The Impact of AI on Workplace Performance Metrics

Two recent research reports examining AI's impact on teamwork and organizational structures at US companies provide some interesting insights that can also inform our approach to GenAI adoption in K12 and HE. A recent article by Ethan Mollick breaks down findings from a randomized controlled trial at Procter & Gamble examining how AI affects team performance. Key points from the study: • AI significantly boosted performance - individuals with AI performed as well as two-person teams without AI, and AI-enabled groups worked 12-16% faster while producing longer, more detailed solutions • Teams using AI performed best overall and were more likely to produce exceptional solutions • Workers using AI reported higher positive emotions and lower negative emotions compared to non-AI groups McKinsey's latest Global Survey on AI examines how organizations are structuring their AI deployment and creating value from it. Key points from the study:   • 78% of organizations now use AI in at least one business function • Only 21% of organizations have fundamentally redesigned workflows for AI, though this drives the biggest impact on revenue • Larger companies lead in implementing best practices like establishing dedicated AI teams, organization-wide adoption road maps, and AI literacy programs • 61-70% report revenue increases and cost reductions in business units using AI, though enterprise-wide impact remains limited Both studies point to the same conclusion: when GenAI is intentionally adopted there can be large positive impacts that go beyond productivity gains. We are particularly excited about how GenAI can act as a teammate for those that do not have access to a support network and its potential applications in high school and college classrooms. Links to the studies in the comments. AI for Education #GenAI #AI #teamwork

AI, something magic, profit? 85% of organizations are either mandating or encouraging the use of #AI tools to improve #productivity, according to recent research from Upwork. So how’s it going? Microsoft data on the use of CoPilot for M365 shows some early, modest results in terms of activity, and no clear impact on outcomes (see p2): 🔹 Email: Copilot users read 11% fewer emails, spent just 4% less time. Not huge, not zero. 🔹 Docs: users edited 10% more documents, spreadsheets and Powerpoints, noting that editing doesn’t tell you anything about time spent or quality. 🔹 Meetings: 10 of 47 companies saw meetings drop , but 14 saw an increase (which might be shifting meetings into Teams to get Copilot summaries). Activity isn’t the same thing as results. Part of the issue is a lack of support, and pressure to be productive without the space to experiment and try new things. Upwork found only 26% of companies are providing employees with any training, for example. Besides training, and investing in time for managers and teams to experiment with the tools together, the answer might be to instead focus on specific use cases — and focus on quality. #GenAI’s impact is very dependent on application to specific activities within functions and importantly might raise quality more than just efficiency. Reading through Microsoft’s recent aggregation of broader AI research, some observations: 🔸 Customer service reps resolve 14% more cases per hour, but also rate the impact of GenAI on quality just as high as productivity. 🔸 Security professionals write incident reports that are 7% more accurate and 49% more likely to include key facts. 🔸 Sales reps answering customer questions can respond faster, and are also 25 percentage points more accurate. 🔸 Training: a bot capturing insights from a webinar allows people taking a quiz on the content to be 39% more accurate. If it was delivered outside their native language, they’re 85% more accurate! All of this requires even more investment in getting data that's underneath AI tools to be accurate. But it requires a different lens than just handing out tools and saying that we expect you to get more productive. Long term, GenAI will change businesses dramatically. The investments you make now in training, making space for experimentation and engaging people in the upside, the faster you'll get there. 🔗 Check out the full report from Microsoft in comments, along with a link to Kelly Monahan, Ph.D. and team's work on AI at Upwork. #FutureOfWork #tech #technology #collaboration

Just out: Quantifying the impact of #genAI on job performance, by Erik Brynjolfsson & team: "Access to AI assistance increases worker productivity, as measured by issues resolved per hour, by 15% on average, with substantial heterogeneity across workers. The effects vary significantly across different agents. Less experienced and lower-skilled workers improve both the speed and quality of their output, while the most experienced and highest-skilled workers see small gains in speed and small declines in quality. We also find evidence that AI assistance facilitates worker learning and improves English fluency, particularly among international agents. While AI systems improve with more training data, we find that the gains from AI adoption are largest for moderately rare problems, where human agents have less baseline experience but the system still has adequate training data. Finally, we provide evidence that AI assistance improves the experience of work along several dimensions: customers are more polite and less likely to ask to speak to a manager." Open access: https://lnkd.in/d4UecpnQ