Teamwork Isn't Dead — AI Is Redefining How Teams Work, Experts Say
Breaking: The rise of the 'superpowered individual' does not spell the end of teamwork, but a fundamental shift in how teams operate, according to leading organizational psychologists.
Generative AI now enables individual marketers, product managers, and developers to accomplish tasks that previously required entire teams. A single marketer can produce campaign assets, analyze data, and generate content at scale; a product manager can prototype and iterate without engineering; a developer can ship high-quality code written by machines.
This trend has sparked speculation that human collaboration may become obsolete. But experts Tomas Chamorro-Premuzic and Dorie Clark argue the opposite in new research shared with Fast Company.
“It’s tempting to think AI makes teamwork irrelevant. But after working with dozens of top companies, we see that teams are not disappearing — they are transforming,” says Chamorro-Premuzic, organizational psychologist and author of I, Human.
The shift, they predict, will occur in three key areas: team composition, team norms, and the role of AI literacy.
Background: The Rise of AI‑Powered Individu
Generative AI has rapidly advanced, allowing individuals to perform cognitive work at scale. For example, AI agents now stress‑test business strategies, handle finance and operations, and act as quasi‑autonomous development teams. This has led some to question whether human teams are still needed.
However, researchers warn that replacing collaboration entirely ignores the value of diverse perspectives, accountability, and trust that only humans can provide. Clark, a keynote speaker and consultant, notes: “Companies experimenting with AI agents are learning that the friction of teamwork — debate, iteration, shared decision‑making — is not a bug; it’s a feature that leads to better outcomes.”
What This Means: Three Ways AI Will Reshape Teamwork
- Smaller, hybrid teams. Teams are becoming smaller and more nimble because individuals can do more alone. They may include both human and AI contributors. “AI literacy is no longer a nice‑to‑have; it must be a core team capability, not just an individual skill,” says Chamorro‑Premuzic.
- New shared norms. Teams need to agree on when to rely on AI and when not to — the trade‑offs between speed and quality, efficiency and accuracy, and between low‑value and high‑value work. “Without shared norms, AI can amplify errors as fast as it amplifies productivity,” Clark explains.
- Interrogating AI output. Teams must learn to critically evaluate AI’s outputs, treating them as drafts rather than final answers. This requires building a culture of skepticism and verification.
The experts stress that these changes do not mean teamwork is dead — only that it must evolve. “The superpowered individual is real, but even superheroes need teams to avoid blind spots and to scale impact,” says Chamorro‑Premuzic.
For organizations, the immediate takeaway is to invest in team‑level AI training and to redesign workflows that encourage human‑AI collaboration. As Clark puts it: “The companies that thrive will be those that treat AI as a teammate, not a replacement for teamwork.”
More insights from Tomas Chamorro‑Premuzic
Dr. Tomas Chamorro‑Premuzic is chief science officer at Russell Reynolds, professor of organizational psychology at UCL and Columbia University, and cofounder of DeeperSignals. He has authored 15 books and over 250 scientific articles on the psychology of talent, leadership, AI, and entrepreneurship. Learn more
Related Articles
- Securing Your Autonomous AI Agent: A Practical Guide to Safely Deploying Tools Like OpenClaw
- Beyond Content Filtering: How TealTiger v1.2 Enforces AI Agent Governance with Deterministic Policy Evaluation
- Mastering GDB's Source-Tracking Breakpoints: A Hands-On Guide
- How to Automate Your Intellectual Toil with Agent-Driven Development
- Securing Your Git SSH Connections Against Quantum Threats: A GitHub Guide
- Exploring Python 3.15 Alpha 2: Key Features and What to Expect
- NVIDIA Unveils Nemotron 3 Nano Omni: One Model to Rule Vision, Audio, and Language – 9x More Efficient AI Agents
- How to Contribute to the Official Python Blog: A Step-by-Step Guide