Leveraging AI for Remote Collaboration

I've received a few questions on this, so thought I'd share 5 ways I'm using AI in my day-to-day at work to boost productivity, insight, and strategic clarity: Benchmarking: I use AI daily to quickly validate metrics and performance benchmarks. For instance, when reviewing email open rates, I ask ChatGPT (and other LLMs) for industry benchmarks segmented by email types, industries and content. This provides immediate clarity on performance against the rest, and I can see if we're good, great, or have work to do. This information was hard to find or non-existent before and instantly helps builld context. Thought Partner: LLMs elevate my strategic thinking. Whether analyzing competitors or drafting new strategies, I leverage AI to rapidly identify gaps, assess my thoughts against frameworks like "Seven Powers," and run game theory on them with competitive response and market players. It uplevels my thinking and leads to more comprhensive considerations. Deepening Customer Insights: By processing sales call transcripts and meeting notes through AI, I can surface customer pain points and uncover new insights, which improves my understanding of customer needs, sales blockers and messaging that otherwise would be hard to come by. Writing Partner: I use AI to power my writing process—from refining documents to constructing logical, concise, and compelling arguments. It helps draft outlines, provides examples and proof-points to reinforce my assertions, and streamlines my writing. All-in it makes my writing better and faster. Automating Daily Tasks: I use AI-powered tools daily to track competitors, monitor market trends, and check-in on things I care about. It never stops working and so I always have this information available as needed. Today, AI is integral to about half of my workday. And this is just the beginning—there's even more potential to unlock with automations such as reviewing and drafting replies for my emails, prioritizing which documents to review next, and automated meeting prep. How are you integrating AI into your workflow? I'd love to hear what's worked for you.

ChatGPT is the new Excel. Here’s your first step toward AI. Many companies are racing to adopt AI, but the biggest opportunity often goes unnoticed: empowering your team with AI tools. It’s not just about building new AI products; it’s about integrating AI into the daily workflow of your employees. The tools—like ChatGPT, Claude, and Perplexity—are available, but the knowledge gap is significant. While people experiment with these tools, few companies provide the right training to maximize their value. A well-trained workforce using AI effectively is a game changer. This skill set not only accelerates daily tasks but also builds the foundation for larger AI initiatives. Companies that fail to build this muscle now are not only leaving productivity gains on the table but also signaling to their most innovative employees that they’re not serious about AI. The wrong step? Banning AI tools like ChatGPT. The right step? Training employees on their effective use. Here’s what you need to be doing: 1 — Align on an AI Assistant (ChatGPT, Perplexity, Claude, etc.) Start by choosing one of the key AI assistants—whether it’s ChatGPT, Claude, or Perplexity—or a combination of them. The great news is that all of these now offer enterprise-grade plans that help you manage your teams efficiently. Plus, they come with major certifications like SOC 2, GDPR, CCPA, and CSA Star, ensuring compliance and security for your business. 2 — Make AI Part of Your Team’s Daily Toolkit Make it clear across your company: just as everyone uses a computer, email, PowerPoint, or Excel daily, AI assistants are going to be a prerequisite for everyday work. Part of becoming an AI-powered organization is ensuring these tools are integrated into everyone’s daily routine. 3 — Organize Structured Training Set up a comprehensive training program that teaches your employees how to work effectively with these tools. Focus on prompt engineering, real use cases, and practical examples. Just as important, provide clear guidelines on what not to do—such as entering sensitive IP or customer/employee information—to ensure proper usage and avoid risks. There’s a lot of FOMO out there, and many companies are rushing to figure out how to implement AI projects. But a prerequisite to all of this is having your workforce turbocharged and powered by AI assistants. Whether or not you end up building your own AI-powered features, this will help boost your team’s overall productivity. It will also build the familiarity and intuition your team will need for working with AI-powered services—or vendors who are leveraging this technology. All in all, it’s a win-win: a low-effort, low-cost, easy way to get started with AI adoption and transformation.

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!

Are you grappling with how to integrate #GenAI into your daily work? The AI Integration Framework might just be the keys you need to unlock this new technology. When I developed this framework, my goal was to empower individuals, teams, and organizations to intentionally incorporate AI by starting with their own tasks. Whether you’re an AI novice or a seasoned professional, the AI Integration Framework helps identify the tasks only you can do, the ones AI can handle for you, and - most excitingly - the work where you and AI can collaborate to create exceptional results. Effectively integrating AI into our days means working at higher quality, in less time, with less mental strain, and with more enjoyment. This model helps you spot where and how. In this article, I dive into the three categories of work: 🙋♂️ Human Exclusive Tasks: The uniquely human, high-touch work AI can’t replicate. This is My Work. 🤖 AI Automation Potential: Tasks AI can do independently, freeing you for higher-value work. This is “For Me” Work. 🤝 AI Collaboration Opportunities: The "sweet spot" where AI becomes a true partner, enhancing quality, efficiency, and enjoyment. This is “With Me” Work. The AI Integration Framework is not just about understanding AI; it’s about owning your AI journey. It’s about reshaping the narrative from "What will AI do to me?" to "What will I do with AI?" I’ve included practical steps, reflective questions, and real-world examples to help you start applying this framework today. Whether you’re exploring AI’s role in change management, team leadership, or strategic decision-making, this framework offers a foundation for thoughtful integration. Enjoy! And remember, sharing is caring, especially with articles that help you unlock AI 😉

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

3 AI USE CASES YOUR ORGANIZATION CAN IMPLEMENT TODAY Forget the AI hype cycle—while everyone's talking about tomorrow's possibilities, forward-thinking organizations are already gaining ground with practical applications. Here are three AI implementations you can launch this week: 1. AI-Powered Meeting Analysis ➤ Deploy an AI agent to record, transcribe, and analyze team discussions—identifying action items, tracking decisions, and ensuring all voices are heard. 2. Custom Knowledge Base AI ➤ Build an AI partner trained on your organization's internal documents and processes. New team members get up to speed faster, and experts focus on high-value work instead of answering repetitive questions. 3. Collaborative Strategy Development ➤ Create a virtual strategy team with AI personas designed for different thinking styles—one analyzing data, another challenging assumptions, a third generating alternatives. The organizations that will dominate aren't waiting to see how AI develops—they're actively building the hybrid workforce today. Across industries, companies are reimagining collaboration between humans and AI, finding ways to augment team capabilities rather than simply replacing tasks. 💡What AI applications are you exploring? I'd love to hear your experiences. #ArtificialIntelligence #FutureOfWork #Strategy #business #innovation

I've been deeply inspired by new research from my brilliant colleagues and friends Karim Lakhani and Hila Lifshitz-Assaf, alongside Ethan Mollick at Wharton, P&G, and others: The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise. This work gets to the heart of something I’ve been exploring for years—the blurring boundaries between disciplines and the potential for technology to unlock new forms of human creativity and collaboration. What’s so powerful here is not just the scale of impact AI is having, but the shape of that impact. A couple of charts from the study really hit home: Performance Distribution Teams using AI were three times more likely to deliver top 10% solutions. Let that sink in. We’re not just talking about incremental improvement—we’re seeing a fundamental shift in the curve. The whole distribution moves up. Expertise Equalization Perhaps even more profound—individuals (even novices) using AI were able to match or outperform seasoned experts. The old silos between technical and commercial capabilities? Gone. AI is flattening hierarchies and expanding what’s possible for everyone. But it’s not just about outcomes—it’s about experience. Participants reported more excitement, less anxiety, and stronger emotional connection with their work. That matters. A few takeaways that stood out: - Teams with AI were three times more likely to reach top-tier results - Individuals using AI matched team performance at 16% faster speed - Silos between specialties dissolved—more integrated, well-rounded solutions - Emotional boost: higher excitement, lower stress For me, the big idea here is the democratization of expertise. This is about more than automation—it’s about amplification. It’s about empowering people, regardless of where they sit on the org chart, to contribute meaningfully in ways they couldn’t before.   It’s exciting to see this kind of validation for the themes we’ve been working on for decades: open talent, distributed innovation, and the power of creative collaboration. This isn’t just the future of work—it’s already happening. Here's a link to the paper: https://lnkd.in/g3KiQuw4

Throwing AI tools at your team without a plan is like giving them a Ferrari without driving lessons. AI only drives impact if your workforce knows how to use it effectively. After: 1-defining objectives 2-assessing readiness 3-piloting use cases with a tiger team Step 4 is about empowering the broader team to leverage AI confidently. Boston Consulting Group (BCG) research and Gilbert’s Behavior Engineering Model show that high-impact AI adoption is 80% about people, 20% about tech. Here’s how to make that happen: 1️⃣ Environmental Supports: Build the Framework for Success -Clear Guidance: Define AI’s role in specific tasks. If a tool like Momentum.io automates data entry, outline how it frees up time for strategic activities. -Accessible Tools: Ensure AI tools are easy to use and well-integrated. For tools like ChatGPT create a prompt library so employees don’t have to start from scratch. -Recognition: Acknowledge team members who make measurable improvements with AI, like reducing response times or boosting engagement. Recognition fuels adoption. 2️⃣ Empower with Tiger Team Champions -Use Tiger/Pilot Team Champions: Leverage your pilot team members as champions who share workflows and real-world results. Their successes give others confidence and practical insights. -Role-Specific Training: Focus on high-impact skills for each role. Sales might use prompts for lead scoring, while support teams focus on customer inquiries. Keep it relevant and simple. -Match Tools to Skill Levels: For non-technical roles, choose tools with low-code interfaces or embedded automation. Keep adoption smooth by aligning with current abilities. 3️⃣ Continuous Feedback and Real-Time Learning -Pilot Insights: Apply findings from the pilot phase to refine processes and address any gaps. Updates based on tiger team feedback benefit the entire workforce. -Knowledge Hub: Create an evolving resource library with top prompts, troubleshooting guides, and FAQs. Let it grow as employees share tips and adjustments. -Peer Learning: Champions from the tiger team can host peer-led sessions to show AI’s real impact, making it more approachable. 4️⃣ Just in Time Enablement -On-Demand Help Channels: Offer immediate support options, like a Slack channel or help desk, to address issues as they arise. -Use AI to enable AI: Create customGPT that are task or job specific to lighten workload or learning brain load. Leverage NotebookLLM. -Troubleshooting Guide: Provide a quick-reference guide for common AI issues, empowering employees to solve small challenges independently. AI’s true power lies in your team’s ability to use it well. Step 4 is about support, practical training, and peer learning led by tiger team champions. By building confidence and competence, you’re creating an AI-enabled workforce ready to drive real impact. Step 5 coming next ;) Ps my next podcast guest, we talk about what happens when AI does a lot of what humans used to do… Stay tuned.