Will AI Destroy Teamwork?
At the very least, it will transform it.
The following contribution comes from the Fast Company website, which defines itself as follows: the world’s leading business media brand, with an editorial focus on technological innovation, leadership, transformative ideas, creativity, and design. Aimed at the most forward-thinking business leaders, Fast Company inspires its readers to think big, lead with purpose, embrace change, and shape the future of business.
Launched in November 1995 by Alan Webber and Bill Taylor, two former editors of Harvard Business Review, Fast Company magazine was founded on a fundamental premise: a global revolution was transforming business, and business was transforming the world. Leaving behind the old business rules, Fast Company set out to document how constantly changing companies create and compete, highlight new business practices, and introduce the teams and individuals who are creating the future and reinventing business.
The article is authored by Tomas Chamorro-Premuzic and Dorie Clark. Tomas, an organizational psychologist and author of «I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique,» and Dorie, a keynote speaker and consultant for companies reinventing themselves in the face of AI.
Dr. Tomas Chamorro-Premuzic is the Russell Reynolds Chief Scientific Officer, Professor of Organizational Psychology at UCL and Columbia University, and co-founder of DeeperSignals. He is the author of 15 books and more than 250 scientific articles on the psychology of talent, leadership, AI, and entrepreneurship.
Will AI Destroy Teamwork?
Generative AI has enabled individuals to perform tasks that previously required entire teams. Today, a single marketing professional can create campaign materials, analyze data, and generate content at scale. A product manager can prototype, test, and iterate without relying on the engineering team; And developers can deliver vast amounts of high-quality, machine-written code. The result is the rise of the “superhuman” capable of doing the work of many.
It’s tempting to extrapolate that human collaboration is becoming obsolete. If AI can replicate or enhance the cognitive contributions of multiple individuals, why bother with the difficulties of teamwork?
In our work with leading companies—Tomas, an organizational psychologist and author of “I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique,” and Dorie, a keynote speaker and consultant for companies reinventing themselves in the face of AI—we’ve observed a wide range of experimentation. Companies are using agents to test their strategies, manage key functions like finance and operations, and operate as quasi-autonomous development teams.
Even so, we believe that teamwork is here to stay,
though AI will almost certainly transform it. Specifically, we believe teamwork will change in three key ways:
- Team composition will change. Teams are likely to become smaller (and perhaps more agile) because individuals can do more on their own, and teams may include both human and non-human contributors. Consequently, it won’t be enough for just a few people to be «good with AI.» AI literacy must become a core team capability, not an individual skill.
Teams need shared norms on emerging issues such as:
– When to trust AI (and when not to);
– Understanding the difference and trade-offs between speed and quality, efficiency and accuracy, low-value and high-value work; and
– How to analyze AI output and combine it with human judgment. Effective teams will need to develop a mechanism to reward people not only for using AI efficiently but also for detecting when it fails. In practice, this could mean incorporating «AI skepticism» as a formal part of performance reviews.
- The focus of teams will change. Today, many teams are centered on logistical issues: a heterogeneous mix of analysis, reporting, and coordination across divisions and departments. (Anyone want a status update?) This kind of task-based teamwork could soon become obsolete, as AI can manage it more quickly and efficiently.
But teamwork has never been limited to task execution, and in the age of AI, it will evolve into a higher-value activity that unlocks new possibilities for organizations. In fact, as transactional collaboration declines, relational collaboration becomes more important.
Leaders must deliberately invest in building trust: fewer but higher-quality interactions; more face-to-face time when possible; and structured opportunities for disagreement. Psychological safety is important, as is intellectual friction. The goal is not harmony, but productive conflict.
As a result of this shift, teamwork is likely to be increasingly perceived as meaningful, as a fundamental component of both work and professional identity. When a deep connection is forged with others through shared goals and activities, it becomes a highly valuable experience that fosters loyalty to the team and the company.
- The role of leaders will also change. In the age of AI, leaders will need to make three significant changes in how they guide their team members. Specifically, this means:
Being more intentional in focusing the team on high-value tasks. With AI handling a larger portion of the analytical and operational workload, leaders will need to redesign teams around criteria, not tasks. Teams should be explicitly defined around higher-order objectives: raising issues, making strategic decisions, and aligning priorities. In other words, leadership’s soft skills may be the hardest to replace. A simple rule of thumb is that if a meeting could be replaced by an AI-generated briefing, it probably should be.
Reconceptualize your role as an orchestrator, not a source of answers. Leaders should begin to see themselves as architects of human-machine collaboration. This involves clarifying the roles of AI and people, establishing decision-making authority, and ensuring accountability. It also requires resisting the temptation to delegate to AI when the stakes are high. Judgment, not the outcome, remains the leader’s ultimate responsibility.
Measure what truly matters. In many organizations, performance is still evaluated based on visible activity, rather than the quality of thought. In an AI-driven world, this becomes dangerous. Leaders should orient metrics toward the quality of decisions, the speed of learning, and long-term outcomes, rather than short-term productivity gains.
In short, the old model of teamwork based on processing and coordination is disappearing. But the new teamwork—integrated with AI and infused with human talent and judgment—will be more essential than ever, and organizations will need to find a way to evolve.
The risk is not that AI will destroy teamwork, but that it will reveal that much of what we once called teamwork was never truly valuable. The opportunity lies in rebuilding it around human strengths: critical thinking, meaningful connection, and sound decision-making, so that the whole is greater than the sum of its parts.
When AI Joins the Team, Better Ideas Emerge
The following contribution comes from the Harvard Business Review portal in its “Working Knowledge” section, which is defined as: Practical Knowledge
Distilling Harvard Business School Research for Leaders Who Make a Difference
It is authored by Scott Nover, a writer based in Washington, D.C. He contributes to Slate and was previously a writer at Quartz and Adweek, where he covered media and technology. This article is based on research by Fabrizio Dell’Acqua, Raffaella Sadun, and Karim R. Lakhani.
Generative AI can act as a high-performing collaborator on team projects, driving innovative thinking, according to research by Fabrizio Dell’Acqua, Raffaella Sadun, and Karim Lakhani. They offer four recommendations for applying AI to teamwork.
When AI Joins the Team, Better Ideas Emerge
Many companies are adopting artificial intelligence as a practical tool to boost employee productivity, but research shows that AI can go further, even acting as a collaborator on team projects.
After studying 791 product development professionals at Procter & Gamble, researchers at Harvard Business School discovered that AI can function as a «cyber companion,» offering many of the same benefits as human collaborators, such as generating better ideas and sharing knowledge. Furthermore, this technology can even increase team members’ enthusiasm for their work.
If you want to be among the top 10%, a human team complemented by AI appears to be the key to success.
The findings demonstrate that AI can go beyond summarizing texts or cleaning spreadsheets, according to the researchers. The results of the field experiment revealed that workers using AI were more likely to generate ideas that ranked in the top 10% of all proposals, demonstrating that the technology can help companies produce «the kind of innovative solutions that drive organizational success,» according to the working paper «The Cybernetic Companion: A Field Experiment on Generative AI Transforming Teamwork and Experience,» updated in April 2025.
«If you want an individual to be as effective as a team, just give them AI,» says Fabrizio Dell’Acqua, a postdoctoral researcher at Harvard Business School (HBS) and one of the study’s co-authors. «But if you want to be among that top 10%, a full human team combined with AI seems to be the formula for success.»
Two HBS professors were among the co-authors: Raffaella Sadun, Charles E. Wilson Professor of Business Administration at HBS, and Karim R. Lakhani, Dorothy & Michael Hintze Professor of Business Administration. Additional co-authors included Charles Ayoubi of ESSEC Business School; Hila Lifshitz of the University of Warwick; Ethan Mollick and Lilach Mollick of the University of Pennsylvania; and four P&G employees: Yi Han, Jeff Goldman, Hari Nair, and Stew Taub.
AI improves team performance.
During the P&G experiment, conducted between May and July 2024, researchers randomly assigned participants to work individually or in multidisciplinary teams on projects related to the company’s childcare, feminine care, grooming, and oral care units.
The goal was to develop viable ideas for new products, packaging, communication strategies, or retail functions for the consumer packaged goods company. Some individuals and teams used an internal AI tool based on GPT-4, while others did not.
With AI:
Teams produced the highest-quality solutions. Ideas that ranked in the top 10% were three times more likely to come from teams using AI, compared to ideas from individuals working without it.
Individuals also generated better ideas, matching the quality of a two-person human team that did not use AI.
Both teams and individuals contributed ideas that combined technical and business elements equally, challenging organizational barriers.
Employees less familiar with product development tasks achieved performance levels comparable to those of experienced colleagues, suggesting that AI can extend problem-solving capabilities to a wider range of employees.
“Now we have many more areas in any company that can contribute great ideas,” says Dell’Acqua. “The traditional notion of who has expertise in tasks and domains is much less relevant.”
In numbers
Dell’Acqua, Sadun, Lahkani, and other researchers found that AI reduced the time it took Procter & Gamble employees and teams to develop innovative ideas.
16% reduction in time for individuals
13% reduction in time for teams
Without AI, individuals generated the lowest-quality ideas: those considered less novel and with less potential business impact. Research and development staff also tended to offer technical solutions, while marketing staff contributed business insights, compared to the innovative ideas of teams and individuals using AI.
Employees using AI reported significantly higher levels of enthusiasm and energy for projects, and less anxiety and frustration, compared to employees working alone without AI.
“We’ve seen technologies that improved productivity or performance, but at the same time were perceived somewhat negatively,” says Dell’Acqua. “However, when workers interacted with AI, they felt at least as satisfied as when they interacted with other people. That was truly fascinating.”
Recommendations for Using AI in Teams
Based on the findings, Dell’Acqua offered several recommendations for companies looking to optimize AI-human collaboration:
Reconceptualize AI as a teammate, not a tool.
Focus on managing relationships with AI rather than understanding technical specifications. This shift in mindset can foster more effective interactions and better results.
Offer targeted training on interacting with AI.
Even short, hands-on training sessions can dramatically improve outcomes. Teach employees to treat AI as a collaborative thinking partner, rather than a search engine.
Consider different AI strategies for different objectives.
Utilize people with AI capabilities to increase efficiency, but maintain AI-powered teams to capitalize on disruptive innovation opportunities.
Address fears about AI adoption through empowerment.
Focus training on how AI augments, rather than replaces, human capabilities, emphasizing the collaborative, rather than competitive, aspects of human-AI interaction.
As organizations continue to integrate AI technologies, the study suggests we are witnessing more than just productivity gains. AI integration is transforming how work is done, not only helping people work faster but also changing the very nature of collaboration.
«If these knowledge silos can take a very different form with AI, perhaps we should rethink the design of organizations,» says Dell’Acqua.
The Real Reason AI Doesn’t Help Your Team Work Better
The following contribution comes from the Thoughts on Design, Technology and Culture portal and is authored by Itamar Medeiros, who describes himself as follows: Originally from Brazil, I currently reside in the Heidelberg region of Germany, where I work as Vice President of Design Strategy at SAP and teach Project Management for UX in the Master’s Program in Usability Engineering at the Rhein-Waal University of Applied Sciences, promoting User Experience (UX) Design.
I have worked in the Information Technology industry since 1998 and have served as a juror in several international design competitions, including the 2016 IxDA Interaction Awards, the 13th, 12th, 11th, and 10th editions of the Brazilian Association of Graphic Design Biennial, and the 2010 IxDA Global Student Design Challenge, among others.
The problem with AI-powered collaboration tools failing remote teams isn’t the technology itself, but rather the poorly implemented work structures that AI simply exposes.
Itamar Medeiros
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CSCW: Why Do AI-Powered Collaboration Tools Fail Remote Teams?
What appears to be a connected system can be fundamentally broken. When teams structure work incorrectly, AI doesn’t fix it; instead, it makes the misalignment impossible to ignore.
Many teams are investing in AI to improve their collaboration. However, many continue to grapple with the same coordination issues.
Why Do AI-Powered Collaboration Tools Fail Remote Teams?
The problem rarely lies with the technology itself. Instead, it lies in how teams structure their work. Most AI systems prioritize individual productivity, not team coordination. As a result, they often amplify existing problems rather than solve them.
This publication analyzes the conditions that must be met for support to be useful.
Most teams turn to AI before diagnosing the type of work they actually do. Therefore, the problem is usually not the technology itself. Agents don’t create coordination failures; they simply expose existing ones.
Most teams don’t have a collaboration problem, but rather a poorly implemented collaboration structure.
AI-powered collaboration tools fail in remote teams not due to a lack of capability, but because teams apply them to the wrong type of work.
