How AI is Reshaping Teamwork: Why Collaboration Remains Essential in the Age of Automation

Generative AI has fundamentally changed the way work gets done. Today, a single marketer can produce campaign assets, analyze data, and generate content at scale. A product manager can prototype, test, and iterate without relying on engineering, and developers can deploy high-quality code written by machines. The result? The rise of the “superpowered individual” who can accomplish the work of many.

This shift has led some to question whether human collaboration is becoming obsolete. If AI can replicate or augment the cognitive contributions of multiple individuals, why endure the friction of teamwork? However, research and real-world experimentation suggest otherwise. In our work with top companies—Tomas as an organizational psychologist and author of I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique, and Dorie as a keynote speaker and consultant for companies adapting to AI—we’ve observed how organizations are integrating AI agents to stress-test strategies, handle critical functions like finance and operations, and even function as quasi-autonomous development teams.

Despite these advancements, we believe teamwork is here to stay—though AI will reshape it in profound ways. Specifically, we see three key shifts in how teams will operate:

1. Team Composition Will Change

Teams are likely to become smaller and more nimble as individuals take on more responsibilities. These teams may include both human and nonhuman contributors, blending AI capabilities with human judgment. However, AI literacy must evolve from an individual skill to a core team capability. Teams will need shared norms around critical questions, such as:

• When to rely on AI (and when not to): Understanding the strengths and limitations of AI tools.
• Balancing speed and quality: Navigating the trade-offs between efficiency and accuracy.
• Distinguishing low-value from high-value work: Focusing on tasks that drive meaningful outcomes.
• Interrogating AI outputs: Combining machine-generated results with human judgment to ensure reliability.

Effective teams will also need mechanisms to reward not just AI efficiency, but the critical skill of spotting when AI is wrong. In practice, this could mean formalizing “AI skepticism” as part of performance evaluations, ensuring teams remain vigilant and discerning.

2. The Focus of Teams Will Shift from Tasks to Relationships

Many teams currently spend significant time on logistical tasks—coordinating updates, analyzing data, and reporting across departments. However, AI can handle these transactional activities faster and more efficiently. As a result, the nature of teamwork will evolve into something far more valuable: relational collaboration.

Leaders should prioritize building trust and fostering meaningful interactions. This means:

• Reducing the volume of low-value interactions in favor of higher-quality engagements.
• Increasing in-person collaboration when possible to strengthen connections.
• Creating structured opportunities for constructive disagreement.

Psychological safety remains essential, but so does intellectual friction. The goal is not harmony for its own sake, but productive conflict that drives innovation and better decision-making. In this AI era, teamwork is likely to feel more meaningful than ever—becoming a core component of both professional roles and personal identity.

Why Meaningful Collaboration Matters

When teams connect deeply through shared goals and activities, collaboration transcends mere task execution. It becomes a source of fulfillment, purpose, and professional growth. AI may automate many of the mundane aspects of work, but it cannot replicate the human connections that drive creativity, trust, and collective achievement.

In short, AI will not destroy teamwork—it will elevate it. Organizations that embrace this shift, investing in relational collaboration and AI literacy, will be best positioned to thrive in the evolving workplace.