The Digital Transformation Playbook
Kieran Gilmurray is a globally recognised authority on Artificial Intelligence, intelligent automation, data analytics, agentic AI, leadership development and digital transformation.
He has authored four influential books and hundreds of articles that have shaped industry perspectives on digital transformation, data analytics, intelligent automation, agentic AI, leadership and artificial intelligence.
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The Digital Transformation Playbook
My AI Buddy Made Me Better Than Your Entire Team
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The boundary between AI as a tool and AI as a teammate is dissolving before our eyes. Drawing from ground breaking research with 776 Procter & Gamble professionals working on actual product innovation challenges, we unpack how generative AI is fundamentally reshaping workplace collaboration, expertise sharing, and team performance.
TLDR:
- AI-assisted individuals perform as well as traditional two-person teams without AI
- Teams using AI create higher-quality solutions and work 12.7% faster
- AI breaks down knowledge silos between different expertise domains
- Less experienced employees with AI can perform at expert levels
- People working with AI report more positive emotions and less anxiety
- AI serves as more than a writing tool—it's a true thought partner
- Using AI creates more balanced ideas combining both technical and commercial perspectives
- Teams with AI are 9.2 percentage points more likely to develop top-tier solutions
- Despite creating better work, AI users feel less confident about their solutions
- The "cybernetic teammate" concept captures how AI is becoming a collaborative partner rather than just a tool
The findings are striking. Individuals with AI support performed at the same level as traditional two-person teams without AI. Teams augmented with AI not only produced higher quality solutions but did so 12.7% faster while exploring more dimensions of each problem. Most surprisingly, AI demolished the traditional knowledge silos between technical and commercial domains, creating more balanced and integrated solutions where expertise flowed freely.
Perhaps most transformative was the democratizing effect—less experienced employees using AI performed at expert levels, effectively leveling the playing field across experience levels. And contrary to concerns about cold machine interactions, people working with AI reported higher levels of enthusiasm and lower anxiety than conventional teams.
This isn't just about productivity gains. We're witnessing the emergence of what researchers call the "cybernetic teammate"—a collaborative partnership where AI doesn't replace human judgment but expands our creative and analytical capacities. As one person with AI can now match a team's output, organizations may need to reconsider traditional team structures, expertise valuation, and collaboration frameworks.
Have you experienced working with AI as a teammate rather than just a tool? How might this reshape your approach to solving complex problems? Join the conversation about how "cybernetic teamwork" is redefining what's possible in workplace collaboration.
AI is transforming teamwork from a tool into a genuine teammate.
Reading the full paper to understand how these insights might apply to you and your work.
HBR Working paper, "The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise,"
Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5188231
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Introduction to AI and Teamwork
Speaker 1Teamwork right. It's how we've always gotten things done solved problems.
Speaker 2Yeah.
Speaker 1From small groups to like huge collaborations Totally. But with AI changing so fast, you know, it kind of makes you wonder if this technology can really be a teammate.
Speaker 2Oh, absolutely.
Speaker 1Or is it always just going to be a tool? You know what I mean.
Speaker 2Like yeah, it's a fundamental question.
Speaker 1It is For you, the learner, we're diving into this headfirst today.
Speaker 2Exactly. We know you want to get to the heart of the matter quickly.
Speaker 1Right to the good stuff.
Speaker 2So this research is perfect for that. It tackles this question directly.
Speaker 1Well, sure, we're looking at a paper called get this the Cybernetic Teammate. Ooh.
Speaker 2I like that.
Speaker 1It's about how generative AI reshapes teamwork and expertise.
Speaker 2Catchy title.
Speaker 1It is right, and it's from some serious folks Harvard Business School, wharton, even people from Procter Gamble so it's practical too.
Speaker 2Really grounded in the real world.
Speaker 1Yeah, totally, and generative AI, just so you know.
Speaker 2Right. Got to make sure we're all on the same page. It's AI that creates stuff like text, like some tools you might have heard of Exactly Okay.
Speaker 1So our mission today to give you the key insights from this paper.
Speaker 2That's it.
Speaker 1How does AI actually impact? How well teams perform?
Speaker 2You know, performance is crucial.
Speaker 1How does it affect how they share knowledge expertise?
Speaker 2Yeah, yeah.
Speaker 1And get this even, the social dynamics, the feelings involved, the human side of things. Exactly, and what's so cool is that this wasn't just some lab experiment.
Speaker 2Oh no.
Speaker 1They had 776 professionals at P&G working on real product innovation stuff.
Speaker 2Wow, that's a lot of people.
Speaker 1It is right. Real challenges they face every day.
Speaker 2That's great data.
Speaker 1It is. So today we'll see how they set up the experiment, what they learned about performance, expertise and you know, all those social things, and then we'll zoom out and think about what it all means for the future of work. Sound good.
Speaker 2Sounds like a plan.
Research Setup: P&G's Innovation Experiment
Speaker 1So how did they even run this experiment?
Speaker 2OK, so they created four different groups to compare different ways of working. First, individuals working alone. No AI help like completely solo.
Speaker 1Got it the lone wolves.
Speaker 2Yeah, exactly Then. Classic human teams, Someone from research and development paired up with someone from the commercial side.
Speaker 1Okay, R&D and commercial.
Speaker 2Yep, and they also didn't have any AI.
Speaker 1No AI for them either.
Speaker 2Nope, Then to see what AI does, they added two more groups.
Speaker 1All right, bring on the AI.
Speaker 2Individuals working on the same tasks, but this time they got an AI tool.
Speaker 1Ah, so they're not alone anymore, they have AI.
Speaker 2Exactly. And the final group, a team, again R&D and commercial, but with AI. They all got training on how to use it.
Speaker 1So everyone using AI was trained up.
Speaker 2Yeah, they made sure everyone was comfortable with the tool.
Speaker 1Makes sense.
Speaker 2For you, the learner. It's important to note these weren't made-up tasks.
Speaker 1Oh, this was real work.
Speaker 2These were experienced P&G people working on actual new product development stuff.
Speaker 1Wow, like what kind of stuff?
Speaker 2Think new ideas for baby care products, feminine care, grooming, oral care you know everyday things.
Speaker 1Wow so like real products people use.
Speaker 2Yep In their actual markets, Europe and the Americas. That's why it's so relevant.
Speaker 1Totally, and they didn't just use any AI, they had a specific tool built on GPT-4 and later GPT-4.
Speaker 2You powerful stuff.
Speaker 1And it was accessed through Microsoft Azure. And that training they got it was a whole hour on using this tool for consumer product innovation.
Speaker 2So not just general AI knowledge, very specific training.
Speaker 1They even got a guide with like suggested prompts to get them started.
Speaker 2Cool like training wheels.
Speaker 1Kind of right. And here's what's really interesting they focused on the very beginning of innovation, what they call the seed stage.
Speaker 2Ah, where it all starts.
Speaker 1And the P&G leadership. They said this phase was crucial for the whole process.
Speaker 2So better starting ideas lead to better products in the end.
Speaker 1That's the thinking. All the teams, with or without AI, collaborated remotely through Microsoft Teams.
Speaker 2Oh, so like how many companies work now.
Speaker 1Exactly, totally normal for a global company like P&G.
Performance Findings: AI Boosts Results
Speaker 2Makes sense. So we have the setup. Now let's see what happened when these different groups actually started working. First up performance. How good were their solutions? No-transcript. Well, teamwork does have its perks. Teams without AI. They improve the quality of their ideas. It was a 0.24 standard deviation increase compared to individuals working alone, also without AI.
Speaker 1So two heads are better than one, even without AI.
Speaker 2Yeah, basically confirms that collaboration helps.
Speaker 1Yeah.
Speaker 2But here's where it gets really interesting what happened when they added AI.
Speaker 1Yeah, that's the big question.
Speaker 2The effect was honestly remarkable. Individuals with AI they performed, as well as those human teams without AI.
Speaker 1Wow, so the AI really boosted them.
Speaker 2Big time A 0.37 standard deviation increase compared to those solo individuals. And it gets better the teams using AI they showed even more improvement 0.39 standard deviation increase.
Speaker 1So AI helped both individuals and teams, but teams still did a bit better.
Speaker 2That's the takeaway. It's like AI gave individuals superpowers, letting them play at the team level.
Speaker 1And a team plus AI was like supercharged.
Speaker 2Exactly. It shows how much AI can enhance what a single person can do.
Speaker 1And it wasn't just about quality either.
Speaker 2Right. They also looked at efficiency how long it took to come up with those solutions.
Speaker 1Because AI is all about productivity right.
Speaker 2Totally. People with AI spent 16.4% less time on their solutions.
Speaker 1Wow, almost a fifth of their time saved.
Speaker 2And AI-powered teams. They were 12.7% faster, so less time overall.
Speaker 1That's a lot of time saved. But were they rushing? Were the AI solutions less detailed?
Speaker 2Actually the opposite. The AI-assisted solutions were way longer. Ah, so more detailed it seems people explored more aspects of the problem, wrote more, but still finished faster.
Speaker 1It's kind of amazing. That is pretty cool. So what about those truly groundbreaking ideas, the top-tier ones?
Speaker 2This is where it gets really exciting.
Speaker 1They looked at the top 10% solutions, the very best of the best, like the cream of the crop Exactly.
Speaker 2Teams with AI were 9.2 percentage points more likely to have those top solutions.
Speaker 1So AI not only helps you do better, it helps you reach excellence.
Speaker 2You got it. It's like combining human ingenuity with AI power, but there's a twist.
Speaker 1Oh, what's that?
Speaker 2Even though their solutions were better, the people using AI were less confident about them.
Speaker 1Really.
Speaker 2They were 9.2 percentage points less likely to think they'd be in the top 10%. Like they underestimated themselves.
Speaker 1Maybe they thought the AI did all the work.
Speaker 2Yeah, maybe. It's like they discounted their own contribution.
Breaking Knowledge Silos with AI
Speaker 1Interesting. Okay, so AI affects performance, but what about how people share knowledge?
Speaker 2This is where AI really starts breaking down walls. Remember those teams without AI.
Speaker 1Yeah, the R&D and commercial folks.
Speaker 2Well, the commercial people. They liked ideas with a strong commercial focus.
Speaker 1Makes sense. They know that world.
Speaker 2Right and the R&D folks. They lean towards technical solutions.
Speaker 1Also makes sense.
Speaker 2Like their backgrounds, created these invisible silos in their thinking.
Speaker 1We all have our comfort zones, right.
Speaker 2We do, but with AI this difference vanished.
Speaker 1There are more silos.
Speaker 2Both groups, With AI proposed more balanced ideas, both commercial and technical.
Speaker 1So the AI helped them thing outside their boxes.
Speaker 2Exactly, it's like AI became this bridge between different areas of expertise.
Speaker 1That's amazing. So we're seeing these performance gains, but who's contributing? What Is AI changing the team dynamics?
Speaker 2It is definitely. It's like AI, is this facilitator helping people see beyond their own roles.
Speaker 1Hmm, interesting Like a neutral third party.
Speaker 2Exactly, and it had a huge impact on less experienced employees. They called them non-core job individuals.
Speaker 1So people who weren't product development experts.
Speaker 2Right Without AI. These folks struggled when working alone Makes sense. They lacked experience.
Speaker 1Yeah, totally.
Speaker 2Even in teams without AI they didn't prove much. But here's the kicker With AI, these less experienced folks performed as well as the experienced teams.
Speaker 1Seriously, that's incredible.
Speaker 2It really is. Ai leveled the playing field big time. It's like a democratized expertise.
Speaker 1So anyone with AI can contribute like an expert.
Speaker 2That's the potential, and when they looked at how teams collaborated, they saw the same thing. Without AI, the team solutions were either very technical or very commercial what they call a bimodal distribution.
Speaker 1Two extremes.
Speaker 2Yep. But with AI the solutions became more balanced, more uniform, like everyone contributed equally.
Speaker 1So AI made the teamwork more even.
Emotional Impact and AI Collaboration
Speaker 2And more inclusive. Now let's talk about the social side, the feelings. This is where things get surprising.
Speaker 1Yeah, how did using AI affect people's moods? I'd imagine it could feel a bit isolating.
Speaker 2You'd think so. Right, but they found the opposite. People who used AI, they felt more positive emotions.
Speaker 1Really Like what.
Speaker 2Excitement, energy, enthusiasm.
Speaker 1Yeah.
Speaker 2And less negative stuff like anxiety and frustration.
Speaker 1So working with a machine actually made them feel better.
Speaker 2That's what the data shows. Their positive feelings were as good as, or even better than, human teams without AI.
Speaker 1Maybe because AI takes some of the pressure off.
Speaker 2Maybe, or maybe the way we interact with AI through language makes it feel more engaging.
Speaker 1It's not just clicking buttons. You're having a conversation.
Speaker 2Exactly and they found a correlation the more people expected to use AI in the future, the more positive they felt during the experiment.
Speaker 1So liking AI makes you want to use it more, which probably makes you like it even more.
Speaker 2Right, it's a positive feedback loop.
Speaker 1Interesting. So AI affects not just the work but also the workers.
Speaker 2For sure. Now, how were people actually using AI? Were they just taking what is spit out?
Speaker 1Yeah, was it just copy and paste?
Speaker 2Well, they looked at how much of the AI generated content ended up in the final solutions.
Speaker 1Okay, so how much did they actually use?
Speaker 2It was a lot Over 75% in many cases. So people were definitely using the AI's output.
Speaker 1But not always right.
Speaker 2Right, some people had zero AI content in their final work.
Speaker 1So they were using AI for brainstorming, not just writing the final product.
Speaker 2Exactly, it was like a thought partner. And here's the key thing Even in those solutions with a lot of AI content, the meaning was closer to human-made solutions.
Speaker 1So they were still adding their own touch, their own understanding.
Speaker 2Totally. Ai wasn't just writing for them, it was collaborating with them.
Speaker 1Humans were still in control.
Future of Work: The Cybernetic Teammate
Speaker 2Absolutely so. What does this all mean for how we work in the future?
Speaker 1Yeah, big picture time.
Speaker 2Well for you, the learner. Think about this. Maybe our idea of team size needs to change.
Speaker 1If one person plus AI, can do the work of two.
Speaker 2Exactly, we could have more flexible, more efficient teams, maybe even individuals, leading projects with AI support.
Speaker 1Wow, that's a big shift.
Speaker 2It is. We could work faster, aim higher, but we need to train people to work with AI.
Speaker 1AI skills are essential now.
Speaker 2Definitely. It's not just about your expertise anymore. It's about how you combine it with AI.
Speaker 1And since AI helps break down those knowledge silos, we need to teach people to think more broadly, like be more well-rounded.
Speaker 2Right, those old departmental boundaries are fading away.
Speaker 1AI is changing the whole game.
Speaker 2It is. It's not just automating tasks, it's changing how we think, how we collaborate.
Speaker 1It's a new way of working.
Speaker 2The researchers call it a cybernetic teammate, and that's spot on.
Speaker 1Yeah, it's not just a tool, it's a partner.
Speaker 2It helps you, it gives you feedback, it even affects your mood.
Speaker 1That term really captures it. So, the learner, what are the big takeaways for you?
Speaker 2AI makes you perform better, sometimes as well as a whole team. It helps you share knowledge, break down those silos and it actually makes you feel better about your work.
Speaker 1It's like that friendly coworker who's always got your back.
Speaker 2And for me, the most amazing thing is that individuals with AI can reach the same level as teams without it and AI-powered teams. They have a way better shot at creating those groundbreaking innovations.
Speaker 1Yeah, that's powerful. So, as you think about your own work, your own teams, ask yourself what doors does this cybernetic teammate open?
Speaker 2What new possibilities are there?
Speaker 1And what does it mean for how humans and AI will work together in the future?
Speaker 2We highly recommend you read the whole paper, Dig deep, think critically and see how these insights apply to you.
Speaker 1Yeah, this research is a peek into the future of teamwork. We're just starting to grasp what it all means.
Speaker 2It's an exciting time.
Speaker 1It is Thanks for joining us on this deep dive, the Learner, until next time.
Speaker 2Keep learning.