How AI Became a create Teammate – From Research to Daily Work
- AI as a capable teammate: According to the Harvard study, individuals supported by AI achieve similar or even better results than traditional two-person teams thanks to structured idea development, feedback, and suggestions.
- Breaking down functional silos: AI promotes cross-functional thinking by introducing interdisciplinary knowledge and encouraging employees to think beyond their usual roles.
- Motivational and efficiency gains: Users experience working with AI as more focused, structured and motivating tasks are completed faster and with greater depth, especially during early stages of thinking.
- Concrete practical applications: AI supports the evaluation of business ideas, risk planning, financial topics, sales training, market observation and the development of new business models.
- A transformed way of working: AI leads to more efficient, integrated and autonomous workflows it not only complements expertise but expands the scope for thinking and action in daily work.
Can AI really act as a teammate and not just a tool but a collaborative partner in your daily work?
This idea has moved from speculation to real-world relevance, especially after a recent field experiment conducted by Harvard Business School. The study, “The Cybernetic Teammate” (Dell’Acqua et al., 2025), explored how Generative AI influences collaboration, performance and expertise across teams.
Their findings align surprisingly well with my own experience using AI tools like ChatGPT, Copilot and other tools in sales, project management and business model innovation.
What the Research Shows: AI That Thinks (Almost) Like a Colleague
The Harvard study involved 776 professionals at Procter & Gamble who worked on realistic innovation tasks. Some worked in teams, others alone with or without AI support.
One of the most striking outcomes: individuals using AI performed at the same level or better than two-person teams without it. The reason? AI contributed to the thinking process—structuring ideas, proposing alternatives and generating insights just like a capable team member would.
Another key finding: AI helped professionals break free from their functional silos. For example, R&D staff and commercial staff normally proposed very different types of solutions. But when supported by AI, both groups offered more balanced, cross-functional proposals. This happened because the AI, trained on a vast range of topics, introduced ideas beyond users’ core domains.
The study also noted a motivational shift. People using AI felt more energized, excited and focused. This wasn’t a coincidence. The conversational feedback from AI seemed to simulate social support-providing structure, suggestions and reinforcement, which reduced stress and made tasks feel more engaging.
And finally, there were efficiency gains. Participants with AI completed their tasks more quickly, with more depth and detail. The AI accelerated early stages of thinking, helping users focus on refinement and implementation.
What It Looks Like in Practice: My Daily Use Cases
These findings aren’t just theoretical. I’ve seen the same effects across multiple business areas. Here’s how AI now supports teams in my courses:
Evaluating Business Ideas with Risk Profiles
AI helps me quickly explore the strengths, weaknesses and risks of new concepts. It offers perspectives teams might miss, helping them build more balanced and well-argued proposals.
Enabling Project Managers to Understand Financial Structures
AI is particularly useful when navigating financial concepts like hedging, Letters of Credit, or how to manage cash flow risks in complex projects. It doesn’t replace a finance department but it helps understand what questions to ask and what options to consider.
Assessing Project Risks and Contingency Planning
For project planning, AI assists in building structured risk models, defining possible disruptions, and recommending contingency reserves. This makes planning more robust without slowing it down.
Training Sales Team Members
When onboarding new sales colleagues, team leads can use GPTs to create learning modules, simulate customer conversations and draft objection-handling scripts. The content is targeted, immediate and also scalable.
Monitoring Industry Trends and Competitor Activity
AI helps summarize the latest developments from different sectors. With the right prompts, teams can generate industry overviews that once took hours and now completed in minutes with even better coverage.
Designing New Business Models in the Machine Building Industry
In markets where capital goods sales are slowing down, AI has become essential in exploring alternative revenue models like pay-per-use, leasing or service-based pricing. I use GPT to simulate customer ROI, cash flow impacts and breakeven scenarios. It helps turn strategy into something concrete and actionable and it does so quickly.
How Work Is Changing Around AI
What these examples show is not just faster execution but expanded thinking. AI helps operate beyond core expertise blending financial, commercial and technical thinking when needed. Tasks that used to require multiple roles or departments now start with the user and a well-crafted prompt.
Daily work becomes more efficient, yes. But it also becomes more integrated. AI reduces the need to wait for handovers or approvals and it helps professionals become more self-sufficient. That’s a subtle but important shift.
And perhaps most notably, it changes how work feels. When teams use AI effectively, it feels like they co-creating something not just completing a task. That momentum, structure and sense of progress are part of what make AI not just a tool but a real collaborator.
Conclusion
The Harvard study confirmed something I already suspected: AI isn’t just about automation. It’s about amplification. It doesn’t replace expertise but it enhances and complements it. It doesn’t do your thinking for you but it challenges and extends how you think.
(This article was partly developed and refined with the support of AI)
Projektmanagement & KI – Kurs – IHK Akademie Bielefeld
KI im Vertrieb Seminar: Verkaufsstrategien optimieren – IHK
