study reveals that teams with AI completed their tasks in about 13% less time while producing more comprehensive solutions.

Imagine what your organization could do with that kind of efficiency gain across multiple teams.