How AI can Boost Productivity and Security

"AI is going to do to knowledge work what Lean did to manufacturing." – Satya Nadella This quote has been stuck in my head since I first heard it. The more I think about it, the clearer it becomes: Lean eliminated waste, optimized workflows, and empowered workers to operate at a higher level. AI is doing the same for knowledge work, not by replacing people, but by shifting their focus to higher-impact tasks. Here’s where the parallels stand out to me—and why I think you should pay attention: ✅ Eliminating Waste - Lean cut unnecessary inventory and idle time. AI is removing repetitive knowledge tasks that were once too unstructured to automate. ➡️ Instant meeting summaries ➡️ Automated data entry ➡️ Seamless report generation 🤔 What changes? Roles shift. Companies will need to redefine job responsibilities, redeploy talent, and rethink required skills. ✅ Just-in-Time Insights - Lean production meant the right materials, at the right time. AI can deliver insights exactly when needed. ➡️ No more waiting for monthly reports—benchmarking happens instantly. ➡️ Marketing teams can approve AI-recommended campaign updates in real time. 🤔 What changes? Decision-making accelerates. Companies will need flatter org structures and leaders who are comfortable with continuous iteration instead of rigid planning cycles. ✅ Continuous Improvement - Lean championed small, ongoing improvements. AI now enables continuous, real-time enhancements. ➡️ Writers get instant clarity recommendations. ➡️ Sales teams receive AI-driven coaching on the fly. ➡️ Customer interactions improve through proactive suggestions. 🤔 What changes? A culture of experimentation becomes essential. Companies that reward iteration and learning will move faster than those that don’t. ✅ Empowered Workers- Lean gave factory workers more control over processes. AI is doing the same for knowledge workers by equipping them with expert-level insights and decision-making capability. ➡️ Customer support reps can resolve complex issues without escalation. ➡️ Employees make better, faster decisions without waiting for approvals. 🤔 What changes? Employee expectations shift. More autonomy means leaders must focus on coaching over command-and-control management. We’re at the start of a major transformation. At Dropbox, we’re building Dash to help knowledge workers focus on high-impact work, not busywork. And tomorrow, I'm giving a talk at the Gartner symposium in Dallas to share what we've learned tackling these challenges head on. Which Lean principles feel most relevant to how AI is changing your work? Let me know down below (and if you're in Dallas, come say hi!).

CISOs and security teams,   Microsoft just changed the landscape of AI security and how easy it is to secure it and approve it.   I normally don't push security folks to these kinds of events/announcements, but this one is a big change for security. I strongly urge security leaders and practitioners to see this themselves because these will change how security teams can mitigate AI risk (and also fundamentally change how people do work in general). Two key things caught my attention: 1. New product (Bing Chat Enterprise) that is built on ChatGPT that is designed for enterprises (inherits security/privacy/compliance policy, follows existing permissions, data is logically isolated and protected within Microsoft 365 tenant, verifiable answers, text/image interactions and coverage, etc.). This will also be very widely available (included at no additional cost in Microsoft 365 E3, E5, Business Standard and Business Premium). https://lnkd.in/eWQTBvS4   2. Content Safety features that provide powerful features to mitigate common AI risks (see screenshot) https://lnkd.in/exdZw4xA   Do these magically mitigate all AI risk? No Will it help many organizations get started on AI safely? Yes Will it increase demand on security to approve AI usage from business and technology colleagues? Yes! The productivity demos very impressive and included having AI compare a proposed project against existing products in the market and generating SWOT analysis in seconds. These tasks are critical to business decision makers and normally take hours/days/weeks for experts to build. I expect a lot of job tasks will be transformed by AI significantly in the next few years (and fast!)   I can't find the full keynote recording link at the moment, but this is a link to all the announcements with demo videos, etc. https://lnkd.in/emru8U5w

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

Excited to share insights from Microsoft’s study on "Generative AI and Security Operations Center Productivity." This first-of-its-kind research reveals how generative AI is transforming cybersecurity operations.   Key findings: 🔹 30%+ reduction in Mean Time to Resolution for security incidents, consistently demonstrated across various modeling scenarios 🔹 Significant cost-saving potential: SOC analysts currently spend ~3 hours daily resolving incidents, contributing to a $3.3B cost in the U.S. alone 🔹 Enhanced threat identification accuracy and speed, allowing analysts to handle more incidents in less time   These findings underscore the transformative potential of tools like Microsoft Security Copilot in reducing security incident resolution times and improving SOC efficiency. Looking ahead, I'm excited to see how these GAI tools continue to evolve and strengthen the cybersecurity landscape. #Cybersecurity #MicrosoftSecurity #GenAI #Copilot   Read the full study here: