How AI is Changing Daily Work Tasks

AI is reshaping not just what we build, but how we build. It was a big topic of conversation at my team’s recent town hall. We know AI has played a significant role in writing code. In fact, much of the code behind Visa Intelligent Commerce was generated by AI. But the real story is broader: AI is becoming a core competency for every function, not just engineering. I use AI daily—for synthesis, planning and speed. Whether I’m preparing for a meeting or exploring a new concept, AI helps me move faster and think more clearly. It’s replaced traditional search in my workflow and unlocked new levels of productivity. And I’m seeing the same across our teams. AI is reducing their time spent on repetitive tasks and redirecting that energy toward client engagement, problem solving and innovation. From developing design personas to writing developer documentation, we’re seeing time savings measured in weeks, not hours. Efficiency gains of 90+% not 10%. This isn’t about novelty—it’s necessity. The pace of innovation is accelerating, and it is time to sink or swim. The call to action is clear: every leader should be exploring and using AI to elevate their team’s impact today. Where are your biggest unlocks with AI?

AI is changing how we work. It's fundamentally reshaping team dynamics. From fluid roles to global collaboration, today’s team dynamics are evolving faster than ever. Understanding these 12 shifts isn’t optional; it’s critical to staying agile, competitive, and future-ready: 1/ From Fixed to Fluid Roles ↳ Teams swap tasks based on AI proficiency ↳ Skills matter more than titles 💡 Pro tip: Create a team skills matrix that tracks both AI and human capabilities. 2/ From Knowledge Silos to Open Learning ↳ AI tools democratize expertise ↳ Everyone becomes a teacher-learner 💡 Pro tip: Set up a shared prompt library where teams document their AI breakthroughs. 3/ From Linear to Parallel Processing ↳ Multiple projects run simultaneously ↳ AI handles routine tasks while teams focus on strategic thinking 💡 Pro tip: Use AI project managers to track parallel workstreams. 4/ From Competition to Collaboration ↳ Success = enhancing AI outputs ↳ Shared prompt libraries 💡 Pro tip: Create weekly "AI win sharing" sessions where teams present their best AI solutions. 5/ From Meetings to Async Intelligence ↳ AI summarizes discussions ↳ Continuous feedback loops 💡 Pro tip: Use AI meeting summaries as living documents that teams can enhance asynchronously. 6/ From Individual to Collective Problem-Solving ↳ AI provides initial solutions ↳ Teams refine together 💡 Pro tip: Start problems with AI-generated solutions, then use human wisdom to enhance them. 7/ From Status Updates to Strategy Sessions ↳ AI handles progress tracking ↳ Meetings focus on innovation 💡 Pro tip: Automate status reports with AI. Save meeting time for strategic discussions only. 8/ From Fixed Skills to Learning Networks ↳ Continuous AI upskilling ↳ Rapid knowledge sharing 💡 Pro tip: Rotate "AI champions" monthly to spread expertise across the team. 9/ From Task Completion to Value Creation ↳ AI handles the routine ↳ Teams focus on innovation 💡 Pro tip: Track time saved by AI and reinvest it in innovation projects. 10/ From Hierarchical to Neural Networks ↳ Expertise flows freely ↳ Innovation comes from everywhere 💡 Pro tip: Create open channels where anyone can share AI innovations. 11/ From Risk Aversion to Rapid Testing ↳ AI reduces experiment costs ↳ Faster iteration cycles 💡 Pro tip: Set up an "AI sandbox" where teams can experiment. 12/ From Individual Metrics to Team Impact ↳ Shared success metrics ↳ Focus on team outcomes 💡 Pro tip: Create team-based AI efficiency scores instead of individual performance metrics. These shifts are building a new foundation for how teams think, collaborate, and innovate. The key is to adopt change intentionally, not all at once. Start where your team has the most momentum, and let AI become a catalyst for stronger, smarter collaboration. Which team dynamic shift are you experiencing most strongly? Share below 👇 ♻️ Repost if your team is navigating these changes. Follow Carolyn Healey for more like this.

𝐀𝐈 𝐈𝐬 𝐀𝐥𝐫𝐞𝐚𝐝𝐲 𝐂𝐡𝐚𝐧𝐠𝐢𝐧𝐠 𝐖𝐨𝐫𝐤—𝐇𝐞𝐫𝐞’𝐬 𝐖𝐡𝐚𝐭 29 𝐘𝐞𝐚𝐫𝐬 𝐢𝐧 𝐓𝐞𝐜𝐡 𝐇𝐚𝐬 𝐓𝐚𝐮𝐠𝐡𝐭 𝐌𝐞 After nearly three decades in the tech industry, I’ve seen game-changing transformations—from the early days of enterprise software to the rise of cloud computing, automation, and now AI. But what’s happening today with AI-driven workplace transformation is unlike anything before. Microsoft is leading this charge, and Microsoft Copilot is not just another tool—it’s an architect of efficiency, innovation, and strategic decision-making. Across industries, AI is not replacing people; it’s amplifying human potential and reshaping workflows in ways that were unimaginable a few years ago. The Real-World Impact of AI Across Key Business Functions: ✅ Customer Service: AI is reducing case resolution time by 11.5%, allowing teams to focus on complex problem-solving instead of repetitive queries. ✅ Sales: In some divisions, AI-powered insights have driven 9.4% higher revenue per seller—proof that intelligent automation enhances, not replaces, human expertise. ✅ Marketing: We’re seeing a 21.5% increase in conversion rates—AI is making data-driven personalization a reality at scale. ✅ Human Resources: AI-enhanced self-service tools now deliver 42% greater accuracy, giving HR leaders more time to focus on strategy and people development. ✅ Finance: A 60% reduction in case resolution time—AI is eliminating bottlenecks and enhancing decision-making in cash collections and financial operations. ✅ Legal: Even in the highly regulated legal space, AI is expected to reduce external regulatory spend by 5% by automating compliance and risk assessment. ✅ IT: AI-driven self-help tools have improved self-resolution rates by 36%, empowering employees while reducing IT workload. The Future of Work Isn’t About Automation—It’s About Augmentation The biggest lesson from 29 years in tech? Every major technological shift rewards those who adapt early and embrace change. This isn’t just about efficiency—it’s about reimagining the way we work. AI won’t take jobs; it will redefine roles. Leaders who harness AI as a collaborator—rather than fearing it—will drive the next wave of innovation. 🔹 The real differentiator in this AI-powered world? Your ability to think critically, lead with insight, and leverage AI as a force multiplier. So, are you ready to adapt? Let’s talk about how AI is impacting your work. Drop your thoughts below! ⬇️ #AI #FutureOfWork #Leadership #DigitalTransformation 

It’s easy to think of AI as a time-saver that streamlines workflows and accelerates output. But the deeper opportunity lies in how it’s reshaping the nature of work itself. A new study from Harvard Business School’s Manuel Hoffmann followed more than 50,000 developers over two years, with half using GitHub Copilot. The results were striking: developers shifted away from project management and toward the core work of coding. Not because someone told them to, but because AI made it possible. With less need for coordination, people worked more autonomously. And with time saved, they reinvested in exploration—learning, experimenting, trying new things. What we’re seeing here isn’t just productivity. It’s a shift in how work gets done and who does what. Managers may spend less time supervising and more time contributing directly. Teams become flatter. Hierarchies adapt. This is just one signal of how generative AI is changing our org charts and challenging us to rethink how we structure, support, and lead our teams. The future of work isn’t just faster. It’s more fluid. And if we get this right, it’s a whole lot more human. https://lnkd.in/gaUgXnRY

Over the past few weeks, I’ve had time to reflect — between AI briefing sessions, leading workshops, and teaching at LinkedIn offices in London. One question keeps coming up: “Will I still have a job?” It’s a fair question. The reports, social posts, and videos can be overwhelming — even frightening. But here’s what I’ve come to believe: -- AI isn’t replacing jobs outright. It’s replacing tasks. And that changes everything. In my role as Course Director at the CIM | The Chartered Institute of Marketing — and through my work with marketers, consultants, and business owners — I’ve seen the same shift again and again: Those who are moving forward are reframing their role. They’re not competing with AI — they’re learning how to work alongside it. Here’s how I break down the Human + AI relationship in practical terms: 👉 20% – Spark Ideas Use AI to generate ideas, explore angles, and overcome creative blocks. 👉 40% – Co-Pilot Mode Let AI support your process — drafting, outlining, and iterating while you steer. 👉 60% – Efficiency Booster AI automates and structures routine work so you can focus on higher-value thinking. 👉 80% – Heavy Lifter AI takes on the complexity. You bring the insight, oversight, and strategic direction. 👉 100% – Full AI Execution In some cases, AI completes the task. But the human still sets the brief, guides the tone, and makes the decisions. For Marketers, Consultants, and Business Owners, this is not the time to resist. It’s time to rethink your value, redistribute your time, and reimagine your workflows. Humans won’t be replaced.... But we will be expected to become smarter — by collaborating with AI. Of course, there’s a much bigger discussion to be had. This post is just one thought in that wider conversation. But it’s a good place to start. With Positivity, Imran. #AIinMarketing #MarketingLeadership #CharteredInstituteOfMarketing #FutureOfWork #AIMarketer

I used to pride myself on my lightning-fast IDE shortcuts. But now? The Tab key has taken over, mostly. AI coding assistants are completely transforming the way we code. Here’s how: Before: We typed out every line of code. Now: We review AI-suggested code. Before: We thought carefully before typing. Now: We think after reading AI suggestions. Before: We expressed ideas in code syntax. Now: We express them through prompts. Before: We spent hours Googling and scrolling StackOverflow. Now: We just ask the AI chat. Before: We debug errors manually. Now: We ask AI to debug and fix them. Before: We dreaded writing boilerplate code. Now: AI autocompletes them in seconds. Before: We asked colleagues for suggestions. Now: We switch between AI models. Before: We worked solo. Now: We pair with AI as our coding partner. Before: Writing tests and documentation felt like a chore. Now: It’s (hopefully) something we look forward to. 🤞🏼 AI isn’t just changing how we write code. It’s also changing how we approach and think about coding. What about you? How has AI transformed your coding workflow? Share your experiences in the comments below! 💬

AI is quietly crossing an important line. For a while, the conversation has been about how well AI can respond better answers, faster summaries, cleaner outputs but that phase is giving way to something more consequential. AI systems are starting to act on goals, not just prompts. This is what many are calling agentic AI systems designed to plan, coordinate, and execute multi-step tasks with limited human supervision. Not just drafting an email, but deciding when to send it. That shift matters because it changes how work is structured. When AI can: • break down objectives, • sequence actions, • and operate across tools, the role of humans starts to move upstream away from constant execution and toward judgment, direction, and oversight. This is why the conversation is moving beyond hype. The real question is no longer “What can AI generate?” It’s “What outcomes can AI responsibly own?” And that question cuts across roles. Founders will rethink delegation. Operators will redesign workflows. Creators will shift from production to curation. Strategists will spend less time compiling inputs and more time choosing priorities. The implication isn’t that AI replaces work. It’s that work itself becomes more about setting intent than managing steps. The real change isn’t how fast AI responds. It’s how independently it can start, sequence, and complete meaningful work and that’s the shift quietly gaining traction right now. #ArtificialIntelligence #FutureOfWork #AIAgents #ModernOrganizations #StrategicThinking

𝐇𝐨𝐰 𝐡𝐚𝐬 𝐀𝐈 𝐛𝐞𝐜𝐨𝐦𝐞 𝐩𝐚𝐫𝐭 𝐨𝐟 𝐦𝐲 𝐝𝐚𝐢𝐥𝐲 𝐥𝐢𝐟𝐞, 𝐛𝐨𝐭𝐡 𝐚𝐭 𝐰𝐨𝐫𝐤 𝐚𝐧𝐝 𝐚𝐭 𝐡𝐨𝐦𝐞? 𝐼 𝑟𝑒𝑐𝑒𝑛𝑡𝑙𝑦 𝑟𝑒𝑎𝑙𝑖𝑧𝑒𝑑 𝑡ℎ𝑎𝑡 𝐼 𝑎𝑚 ℎ𝑒𝑎𝑣𝑖𝑙𝑦 𝑟𝑒𝑙𝑦𝑖𝑛𝑔 𝑜𝑛 𝐴𝐼 𝑛𝑜𝑤, 𝑎𝑛𝑑 𝑡ℎ𝑒𝑟𝑒 𝑎𝑟𝑒 𝑡𝑎𝑠𝑘𝑠 𝑡ℎ𝑎𝑡 𝐼 𝑢𝑠𝑒𝑑 𝑡𝑜 𝑑𝑜 𝑚𝑎𝑛𝑢𝑎𝑙𝑙𝑦 𝑏𝑦 𝑚𝑦𝑠𝑒𝑙𝑓, 𝑏𝑢𝑡 𝑛𝑜𝑤 𝑡ℎ𝑜𝑠𝑒 𝑡𝑎𝑠𝑘𝑠 ℎ𝑎𝑣𝑒 𝑏𝑒𝑒𝑛 𝑡𝑎𝑘𝑒𝑛 𝑢𝑝 𝑏𝑦 𝐴𝐼 𝑐𝑜𝑚𝑝𝑙𝑒𝑡𝑒𝑙𝑦. 𝐴𝑛𝑑 𝐼 𝑡ℎ𝑖𝑛𝑘 𝑖𝑡'𝑠 𝑓𝑜𝑟 𝑡ℎ𝑒 𝑏𝑒𝑡𝑡𝑒𝑟 𝑜𝑛𝑙𝑦. 💥 Sharing some of the best examples here today in this post: -> At PhonePe, where I work as an Android Developer, I use "GitHub 𝐂𝐨𝐩𝐢𝐥𝐨𝐭" almost every day. It doesn’t just help with writing test cases—I rely on it for code completion, boilerplate cleanup, and even when I’m stuck thinking of edge cases or structuring a new feature. -> On days when I’m feeling drained, I turn on its agentic mode, and it genuinely helps me push through without burning out. Recently, I’ve also been exploring Firebase Studio's new AI features for testing and debugging. 𝑇ℎ𝑒𝑠𝑒 𝑡𝑜𝑜𝑙𝑠 𝑎𝑟𝑒 𝑠𝑡𝑖𝑙𝑙 𝑒𝑣𝑜𝑙𝑣𝑖𝑛𝑔, 𝑏𝑢𝑡 𝑡ℎ𝑒 𝑝𝑜𝑡𝑒𝑛𝑡𝑖𝑎𝑙 𝑖𝑠 𝑐𝑙𝑒𝑎𝑟: 𝑠𝑝𝑜𝑡𝑡𝑖𝑛𝑔 𝑏𝑢𝑔𝑠 𝑒𝑎𝑟𝑙𝑖𝑒𝑟, 𝑠𝑚𝑎𝑟𝑡𝑒𝑟 𝑐𝑟𝑎𝑠ℎ 𝑖𝑛𝑠𝑖𝑔ℎ𝑡𝑠, 𝑎𝑛𝑑 𝑒𝑣𝑒𝑛 𝑎𝑢𝑡𝑜𝑚𝑎𝑡𝑒𝑑 𝑡𝑒𝑠𝑡 𝑠𝑢𝑔𝑔𝑒𝑠𝑡𝑖𝑜𝑛𝑠. -> Apart from that, I’ve done multiple debugging sessions using ChatGPT, especially when I’m trying to untangle weird Compose UI issues or sudden crash logs. Sometimes, just talking it out with ChatGPT helps me see the bug from a new angle. 𝗕𝘂𝘁 𝗔𝗜 𝗱𝗼𝗲𝘀𝗻’𝘁 𝘀𝘁𝗼𝗽 𝗮𝘁 𝘄𝗼𝗿𝗸. 𝗜𝘁’𝘀 𝗯𝗲𝗰𝗼𝗺𝗲 𝗮 𝗯𝗶𝗴 𝗽𝗮𝗿𝘁 𝗼𝗳 𝗺𝘆 𝗽𝗲𝗿𝘀𝗼𝗻𝗮𝗹 𝗹𝗶𝗳𝗲 𝘁𝗼𝗼. -> Every morning, I literally ask Google's 𝐆𝐞𝐦𝐢𝐧𝐢 𝐋𝐢𝐯𝐞 things like, “𝑊ℎ𝑖𝑐ℎ 𝑠ℎ𝑖𝑟𝑡 𝑠ℎ𝑜𝑢𝑙𝑑 𝐼 𝑤𝑒𝑎𝑟 𝑤𝑖𝑡ℎ 𝑡ℎ𝑒𝑠𝑒 𝑗𝑒𝑎𝑛𝑠?” 😂 It might sound silly, but it saves time and avoids fashion disasters before meetings! -> Whenever I’m about to buy something—whether it’s a new monitor or an air fryer or I’m comparing two TVs—I come to OpenAI's ChatGPT for a clear, no-BS comparison. The suggestions are fast and well-structured and help me make better decisions. -> 𝐈 𝐞𝐯𝐞𝐧 𝐮𝐬𝐞𝐝 𝐢𝐭 𝐭𝐨 𝐩𝐥𝐚𝐧 𝐦𝐲 𝐒𝐈𝐏 𝐢𝐧𝐯𝐞𝐬𝐭𝐦𝐞𝐧𝐭𝐬 𝐭𝐡𝐢𝐬 𝐲𝐞𝐚𝐫. It helped me estimate returns, compare mutual funds, and gave me clarity on where I might be overexposed or under-diversified. I still remember calculating the corpus I’ll have by 37 based on step-up SIPs—and how clear it all looked after one single prompt. 😅 I’ve started seeing AI not just as a tool, but as a thinking assistant. It helps me code faster, debug smarter, plan better, and even dress sharper. 😄 As we get closer to 𝟐𝟎𝟐𝟔, I believe professionals who learn how to collaborate with AI—not just use it—will grow faster, ship better, and feel less stuck. I’d love to know: how are you using AI in your work or life? #AndroidDev #PhonePe #GitHubCopilot #FirebaseStudio #ChatGPT #GeminiLive #DevLife

I'll be honest. Before joining Microsoft, I wasn't using AI in my daily work as much as I could have. I wasn’t skeptical, but I hadn’t yet embraced the full potential of integrating AI into my workflows. That has changed completely, and now, with tools like Copilot, I can’t imagine working without it.   The most noticeable shift has been in how Copilot helps me prepare for meetings. Whether it's gathering insights from a series of documents, transcribing conversations, or pulling together key data points, it’s become an invaluable tool for streamlining my prep. I can dive straight into the substance of meetings with my team or customers, knowing that I’m fully backed by AI-generated insights that would have taken hours to compile.   Thanks to Copilot, my team and I are freed up to focus on what truly matters—driving strategic initiatives forward—rather than getting bogged down in administrative tasks. The results are clear: more impactful meetings, faster decision-making, and a level of efficiency that was previously out of reach. How has AI changed the way you work?

Curious if that new AI tool at work is actually making you more productive? Meet Sonia Jaffe, an economist at Microsoft who turns the hype around AI into real, measurable impact. Sonia’s research doesn’t just ask whether AI works. It shows how, where, and for whom these tools are changing the way we work. Sonia’s research maps where AI can make the biggest difference. Her ‘AI Applicability Score’ highlights which jobs are most susceptible to AI-driven change (https://lnkd.in/geXmaCQD), reflecting frequent and successful use of AI for activities such as information gathering and writing. And we can see that shift playing out in real-world AI usage. When employees first got access to M365 Copilot, she found that frequent users spent significantly less time on email and drafted documents faster (https://lnkd.in/gB6xi3wa). In the context of software development, Sonia’s research across three companies showed that GitHub Copilot users completed about 26% more tasks on average, with the biggest gains being for newer engineers (https://lnkd.in/gG3mMRsc). These aren’t just numbers. They’re evidence that AI can meaningfully accelerate routine work without sacrificing quality. Sonia’s knack for measuring the impact of technology on AI started long before AI. I first got to know her during the pandemic, when we co-authored a study exploring how remote work affected collaboration (https://lnkd.in/gQD7qrcg). We found that without offices, people leaned more on their close teammates and less on casual connections. As offices reopened, Sonia then studied how knowledge workers coordinated their in-office time (https://lnkd.in/gEkNWGMY) and managed their communication load (https://lnkd.in/gSz_uV8C), always grounding her insights in real-world data. But Sonia doesn’t just study the future of work – she helps shape it. As a leader of Microsoft’s New Future of Work initiative (http://aka.ms/nfw), she helps synthesize research findings into annual reports that inform decision makers and curates real world research on generative AI adoption (https://lnkd.in/gjnh5jCq). Her blend of forward-looking research and grounded experience in workplace dynamics makes her insights both practical and visionary. If you’re not yet following Sonia’s research, I highly recommend checking it out! #AIInnovators #AppliedResearch #FutureOfWork #LeadingLikeAScientist