Most teams are still using AI like duct tape — quick fixes for small tasks, scattered across the team. But the real shift happens when AI stops being a side tool… and starts becoming part of how your team actually works.

That’s exactly what Harvard and P&G set out to test — in one of the largest real-world AI studies to date. 

Their findings? AI didn’t just make people faster — it changed how they worked. Not only did they work faster, but silos broke down and teams created higher-quality ideas with less stress.Let’s break down what they found and how you can put those insights into action.

What Harvard Just Learned from P&G

Harvard Business School recently studied 776 professionals at Procter & Gamble—working across real product development sprints (baby care, grooming, oral care, the works).

Here’s what stood out:

• Individuals using AI (GPT-4) performed just as well as two-person teams without AI
• Teams using AI were far more likely to create top 10% quality work
• AI-enabled teams worked 12–16% faster and produced better outputs
• Silos broke down — R&D got more commercial, commercial teams got more technical
• Energy levels rose — AI supported teams reported more enthusiasm, less frustration

As researcher Ethan Mollick notes, “AI replicated the performance benefits of having a human teammate… Companies that treat AI as a tool miss the bigger opportunity.”

This wasn’t a controlled lab study. These were real teams solving real problems. And the impact wasn’t just faster work—it was better work, done more collaboratively, with less stress.

AI Doesn’t Just Make Work Faster — It Makes Teams Think Differently

In the Harvard study, individuals using AI didn’t just get more done—they thought differently. Commercial folks started suggesting technical ideas, and R&D people came up with better go-to-market concepts.

“With AI, the distinction between commercial and technical specialists disappeared,” the researchers found. AI blurred the lines, helping people break out of their functional silos—something that’s notoriously hard to achieve in traditional team setups.

AI isn’t just a productivity tool—it’s becoming more like a teammate, helping people think better and collaborate across boundaries.

As the report states, “Employees moved beyond routine productivity tasks and were using AI for critical thinking and complex problem solving”

Why Bolt-On AI Isn’t Enough

Using AI to repurpose content, summarise reports and crunch data is fine. But if that’s the extent of your AI use, you’re barely scratching the surface.

The shift happens when AI gets baked into your day-to-day systems. Not as an ad-hoc solution. But as part of the engine that drives your team.

That takes a bit of upfront thinking—but it pays off.

Three Quick Questions Before You Rework Your Workflows

Where’s the friction?

What slows your team down? Repetitive tasks? Endless reviews?

These are signals. Start there.

What are you actually trying to fix?

Be clear on what success looks like. Faster turnaround? Better quality? More consistency?

Is AI the right fix?

Don’t force it. Some issues need clearer hand-offs, effective communication or better processes, not prompts.

A Simple Framework for Building Smarter Workflows

1. Start with obvious wins

Look for the tasks that cause the most friction in your team’s day:

• Time-consuming but low-value repetitive work
• Processes where things regularly get stuck or delayed
• Tasks that create bottlenecks for other team members
• High-volume activities that follow predictable patterns

Ask your team to track where their time goes for a week. The patterns will surprise you—and point directly to your first AI opportunities.

2. Map the whole process

Zoom out to see the complete picture. Where does the task actually start? Where does it end? Who’s involved at each stage?

Find your gaps and opportunities:

• Identify handover points where work often stalls
• Spot repetitive steps that could be automated
• Recognise which parts need human creativity versus AI efficiency
• Determine where technology, automation or AI could solve different problems

3. Connect the dots

The goal isn’t to AI-ify everything — it’s to build a smarter workflow where humans and machines each do what they do best.

Start linking steps together intentionally:

• Human sets direction → AI gathers and organises research
• AI presents findings → Human evaluates and draws insights
• AI drafts → Human edits, refines, and adds nuance
• Human makes key decisions → AI helps scale and implement

When AI supports multiple points in the process — with clear human touchpoints — you get better, faster, and more consistent outcomes.

4. AI Tools – Start with what you’ve already got 

64% of marketers already feel overwhelmed by the abundance of AI tools.

Before adding anything new, explore what’s built-in (or coming soon) to the tools your team already uses. Chances are, your current tech stack is already smarter than you think.

Optimise first. Then fill the gaps, only where it adds tangible value to how you work.

Testing tools is easy, integrating them is the hard part.

5. Build in human guardrails

Set clear checkpoints. Decide where human input matters most: for quality, brand tone, ethics, or just plain good judgement.

And keep it simple. The best clients we work with use a one-pager of do’s and don’ts, or a basic traffic light checklist to guide teams.

Clear rules beat complicated policies — especially when speed is involved.

6. Hone in before you scale up

Don’t try to do it all overnight. Change takes time — and it sticks better when people are part of it.

Start small. Focus on one or two obvious, valuable use cases.

Prove they work. Get feedback. Refine. Then scale what delivers real value.

This isn’t about big-bang transformation — it’s about building momentum with things that matter.

7. Invest in upskilling

Don’t assume people will ‘figure it out’. They won’t.

The best results don’t come from the tech — they come from how people use it. AI isn’t about the tools  – it’s about how teams think, work, and collaborate differently.

That means proper training. Clear workflows. Real examples. Space to experiment.

Invest in your team and you’ll see the benefits fast — in performance, in retention, and in how confidently they adapt to what’s next.

8. Keep evolving

This isn’t a one-and-done AI roadmap — it’s a cycle of continuous improvement.

Your first workflow won’t be your best.

Work in short sprints (3–6 months), then check in:

What’s working? What’s outdated? What’s missing?

Build a cadence of regular reflection and refinement — because the tech will keep moving, and so should your ways of working.

Support the Human Shift — Don’t Just Expect Results

Interestingly, some of the top-performing individuals in the Harvard study felt less confident in their work — even when their output was stronger.

As the researchers noted: “Some AI users performed better but felt less confident.”

That’s a flag for leaders. If you’re rolling out AI across your team, don’t just track outputs.

You need to support the mindset shift too — with feedback, clarity, and shared wins.
The human side of this matters just as much as (if not more than) the tech.

From Faster Tasks to Stronger Teams

The P&G research backs up what we’ve seen first-hand in team after team:
AI isn’t just a productivity boost — it’s an enabler of better teamwork, clearer thinking, and stronger outcomes.

But here’s the thing: that shift doesn’t happen by accident.

• It takes intention.
• Time out to map the real work.
• Clarity on where AI actually fits — and how it helps people think, not just do.

We’ve been working with teams doing exactly this — from strategy and marketing to product and operations. Getting in a room, mapping processes, pressure-testing tools, and building practical ways to embed AI into the day-to-day.

And when that alignment clicks? Performance goes up. Energy goes up. Confidence follows.

As one marketing leader put it at the end of a session with their 80-person team:
“Finally, no more vague theories — just clear next steps to embed AI into workflows for efficiency, value, and impact.”

“Ready to lead this shift in your team?”

We run Team AI Sprint workshops that help you:

• Get everyone on the same page
• Identify high-impact opportunities
• Build working pilots — not just ideas

Book a planning day and we’ll help your team shift from AI bolt-ons… to a smarter, faster way of working together.

Curious how this could work in your team?

We’re happy to share what we’ve done, what’s working inside other teams, and how you could approach it too.