The Future of AI in Team Collaboration

The most powerful use of AI at work won’t be solo. It will be shared. Ben Thompson recently wrote about a compelling use case: how he and his assistant collaborated with a single LLM chat. An example of a shared assistant for team coordination and synthesis. I’ve been thinking about this a lot too. At Dropbox, we’re building toward this future with Dash, our new AI workspace, and specifically with Stacks, a way for teams to organize, track, and reason across all the work happening in a project. Stacks are designed for collaborative intelligence. Teams can pull in docs, links, and tools from anywhere, ask questions about the work, and get AI-generated summaries that evolve as the project does. It’s a persistent shared memory that helps teams move faster, stay aligned, and reduce the drag of context loss. But coordination is just the first step. There are four basic configurations for how humans and LLMs might collaborate: 1. One person working with many agents. The classic orchestration model. Think of a PM using agents for research, writing, and planning. Most solo AI workflows live here today. 2. One agent working with many agents. A tool-using agent. This is the core of agentic infrastructure work. AutoGPT, Devin, and others. A lot of current technical energy is focused here. 3. Many people working with one LLM. A shared assistant for a team. Ben’s focus. This supports team-level memory, project synthesis, and aligned decisions. It’s emerging now. 4. Many people working with many agents, all coordinated through a shared LLM. This is the frontier. Imagine a team approves a campaign plan. Their shared LLM doesn’t just spin up agents. It engages the creative director, strategist, and producer, plus their teams (human and AI). The LLM knows the full context. It routes tasks, surfaces blockers, loops people in, and maintains alignment across the entire system. This isn’t a person using a tool. It’s people and AI, working together, across roles and workflows, with shared direction and shared memory. The shift is from individual productivity to shared intelligence. And the opportunity doesn’t stop at coordination. Negotiation. Conflict resolution. Team morale. Goal tracking. These are the complex, often messy parts of work where tools today tend to disappear. But this is exactly where AI can help. Not by replacing humans, but by holding context, clarifying intent, and accelerating momentum. That’s the future we’re building toward with Dash. AI that doesn’t just respond to prompts. It shows up in the group chat. It remembers the project goals. It knows what’s next. And it helps the whole team move. The future of work is multiplayer. And the most powerful teams will be human and AI, together, all the way down.

AI isn't just a tool; it's becoming a teammate. A major field experiment with 776 professionals at Procter & Gamble, led by researchers from Harvard, Wharton, and Warwick, revealed something remarkable: Generative AI can replicate and even outperform human teamwork. Read the recently published paper here: In a real-world new product development challenge, professionals were assigned to one of four conditions: 1. Control Individuals without AI 2. Human Team R&D + Commercial without AI (+0.24 SD) 3. Individual + AI Working alone with GPT-4 (+0.37 SD) 4. AI-Augmented Team Human team + GPT-4 (+0.39 SD) Key findings: ⭐ Individuals with AI matched the output quality of traditional teams, with 16% less time spent. ⭐ AI helped non-experts perform like seasoned product developers. ⭐ It flattened functional silos: R&D and Commercial employees produced more balanced, cross-functional solutions. ⭐ It made work feel better: AI users reported higher excitement and energy and lower anxiety, even more so than many working in human-only teams. What does this mean for organizations? 💡 Rethink team structures. One AI-empowered individual can do the work of two and do it faster. 💡 Democratize expertise. AI is a boundary-spanning engine that reduces reliance on deep specialization. 💡 Invest in AI fluency. Prompting and AI collaboration skills are the new competitive edge. 💡 Double down on innovation. AI + team = highest chance of top-tier breakthrough ideas. This is not just productivity software. This is a redefinition of how work happens. AI is no longer the intern or the assistant. It’s showing up as a cybernetic teammate, enhancing performance, dissolving silos, and lifting morale. The future of work isn’t human vs. AI. The next step is human + AI + new ways of collaborating. Are you ready?

We just built a commercial grade RCT platform called MindMeld for humans and AI agents to collaborate in integrative workspaces. We then test drove it in a large-scale Marketing Field Experiment with surprising results. Notably, "Personality Pairing" between human and AI personalities improves output quality and Human-AI teams generate 60% greater productivity per worker. In the experiment: 🚩 2310 participants were randomly assigned to human-human and human-AI teams, with randomized AI personality traits. 🚩 The teams exchanged 183,691 messages, and created 63,656 image edits, 1,960,095 ad copy edits, and 10,375 AI-generated images while producing 11,138 ads for a large think tank. 🚩 Analysis of fine-grained communication, collaboration, and workflow logs revealed that collaborating with AI agents increased communication by 137% and allowed humans to focus 23% more on text and image content generation messaging and 20% less on direct text editing. Humans on Human-AI teams sent 23% fewer social messages, creating 60% greater productivity per worker and higher-quality ad copy. 🚩 In contrast, human-human teams produced higher-quality images, suggesting that AI agents require fine-tuning for multimodal workflows. 🚩 AI Personality Pairing Experiments revealed that AI traits can complement human personalities to enhance collaboration. For example, conscientious humans paired with open AI agents improved image quality, while extroverted humans paired with conscientious AI agents reduced the quality of text, images, and clicks. 🚩 In field tests of ad campaigns with ~5M impressions, ads with higher image quality produced by human collaborations and higher text quality produced by AI collaborations performed significantly better on click-through rate and cost per click metrics. As human collaborations produced better image quality and AI collaborations produced better text quality, ads created by human-AI teams performed similarly, overall, to those created by human-human teams. 🚩 Together, these results suggest AI agents can improve teamwork and productivity, especially when tuned to complement human traits. The paper, coauthored with Harang Ju, can be found in the link on the first comment below. We thank the MIT Initiative on the Digital Economy for institutional support! As always, thoughts and comments highly encouraged! Wondering especially what Erik Brynjolfsson Edward McFowland III Iavor Bojinov John Horton Karim Lakhani Azeem Azhar Sendhil Mullainathan Nicole Immorlica Alessandro Acquisti Ethan Mollick Katy Milkman and others think!

If you’re in leadership, you need to understand *how* genAI will transform your organization, and what that means for restructuring teams. Here's what we're learning: BREAKTHROUGH IN AI IDEATION OpenAI is getting ready to launch new AI models (o3 and o4-mini) that can connect concepts across different disciplines ranging from nuclear fusion to pathogen detection. (Reporting from The Information's Stephanie Palazzolo and Amir Efrati). Molecular biologist Sarah Owens used the system to design a study applying ecological techniques to pathogen detection and said doing this without AI "would have taken days." THE NEW TEAMMATE EMERGES Remember the HBS study with 776 Procter & Gamble professionals? It showed that genAI functioned as an actual teammate. Individuals using AI performed at levels comparable to traditional human teams, achieving a 37% performance improvement over solo workers without AI. Teams using AI were three times more likely to produce top-quality solutions while completing tasks 12.7% faster and producing more detailed outputs. BREAKING DOWN SILOS That study showed that AI also dissolves professional boundaries. Without AI, R&D specialists created technical solutions while Commercial specialists developed market-focused ideas. With AI, both types of specialists produced balanced solutions integrating technical and commercial perspectives. A NEW KIND OF TEAM AI users reported higher levels of excitement and enthusiasm while experiencing less anxiety and frustration. Individuals working alone with AI reported emotional experiences comparable to those in human teams. That's wild. RESTRUCTURING FOR ADVANTAGE The HBS study showed that AI reduces dominance effects in team collaboration. When genAI translates between roles, it accelerates iteration at a pace that there’s no way traditional teams could match. ++++++++++++++++++++ THREE THINGS YOU SHOULD BE DOING NOW: 1. Upskill your entire workforce: Develop a fundamental behavioral shift in how teams interact with AI across every task. This only works if everyone is doing it. (We work with enterprise to upskill at scale - more below.) 2. Experiment with new team structures: Test different AI-team combinations. Try individuals with AI for routine tasks and small teams with AI for complex challenges. Find what works best for your specific needs. 3. Redefine success metrics: Set new standards for what good work looks like with AI. Track not just productivity but also idea quality, knowledge sharing across departments, and team satisfaction—all areas where AI shows major benefits. ++++++++++++++++++++ UPSKILL YOUR ORGANIZATION: When your company is ready, we are ready to upskill your workforce at scale. Our Generative AI for Professionals course is tailored to enterprise and highly effective in driving AI adoption through a unique, proven behavioral transformation. It's pretty awesome. Check out our website or shoot me a DM.

𝐌𝐲 𝐀𝐈+𝐇𝐈 𝐑𝐚𝐝𝐚𝐫: 𝐓𝐡𝐢𝐬 𝐖𝐞𝐞𝐤'𝐬 𝐌𝐮𝐬𝐭-𝐑𝐞𝐚𝐝𝐬 Hey everyone, here are the articles that caught my eye this week on AI plus Human Factors. Links in the comments below: Overarching Theme: AI is transitioning from an optional tool to an essential teammate Shopify CEO Makes AI Use Mandatory (TechCrunch/Livemint) Key takeaway: Shopify is operationalizing AI as a default productivity tool and tying headcount decisions to AI capability. Tobi Lütke announced AI proficiency is now a baseline expectation, calling it a "100x multiplier" and requiring proof AI can't handle tasks before approving new headcount. Why it matters: This represents one of the clearest corporate mandates that AI use is non-negotiable, signaling AI fluency as a prerequisite for performance. The Cybernetic Teammate: AI in Real-World Teams at P&G (Ethan Mollick) Key takeaway: AI eliminates professional silos and helps less experienced employees close performance gaps. P&G's study found AI-enabled teams delivered the highest quality solutions, with individuals using GPT-4 performing as well as two-person teams without AI. Why it matters: AI is evolving beyond a productivity tool to replicating benefits of human teamwork, suggesting AI fluency may soon be a team design strategy. Accenture's AI Tool Enhances Employee Feedback (Fortune) Key takeaway: AI overcomes vague feedback by helping employees better articulate their thoughts in evaluations. Accenture's tool has significantly improved feedback quality, giving managers comprehensive performance views throughout the year. Why it matters: Shows AI's transformative potential in HR by enabling more meaningful feedback, leading to more accurate assessments. From One to Many: AI Agents at Microsoft (Christopher J. Fernandez) Key takeaway: Microsoft positions personal "build lists" of AI agents as potentially more valuable than résumés. Microsoft encourages employees to build personal AI agents (no coding required) for everything from self-service to knowledge sharing. Why it matters: This demonstrates how to operationalize agentic AI as extensions of human insight, unlocking distributed innovation. MIT Media Lab Launches AHA Program (MIT Media Lab) Key takeaway: MIT explores how AI can advance human comprehension, well-being, curiosity, and creativity beyond simple utility. The Advancing Humans with AI program explores how AI systems can support human flourishing, focusing on social, emotional, cognitive, and ethical advancement. Why it matters: Signals a shift from AI performance to purpose, positioning AI as a force for expanding human potential. Bottom Line: We're witnessing AI's rapid evolution from optional productivity tool to essential teammate and capability multiplier, with leading organizations already building structures that assume AI proficiency as a baseline skill. #AIWorkforce #HumanAICollaboration #FutureOfWork

If you’re in leadership and still thinking of generative AI as just another software upgrade, you may want to reframe… fast. THE ERA OF INTERDISCIPLINARY IDEAS (BROUGHT TO YOU BY MACHINES) OpenAI is reportedly gearing up to launch new models (O3 and O4-mini), and these aren’t your average chatbot upgrades. We’re talking systems that can connect the dots between nuclear fusion and pathogen detection. (No, really. That’s from The Information’s Palazzolo and Efrati, not a sci-fi pitch.) Molecular biologist Sarah Owens used one of these systems to merge ecology and epidemiology. Without AI? “Would’ve taken days.” With AI? One brainstorming session and a cup of coffee. SO... WHO'S ACTUALLY ON YOUR TEAM NOW? Harvard Business School studied 776 Procter & Gamble professionals and uncovered something fascinating: Generative AI doesn’t just assist—it collaborates. Individuals using AI achieved performance levels typically reserved for human teams—outperforming solo humans by 37%. AI-assisted teams were three times more likely to generate top-tier solutions. Oh, and they did it 13% faster, too. COLLABORATION, UN-SILOED Here’s the plot twist: AI didn’t just boost output—it blurred lines. Traditionally, R&D folks stuck to the tech while Commercial teams focused on market fit. But once AI entered the room, both groups started solving problems with both lenses. Apparently, AI’s not big on departmental turf wars. WHO KNEW BOTS COULD BOOST MORALE? Solo contributors using AI reported emotional responses on par with team collaboration. Yes, the machines made people feel less anxious, more productive, and oddly... excited. Which is more than we can say for most Slack threads. SO WHAT SHOULD YOU ACTUALLY DO ABOUT THIS? Here’s the cheat sheet for business leaders who don’t want to be left in the analog dust: Upskill Everyone Not just the innovation team. Not just the interns. Everyone. You need a cultural shift where every employee engages AI as a daily collaborator. (Need help scaling that? Let’s talk.) Rethink Team Structures Mix and match. Solo with AI for the grunt work. Small teams with AI for the big-picture stuff. Your org chart may need an AI row. Redefine What “Good Work” Means Stop tracking just productivity. Start measuring cross-functional ideation, knowledge flow, and—yes—team satisfaction. Because in this new era, speed is great… but insight is the real edge. 📊 Where data meets behavioral science—shaping the future of work. Join a network of executives, researchers, and decision-makers who rely on Michael Housman for insights at the intersection of AI, analytics, and human behavior. 👉 Stay ahead—subscribe to the newsletter: www.michaelhousman.com #AIinBusiness #FutureOfWork #LeadershipDevelopment #DigitalTransformation #GenAI

New research from Harvard Business School explores a big question: What if AI isn’t just a tool but a teammate? In a large-scale field experiment with Procter & Gamble, researchers tested how GPT-4 affected performance when used by individuals versus teams of experienced professionals working on real product development challenges. Some key findings: - AI-enabled individuals performed as well as teams without AI - Teams using AI produced the best and most exceptional results overall — not only did they outperform others, but they were significantly more likely to generate top 10% solutions - AI helped bridge expertise gaps and broke down professional silos - Participants using AI had better emotional experiences — more excitement, less frustration The takeaway? AI isn't just about individual productivity — it’s reshaping how we collaborate, think, and solve complex problems. It’s acting more like a cybernetic teammate, not just a more efficient tool. The working paper — “The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise” — is worth a read. As someone interested in the future of work, this raises important questions: 1. How do we design teams when AI levels the playing field? 2. What happens to traditional boundaries between roles? 3. How do we rethink collaboration when AI enhances both performance and emotional engagement? Curious what you all think — especially if you’re leading teams or exploring how to integrate AI meaningfully into your org. #FutureOfWork #LinkedInWorkplace #LinkedInLife #WorkplaceResearch

Update: Human-AI Task Scale has expanded. I'm thrilled to share the latest update to the Human-AI Task Scale, now with three critical new agent orchestration levels (Levels 8-10). As AI and machine learning continue to transform Learning & Development (L&D), our roles are evolving rapidly. The newly defined levels represent advanced human and AI collaboration, emphasizing a sophisticated balance between human oversight and AI autonomy. These advanced levels illustrate the pivotal new role emerging in our field—the Human-Machine Performance Analyst™ (HMPA). As we transition towards higher AI autonomy, the HMPA's responsibilities shift from content creation to strategic oversight and ecosystem governance, significantly elevating our impact on organizational performance. Quick Overview: Level 8 (Human-Orchestrated Agent Constellations): HMPAs actively design and coordinate specialized AI agents to enhance immersive learning experiences, such as creating dynamic roleplays and performance assessments. Level 9 (Agent-Agent Collaboration with Human Governance): AI agents independently negotiate and collaborate in real time, guided by the HMPA, who ensures alignment with strategic learning outcomes, relevance, and fairness. Level 10 (Agentic Ecosystems with Distributed Oversight): Autonomous AI ecosystems dynamically self-configure learning environments across departments, with HMPAs setting strategic behavioral policies and governance frameworks, rather than managing individual tasks. As Learning & Development evolves, embracing this strategic role will be crucial. I invite all L&D professionals to explore these advancements and consider how to integrate this powerful human-AI collaboration into your practice. How do you see these advancements reshaping your role or your organization's approach to learning? Special thanks to Kim Denton, MA, CSM, MS, (Cohort #1) for inspiring this post!

The future of work isn’t AI replacing humans … it’s AI working side by side with us. Are we ready for this shift? I see a lot of talk about AI as a threat, but what excites me? Watching my team at StratusDial and UponAI roll up their sleeves and get ready to work WITH AI, not against it. We started with a simple vision: 👉 AI Voice agents on every business phone system, starting with our own. But a vision means nothing without action. Here’s what we’re doing: ✅ Upskilling staff to work with new AI tools (yes, even the folks who said “I’m not a tech person”) ✅ Opening new roles for AI collaboration, think “AI workflow partner” or “voice agent coach” ✅ Measuring the real-world impact, not just counting hours saved but tracking how people feel about their work The changes are real. People spend less time on busywork. More time on the calls and projects that need a human touch. Teams feel less overwhelmed, not more. Even our skeptics are now the ones sharing tips on how to get the most out of our AI voice agents. (I call that a win!) As a leader, I believe it’s my job to prepare us for what’s next. AI isn’t a nice-to-have. It’s part of the toolkit now. You wouldn’t send your team out without a phone system that works—why send them out without AI in their corner? The future of work looks a lot like teamwork, only now, some of our teammates are digital. How are you preparing your team for the age of AI-powered collaboration? #PhoneBill ☎️ #FutureOfWork #AI #Leadership #DigitalTransformation #BusinessCommunications #AIVoice #UCaaS #CCaaS

Around the world, we’re seeing organizations evolve from experimenting with AI to reimagining how work gets done. What starts as a single assistant helping with tasks becomes something far more powerful: AI as a true teammate, seamlessly woven into daily operations.   The 2025 Work Trend Index calls the most advanced of these organizations Frontier Firms and they’re leading the way in both growth and innovation.   But getting there doesn’t happen overnight. It’s a journey.   It begins by empowering individuals with AI tools. Then, teams start collaborating with agents that take on specific roles. Eventually, businesses build systems where humans guide strategy, and AI executes with precision—freeing up time, creativity, and energy.   We’re already seeing powerful signals of this shift in action: 💡 Dow is using AI agents to identify misapplied fees in its supply chain, streamlining operations and unlocking cost savings at scale. 💡ICG - Industrialized Construction Group is using AI for everything from simulations to research, boosting margins and focusing hiring on high-value roles.   The most important ingredient? A people-first mindset. Frontier Firms invest as much in reskilling and readiness as they do in technology.   What’s one capability or mindset your team is building today to get ready for this future?   Explore more in our latest report: https://lnkd.in/exTEnV4D