AI and the Evolution of Teamwork

This is not a romcom although corporate life is not short of comedians – just not the sort that would make you laugh out loud.

„There are two kinds of people, those who do the work and those who take the credit. Try to be in the first group; there is less competition there.“
– Advice from Motilal Nehru to his granddaughter Indira Gandhi née Nehru

Beyond the AI Teammate Fantasy

Recent research reveals a counter-intuitive truth: AI isn’t fixing teamwork – it’s creating super-individuals. A two-year study (by Xiao et al.) found that AI is overwhelmingly used for individual tasks (coding, writing, documentation) while core collaboration issues like „performance accountability and fragile communication“ remained unresolved.

This isn’t failure; it’s revelation. We never wanted AI teammates. We wanted the appearance of collaboration without its inefficiencies, the credit for teamwork without the work of teaming.

The Super-Individual Phenomenon

AI creates what researchers call „super-individuals“ – team members augmented to extraordinary productivity levels. But here’s the twist: instead of using this capability to enhance collaboration, we are witnessing:

1. Efficiency becoming the baseline – AI-augmented productivity is now expected, not exceptional
2. Trust erosion over time – unlike human relationships, trust in AI teammates decreases with experience
3. Exclusion from accountability – teams don’t hold AI responsible for success or failure

The Real AI Opportunity: Enhanced Crew Work

Rather than forcing AI into a „teammate“ box, consider AI as a coordination catalyst:

Individual Enhancement Phase:

• AI augments each team member’s capabilities
• Eliminates routine tasks, freeing cognitive resources
• Provides analytical insights and rapid information processing

Coordination Enhancement Phase:

• AI collates contributions from all augmented team members
• Identifies gaps, inconsistencies and improvement areas
• Maintains project alignment and information flow
• Acts as organizational diagnostician, revealing hidden dysfunctions

Quality Assurance Phase:

• AI cross-checks outputs for consistency
• Highlights potential bottlenecks before they manifest
• Provides predictive analytics on team capacity and deadlines

Preventing Free-Riders on Stilts

The danger: AI could create „free-riders on stilts“ – underperformers whose AI tools mask their lack of contribution. The solution lies in transparency.

The Future: From Reactive to Predictive

Organizations are shifting from reactive conflict management to predictive team optimization. AI systems that adapt based on workplace interactions are replacing static spreadsheets. The key isn’t making AI a team member but using it to:

1. Enhance individual excellence – creating genuinely capable super-contributors
2. Coordinate enhanced individuals – managing the complex interplay of augmented capabilities
3. Maintain human accountability – ensuring responsibility remains clear and personal
4. Reveal true collaboration patterns – exposing both locomotives and free-riders

Conclusion: The Choreography of Enhanced Collaboration

AI won’t fix teamwork because teamwork, as commonly practiced, was always more theater than reality. But AI can enable something better: genuine crew work where enhanced individuals coordinate their augmented capabilities toward clear objectives.

The future isn’t about AI becoming our teammate. It’s about AI helping us become the teammates we always claimed to be – competent, accountable, and genuinely collaborative. The technology offers transformation; whether we choose decoration or genuine change remains to be seen.