Key Findings on AI in the Workplace

We’ve all heard about AI’s potential to boost productivity. But what truly matters to me is whether it’s making work better for the people who show up every day. At Cisco, our People Intelligence team, in collaboration with IT, has been exploring this very topic, and the findings are fascinating. Here are five key insights from our research that leaders should take seriously: 1. Leaders are key to adoption. At Cisco, employees are 2x more likely to use AI if their direct leader uses it. 2. Generic AI training doesn’t work. Role-specific, practical training accelerates AI use. 3. Confidence gaps exist among senior leaders. Directors at Cisco often feel less confident with AI than mid-level employees, underscoring the need for tailored support at all levels. 4. Employee autonomy fuels adoption. Hybrid work environments are powerful accelerators for AI adoption, while mandates can hinder it. Employees who voluntarily go to the office are more likely to use AI, while those who are required to work on-site have lower adoption. 5. AI use is linked to employee well-being, but the relationship is complex, with both benefits and trade-offs that require thoughtful navigation. This is just the beginning. Next, we’re looking at how AI is transforming the way teams operate. For now, one thing is clear, employees who use AI aren’t just more productive. They’re also more engaged, better aligned with company strategy, and empowered to focus on meaningful work. #AIAdoption #EmployeeExperience #FutureOfWork

A new study of 1,488 full-time U.S. workers reveals a striking paradox at the heart of the AI productivity promise: the same tools designed to make work easier may be making it cognitively harder. Researchers have identified a phenomenon they call "AI brain fry" — acute mental fatigue arising from the intensive oversight and management of AI systems — and found it carries measurable costs for decision quality, error rates, and employee retention. The study draws a critical distinction between two separate stress pathways. When AI absorbs repetitive, low-value tasks, workers experience lower burnout and greater engagement. But when AI demands constant human supervision — particularly across multiple simultaneous agents — it can push workers past their cognitive limits, producing a qualitatively different strain that existing burnout surveys rarely capture. These findings arrive at a pivotal moment, as companies increasingly measure performance through AI activity metrics and task employees with overseeing complex, multi-agent workflows. The research offers both a diagnosis and a roadmap for leaders who want the productivity gains of AI without the cognitive casualties. This study offers one of the most rigorous examinations to date of what intensive AI use actually does to the workers deploying it. Its core insight is deceptively simple: AI is not a monolith. The same category of technology can simultaneously reduce burnout and produce acute cognitive exhaustion, depending entirely on how it is deployed. The organizations most likely to benefit from AI are not those that push adoption hardest, but those that deploy it most thoughtfully — protecting the cognitive capacity that makes high-quality human judgment possible in the first place. The tools are powerful. So are the brains that still need to guide them. Ref: HBR

The value of Humans + AI collaboration in the real world: an academic study of 776 R&D professionals at Procter & Gamble revealed not just substantial performance gains from AI, but a host of other gains, including in emotional state. Some of the stand out insights from the research paper (link in comments): 🚀 AI + teams unlock top-tier innovation. Teams using AI were 9.2 percentage points more likely to produce top 10% solutions compared to the 5.8% baseline—making them about three times more likely to generate standout ideas. This effect was not seen for individuals using AI, highlighting a unique benefit in combining AI with human collaboration. ⏱️ AI makes work faster and more detailed. Individuals with AI completed their work 16.4% faster, and teams with AI were 12.7% faster than their non-AI counterparts. At the same time, AI-enabled groups produced significantly longer and more detailed solutions, with higher average quality scores. 🧩 AI dissolves functional silos. Without AI, Commercial and R&D professionals proposed solutions aligned with their functional backgrounds—market-oriented vs. technical. With AI, this gap disappeared: both groups generated more balanced ideas, regardless of their original specialization. This pattern held across individuals and teams. 📈 AI lifts less experienced employees to team-level performance. Employees whose core job did not include product development performed significantly worse in the control conditions. However, when these non-core employees worked with AI, their performance matched that of teams containing core-role employees. 😊 AI improves emotional states during work. Participants using AI reported significantly higher increases in positive emotions—such as excitement, energy, and enthusiasm—and lower increases in negative emotions like anxiety and frustration. Individuals with AI experienced a 0.457 standard deviation increase in positive emotions, and AI-enabled teams saw an even larger 0.635 boost. 🏢 AI challenges traditional assumptions about team structures. The study found that individuals with AI performed as well as human teams without AI, while AI-enabled teams were significantly more likely to produce top-decile solutions. The authors conclude that this challenges long-standing assumptions about the necessity and structure of collaboration. They suggest organizations may need to rethink how they compose teams and allocate expertise in an AI-integrated environment.

Check out this massive global research study into the use of generative AI involving over 48,000 people in 47 countries - excellent work by KPMG and the University of Melbourne! Key findings: 𝗖𝘂𝗿𝗿𝗲𝗻𝘁 𝗚𝗲𝗻 𝗔𝗜 𝗔𝗱𝗼𝗽𝘁𝗶𝗼𝗻 - 58% of employees intentionally use AI regularly at work (31% weekly/daily) - General-purpose generative AI tools are most common (73% of AI users) - 70% use free public AI tools vs. 42% using employer-provided options - Only 41% of organizations have any policy on generative AI use 𝗧𝗵𝗲 𝗛𝗶𝗱𝗱𝗲𝗻 𝗥𝗶𝘀𝗸 𝗟𝗮𝗻𝗱𝘀𝗰𝗮𝗽𝗲 - 50% of employees admit uploading sensitive company data to public AI - 57% avoid revealing when they use AI or present AI content as their own - 66% rely on AI outputs without critical evaluation - 56% report making mistakes due to AI use 𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀 𝘃𝘀. 𝗖𝗼𝗻𝗰𝗲𝗿𝗻𝘀 - Most report performance benefits: efficiency, quality, innovation - But AI creates mixed impacts on workload, stress, and human collaboration - Half use AI instead of collaborating with colleagues - 40% sometimes feel they cannot complete work without AI help 𝗧𝗵𝗲 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗚𝗮𝗽 - Only half of organizations offer AI training or responsible use policies - 55% feel adequate safeguards exist for responsible AI use - AI literacy is the strongest predictor of both use and critical engagement 𝗚𝗹𝗼𝗯𝗮𝗹 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 - Countries like India, China, and Nigeria lead global AI adoption - Emerging economies report higher rates of AI literacy (64% vs. 46%) 𝗖𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗟𝗲𝗮𝗱𝗲𝗿𝘀 - Do you have clear policies on appropriate generative AI use? - How are you supporting transparent disclosure of AI use? - What safeguards exist to prevent sensitive data leakage to public AI tools? - Are you providing adequate training on responsible AI use? - How do you balance AI efficiency with maintaining human collaboration? 𝗔𝗰𝘁𝗶𝗼𝗻 𝗜𝘁𝗲𝗺𝘀 𝗳𝗼𝗿 𝗢𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀 - Develop clear generative AI policies and governance frameworks - Invest in AI literacy training focusing on responsible use - Create psychological safety for transparent AI use disclosure - Implement monitoring systems for sensitive data protection - Proactively design workflows that preserve human connection and collaboration 𝗔𝗰𝘁𝗶𝗼𝗻 𝗜𝘁𝗲𝗺𝘀 𝗳𝗼𝗿 𝗜𝗻𝗱𝗶𝘃𝗶𝗱𝘂𝗮𝗹𝘀 - Critically evaluate all AI outputs before using them - Be transparent about your AI tool usage - Learn your organization's AI policies and follow them (if they exist!) - Balance AI efficiency with maintaining your unique human skills You can find the full report here: https://lnkd.in/emvjQnxa All of this is a heavy focus for me within Advisory (AI literacy/fluency, AI policies, responsible & effective use, etc.). Let me know if you'd like to connect and discuss. 🙏 #GenerativeAI #WorkplaceTrends #AIGovernance #DigitalTransformation

Despite 83% adoption in Danish workplaces, AI chatbots have not moved the needle on productivity or earnings... Everyone's talking about AI transforming the workplace, but this rigorous new study out of Denmark tells a more nuanced story. Over 25,000 workers across 11 occupations (including HR) were surveyed in late 2023 and 2024. The findings? Despite rapid adoption of AI chatbots, the actual effects on the labor market are minimal. There was no significant impact on earnings, hours worked, or employment, not even among daily users. What stood out to me: 1. Employer-led adoption matters. Many firms have not reorganized workflows or provided meaningful training or tools. Time savings and new task creation were 10–40% higher when employers encouraged use or offered training. But AI chatbots also created new job tasks for 8.4 percent of workers, including people who did not use the tools, thus offsetting potential time savings. 2. RCT hype vs. workplace reality. The productivity gains seen in controlled studies don’t hold up when applied more broadly. Teachers, financial advisors, and accountants report far lower benefits. Most workers spend just 5–6% of their time with chatbots. 3. Economic outcomes are weak. Even when productivity improves, it rarely translates into higher pay for employees. For HR, the authors found that HR benefits modestly from AI chatbots (in content drafting and task support) but the gains are highly dependent on employer involvement. And before you say that this study must be wrong and AI does deliver efficiencies: The authors point out that real transformation requires more than just new tools; it needs real workplace change. But it also shows that gains are not spread evenly across the workforce, and some people might have more tasks due to AI, instead of less. The study is a sober, evidence-based counterpoint to the “AI will change everything overnight” narrative and a must-read for anyone thinking seriously about the future of work. I guess it's time to prepare that AI Transformation! I’ve attached the full study—worth your time if you care about the future of workers, productivity, and pay. #futureofwork #ai

This is AI at Work. Over the past few weeks, I’ve joined BCG X teams worldwide to test cutting-edge #GenAI tools and reimagine how we can work together. For BCG X and our clients, true AI adoption is about investing in people to learn new ways of working — a priority many organisations overlook. I cover this in our latest report, AI at Work. The report, co-authored with Vinciane Beauchene, Nipun Kalra and David Martin, draws on data from over 10,600 respondents across global markets to understand how #AI is used in the workplace and where adoption is falling short. Here are five key insights: 1. AI is now part of our daily work lives. While over three quarters of managers and leaders are regular AI users, adoption among frontline employees has stalled at 51%. 2. Proper training, leadership support, and access to the right tools can break this ceiling. Yet only 36% of respondents are satisfied with their AI training. 3. The Global South is again showing higher adoption of AI. India is leading the pack with 92% of regular users. 4. The next frontier: from adoption to value with end-to-end redesign. One-half of respondents say their company is starting to reshape processes. These companies invest more in their people — and it pays off. 5. AI agents are not widely deployed. In practice, only 13% see agents integrated into broader workflows. The report shares deeper insights and offers strategic advice for leadership. 📖 Read the report: https://on.bcg.com/4erQWiq #BCGX #AIatWork

A new study released today by OpenAI and Harvard economists draws on anonymized data from over 700 million weekly ChatGPT users worldwide. It offers the first large-scale, privacy-preserving look at how people actually rely on generative AI for sophisticated reasoning and decision support. Five findings leap out at me: ⭐ Decision support is exploding. Almost half of all messages, and now more than half, are people asking for guidance, advice, or analysis. The real economic value lies here: AI as a thinking partner. ⭐ Workplace reasoning is front and center. Among work-related messages, 56% involve “doing” tasks, and nearly three-quarters of those are writing tasks where the model is helping to solve problems or craft strategy, not just generate boilerplate. ⭐ These tasks match the core of knowledge work. Over 45% of all messages map to O*NET work activities such as “Getting Information,” “Interpreting Information,” and “Making Decisions & Solving Problems.” ⭐ Quality rises with complexity. Interactions in which people ask the model to reason or advise consistently rank highest in user satisfaction. ⭐ AI is becoming a teacher. Roughly 10% of all messages are tutoring or teaching requests, a striking signal that people already trust AI to explain and guide. And for those driving enterprise transformation, the same research adds a powerful call to action: ⚡ ChatGPT adoption has reached 10% of the world’s adult population, with users sending 2.5 billion messages daily, one of the fastest technology diffusions in history. ⚡ Even as personal use grows, absolute work-related usage has more than tripled in a year, proving that employees already incorporate AI into their daily jobs, often before formal corporate programs. ⚡ The highest-value interactions, decision support, strategic writing, and problem-solving are precisely the activities that define knowledge-intensive industries. For enterprises and their advisors, this is more than a trend; it’s an urgent signal. The next competitive edge isn’t just automating routine tasks. It’s embedding AI as a true co-pilot for human judgment, from strategic planning and R&D to regulated decision environments. If you’re shaping an AI strategy today, these data points make the case clear: your teams and your customers are already treating AI as a reasoning partner. The question isn’t whether they will... It’s whether your enterprise is ready to design for it and become truly AI-first. Read the paper here: http://bit.ly/4na2eeA

🚀 Excited to share my latest Fortune column on truly groundbreaking academic work from my co-authors Professor Karim Lakhani and Fabrizio Dell'Acqua at Digital Data Design Institute at Harvard (D^3), where I serve as an executive fellow. This remarkable field experiment with 776 Procter & Gamble professionals fundamentally challenges what we thought we knew about teamwork. The research reveals the emergence of the "cybernetic teammate"—AI that doesn't just assist but actively participates in collaboration. Three breakthrough findings: 1. AI Can Replicate Team Benefits Individuals working with AI achieved nearly 40% performance gains—matching traditional two-person teams. AI is providing the same collaborative benefits we've long attributed to human teamwork. 2. Cross-Functional AI Teams Generate Breakthrough Innovation AI-augmented cross-functional teams were 3x more likely to produce top 10% solutions. This isn't marginal improvement—it's a multiplicative effect that neither human-only teams nor AI-enabled individuals could achieve alone. 3. AI Breaks Down Silos (For Real This Time) R&D specialists with AI proposed commercially viable solutions. Commercial professionals developed technically sound approaches. AI acted as a bridge, enabling each team member to think holistically across functions—achieving the "silo breaking" that leaders have struggled to accomplish through org chart reshuffles. Bonus finding: AI collaboration increased positive emotions by 64% in teams. This isn't cold, mechanical work—it's energizing and engaging. At Seven2, we're translating this research into practice with our portfolio companies, building these AI-augmented cross-functional teams to drive innovation and competitive advantage. This is the future of collaborative work—not AI replacing humans, but human-AI ensembles that combine the best of both worlds. Read the full analysis: https://lnkd.in/ef3f3pED #AI #Innovation #HBS #D3Institute #FutureOfWork #PrivateEquity #TeamDynamics

AI’s impact on the workforce is no longer theoretical. New data from Anthropic provides one of the clearest pictures yet of how AI is actually being used in professional roles today. By analysing millions of real-world interactions with Claude AI, the study moves beyond speculation and reveals where AI is embedded in work, where its adoption remains low, and whether it is augmenting or automating professional tasks. Some key findings: 🔹 AI is now performing 25% or more of the tasks in 36% of occupations. 🔹 57% of AI use is augmentation, meaning workers use AI as a collaborator, refining and improving their work. 🔹 43% of AI use is automation, where AI completes tasks with little human involvement—raising questions about long-term shifts in work. 🔹 AI’s adoption is highest in mid-to-high-wage professions, particularly in software engineering, content creation, and data analysis. 🔹 Industries requiring physical labour or complex interpersonal skills see much lower AI usage—for now. This data brings important implications for education and workforce development. Rather than broad assumptions about AI’s role in work, institutions now have a clearer sense of where AI is being used, where it isn’t, and how qualifications may need to adapt. So, what does this mean for workforce preparation? The findings suggest that AI fluency will be essential in some fields, while in others, the focus must remain on human-led expertise—critical thinking, ethical reasoning, and leadership. The full article unpacks these insights further, exploring what this data means for jobs, education, and the future of work. 🔹 #AI 🔹 #FutureOfWork 🔹 #AIinEducation 🔹 #WorkforceDevelopment 🔹 #EdTech

A new Harvard Business School study involving 700+ professionals at Procter & Gamble reveals AI is reshaping how teams work—moving to what researchers call a “cybernetic teammate.” Teams using AI (specifically ChatGPT-4 and 4o) consistently outperformed others, producing better solutions faster, while also fostering more cross-functional collaboration. AI broke down traditional silos, allowing people to contribute outside their usual expertise and enabling individuals to handle tasks that previously required entire teams. Interestingly, while AI users felt less confident, they did significantly better work and reported more positive emotions—hinting at a future where AI not only accelerates output but also improves the work experience. Key takeaway: Organizations that treat AI as just another tool are underestimating its impact. This study suggests we’re only seeing the floor of AI’s potential. As adoption and skills mature, the performance gap will widen—fast. The divide is no longer between teams—it's between those who embrace AI and those who don't. #ai