Tips for Preparing for an Automated Future

Is AI automating away coding jobs? New research from Anthropic analyzed 500,000 coding conversations with AI and found patterns that every developer should consider: When developers use specialized AI coding tools: - 79% of interactions involve automation rather than augmentation - UI/UX development ranks among the top use cases - Startups adopt AI coding tools at 2.5x the rate of enterprises - Web development languages dominate:          JavaScript/TypeScript: 31%          HTML/CSS: 28% What does this mean for your career? Three strategic pivots to consider: 1. Shift from writing code to "AI orchestration"     If you're spending most of your time on routine front-end tasks, now's the time to develop skills in prompt engineering, code review, and AI-assisted architecture. The developers who thrive will be those who can effectively direct AI tools to implement their vision. 2. Double down on backend complexity     The data shows less AI automation in complex backend systems. Consider specializing in areas that require deeper system knowledge like distributed systems, security, or performance optimization—domains where context and specialized knowledge still give humans the edge. 3. Position yourself at the startup-enterprise bridge     With startups adopting AI coding tools faster than enterprises, there's a growing opportunity for developers who can bring AI-accelerated development practices into traditional companies. Could you be the champion who helps your organization close this gap? How to prepare: - Learn prompt engineering for code generation - Build a personal workflow that combines your expertise with AI assistance - Start tracking which of your tasks AI handles well vs. where you still outperform it - Experiment with specialized AI coding tools now, even if your company hasn't adopted them - Focus your learning on architectural thinking rather than syntax mastery The developer role isn't disappearing—it's evolving. Those who adapt their skillset to complement AI rather than compete with it will find incredible new opportunities. Have you started integrating AI tools into your development workflow? What's working? What still requires the human touch?

🚨 Your role just landed on the “easiest to automate” list? That isn’t a pink slip - it’s an early-warning system. First, zoom out. Tasks go away, not talents. Make an inventory of the underlying abilities your job demands: pattern recognition, client empathy, regulatory knowledge, cross-team coordination. Those skills are transferable, and transfer is where reinvention starts. Next, learn the tech aimed at replacing you. When you understand how the model works, you can spot its blind spots. That turns you from potential redundancy into the resident “AI whisperer” who accelerates adoption and keeps errors in check. Then, double down on the human edge. Negotiation, creative synthesis, trust-building, storytelling-skills too unstructured or emotional for algorithms-gain premium value as everything else gets cheaper. Prioritize projects that showcase them and document measurable wins. Don’t wait for HR to reskill you. Block two hours a week for structured learning: a micro-credential in data literacy, prompt-engineering side experiments, a community hackathon. Momentum is currency when markets shift. Network laterally, not just upward. Peers in adjacent functions-product, compliance, customer success-see opportunities your current title hides. Collaborate on cross-functional pilots and you’ll surface for roles that didn’t exist a quarter ago. Finally, treat uncertainty as venture capital in yourself. Whether you spin up a consultancy, prototype a tool that augments your old workflow, or pivot into an AI-governance niche, the same risk that threatens your job funds your next chapter. Your job may be automatable. Your career is optionality in motion. #CareerGrowth #FutureOfWork

A lot of finance teams are waiting for a magic box. A plug-and-play AI solution that solves all their modeling and forecasting challenges... out of the box. But here's the truth: 𝘛𝘩𝘦 𝘳𝘦𝘢𝘭 𝘰𝘱𝘱𝘰𝘳𝘵𝘶𝘯𝘪𝘵𝘺 𝘪𝘴𝘯’𝘵 𝘪𝘯 𝘰𝘶𝘵-𝘰𝘧-𝘵𝘩𝘦-𝘣𝘰𝘹 𝘢𝘯𝘺𝘵𝘩𝘪𝘯𝘨... It’s in evolving your finance processes and team with automation and AI together. Because AI won’t replace your FP&A team. But it can help: • Automate recurring models • Enhance variance and scenario analysis • Assist decision-making with smarter insights • Help the team see beyond their current sight, creating more capable professionals For AI automation to work, companies need to stop thinking like tech consumers... And start thinking like process designers. Here are key things to consider for a successful AI + automation project: ➤ Start with clarity Know which processes are repetitive, time-consuming, and rules-based. Automate them. ➤ Identify the biggest bottlenecks for a successful automation. They might be good use cases for AI ➤ Don’t skip the human layer AI can assist with insight, but you still need finance judgment to interpret and act. ➤ Data quality is everything Bad inputs = bad outputs. Garbage in, garbage out. Clean, consistent, structured data is key. ➤ Integrate, don’t isolate AI should sit within your tools and workflows, not float in a separate app. It should part of an existing process and not a process created apart. ➤ Implement measures to keep data safe. Governance, policies and compliance. Create guardrails in the processes. ➤ Measure impact, not hype Track real ROI: time saved, accuracy improved, insights gained. The future of FP&A isn't a robot doing your budget. It's smarter tools helping humans do finance better.

The real power in AI isn’t in the tools , it’s in understanding the logic that drives them. The AI era is buzzing with hype around automation tools like Zapier, Make, and n8n. While these platforms offer incredible power to streamline workflows and generate revenue, it’s crucial to approach them with a strategic mindset rather than absolute reliance. They are fantastic for immediate gains and scaling, but the notion of them being the definitive future needs a closer look. The pace of innovation in AI is breathtaking. Consider Google’s recent launch of sophisticated automation tools like Opal. What's revolutionary today could be a footnote tomorrow as new, more advanced solutions emerge at lightning speed. Building an entire business or career path solely on a specific tool, however powerful now, risks obsolescence within a short timeframe. The real enduring value lies in the underlying principles of automation and AI. To truly thrive in this dynamic landscape, focus on mastering the fundamental concepts: problem-solving, logical thinking, data management, and core AI principles. These transferable skills will equip you to adapt to any new tool or platform that arises. Cultivate extreme agility and a perpetual learning mindset. Your ability to pivot and embrace new technologies is a far greater asset than your proficiency with a single, potentially transient, tool. Leverage current automation tools for immediate business impact and revenue generation, but always keep an eye on the evolving horizon. The future belongs to those who can seamlessly integrate new advancements and consistently adapt. Don't just use the tools; understand the problems they solve and the principles that guide them. Share your thoughts below, this is what I think ! #AI #Automation #FutureOfWork #DigitalTransformation #TechTrends #BusinessStrategy #LearnAndAdapt #Zapier #Make #n8n #Innovation

By 2030, 170 million new jobs will be created and 92 million will disappear. (World Economic Forum: Future of Jobs Report) Most people see those numbers and think about loss. But when I look at them, I see something different: A once-in-a-generation redesign of what work is. Not because humans are being pushed aside  but because AI is changing how we create value. And if you look closely, you can already see the shift happening. Over the past few years, I’ve watched entirely new roles appear inside teams I’ve coached and partnered with. Roles that didn’t exist, weren’t taught in school, and had no playbook to follow: Prompt Engineer teaching AI how to think • AI Risk & Governance Specialist, protecting safety and fairness • Decision Engineer, blending human judgment with AI execution • AI Ethicist, guarding what must remain human • AI Operations / ML Ops, keeping models stable in the real world • Head of AI, shaping the strategy, culture, and adoption • AI Translator, turning business problems into AI workflows • Model Validator, ensuring models stay accurate and unbiased Three years ago these sounded experimental. Now they’re becoming essential. 🔄 The real shift isn’t “jobs disappearing” it’s that jobs are changing shape. AI is taking over the parts of work that drain people: • the repetition • the manual steps • the data chasing • the admin • the coordination • the first drafts And as that happens, something interesting emerges: Humans finally get to focus on the parts of work that are actually human. • strategy • creativity • judgment • ethics • communication • leadership • meaning Every leader I’ve worked with eventually realizes this: AI doesn’t threaten the work, it transforms what the work is worth. If you want to stay relevant in this new era, the advantage isn’t “knowing AI.” It’s knowing how to work with it. Here’s where to start: 1. Learn the language. Not to become an engineer  but to understand how LLMs, agents, and AI systems think. 2. Choose your path. Technical or strategic. Both matter more than ever. 3. Build something small. A workflow. A prototype. A simple automation. Hands-on learning hits differently. 4. Strengthen the human skills. The ones AI can’t replicate: judgment, communication, ethics, design thinking. 5. Stay adaptable. In a world moving this fast, curiosity becomes a career strategy. **The future of work isn’t about competing with AI. It’s about learning how to partner with it  so humans can rise to the work that truly needs us.** Because at the end of the day, the future of work is still a story about people. 🔁 Repost to help someone navigate this shift ➡️ Follow Gabriel Millien for human-centered insights on AI, LLMs, and the future of work

AI seems to be everywhere in theory. Yet for many of the leaders I collaborate with, it’s less present in practice. Most are aware its powering backend systems, fewer are proactively leveraging it day-to-day. We are on the cusp of widespread adoption. That makes it a good time to think about what’s coming. Ravi Malick, Box Global CIO, shares, “We must recognize that we are shifting from “managing people and technology” to designing the relationships between humans and intelligent systems.” Today, we are experienced in supporting our team members in leveraging tools, technology, and systems for efficiency and productivity. 𝗦𝗼𝗼𝗻, 𝗹𝗲𝗮𝗱𝗲𝗿𝘀 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗰𝗮𝗹𝗹𝗲𝗱 𝘂𝗽𝗼𝗻 𝘁𝗼 𝗳𝗮𝗰𝗶𝗹𝗶𝘁𝗮𝘁𝗲 𝘁𝗵𝗲 𝗲𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝗽𝗲𝗼𝗽𝗹𝗲 𝗮𝗻𝗱 𝗺𝗮𝗰𝗵𝗶𝗻𝗲𝘀. Managers will need to consciously choose to put people first in workplaces. When machines are sharing the cognitive load at work, as leaders we’ll have to undergo fundamental shifts in how we value information and respect human contribution. It’s clear that interdependence between human and artificial intelligence can create better work, productivity, and results. 𝗟𝗲𝗮𝗱𝗶𝗻𝗴 𝘀𝘂𝗰𝗰𝗲𝘀𝘀𝗳𝘂𝗹 𝘀𝘆𝗻𝗲𝗿𝗴𝘆 𝘄𝗶𝘁𝗵 𝗵𝘂𝗺𝗮𝗻𝘀 𝗮𝗻𝗱 𝗔𝗜 𝘄𝗶𝗹𝗹 𝗾𝘂𝗶𝗰𝗸𝗹𝘆 𝗯𝗲𝗰𝗼𝗺𝗲 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗰𝗼𝗻𝘀𝗲𝗾𝘂𝗲𝗻𝘁𝗶𝗮𝗹 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗼𝗳 𝗼𝘂𝗿 𝗲𝗿𝗮. Here are best practices to consider as you lead in the AI era:  • Openly share with others how you are learning and preparing for co-working with AI.  • Describe, narrate, and communicate changes brought about by AI in plain language.  • Clarify a human Ultimate Responsibility Owner for key decisions, process evaluations, and to promote transparency around how work is being completed by machines.  • Practice AI using sandbox settings, simulating changes so people understand how artificial intelligence augments human contribution and to test and learn of its validity before full integration into workflows.  • Recommit to deeply human leadership moments by building relational leadership skills. Spend more time with people and less time with screens, increase relatability through sharing experiences with team members, and prioritize connection and engagement. 𝗜𝗳 𝘃𝗮𝗹𝘂𝗶𝗻𝗴 𝗵𝘂𝗺𝗮𝗻𝗶𝘁𝘆 𝗿𝗲𝗺𝗮𝗶𝗻𝘀 𝘁𝗵𝗲 𝗳𝗼𝗰𝘂𝘀 𝗮𝘀 𝘄𝗲 𝗱𝗲𝘀𝗶𝗴𝗻 𝗵𝘂𝗺𝗮𝗻 𝗮𝗻𝗱 𝗔𝗜 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗮𝘁 𝘄𝗼𝗿𝗸, 𝗽𝗲𝗼𝗽𝗹𝗲 𝘄𝗶𝗹𝗹 𝗵𝗮𝘃𝗲 𝘁𝗿𝗲𝗺𝗲𝗻𝗱𝗼𝘂𝘀 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝗶𝗲𝘀 𝘁𝗼 𝗳𝗹𝗼𝘂𝗿𝗶𝘀𝗵, 𝗴𝗿𝗼𝘄, 𝗮𝗻𝗱 𝗱𝗲𝗲𝗽𝗲𝗻 𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝗶𝗼𝗻 𝘁𝗼 𝗲𝗮𝗰𝗵 𝗼𝘁𝗵𝗲𝗿. That's exciting progress. 

During a recent speaking engagement, a member of the audience asked me how to best prepare for the coming era of AI and robotic automation so as not to be expendable. My answer was, "Automate yourself out of a job." Proactively automating your role is the best way to ensure you have a job after the automation revolution, which is driven by AI and robotics. By taking the initiative to automate your tasks, you gain an invaluable advantage: you deeply understand how automation works, its strengths, limitations, and its impact on your specific job. This hands-on experience positions you uniquely, making you the perfect candidate to help others implement similar efficiencies. Instead of fearing automation, embrace it. Learn about the tools that threaten your job, master them, and become the go-to expert who knows exactly how and when to deploy automation solutions. Your ability to automate your role proves your adaptability, foresight, and value. Remember: automation isn't about removing you from the workforce; it's about shifting your role from repetitive tasks to high-level strategic thinking and creative problem-solving. Be the conductor of your career and the automation era ahead. Automate yourself today to secure your career tomorrow. #AI #Career #FutureofWork #Automation

➝ Laying the Foundations of Success in 2025: Prepare for Growth in an AI-First World.    We have witnessed several key advancements in technology over the last few years, especially with the public launch of Large Language Models (LLMs) like ChatGPT, Claude, and Gemini. Now, what does that mean for us, our careers, and our future? AI goes a step beyond traditional Robotic Process Automation, and today we're witnessing large-scale automation that can be done fairly easily using custom GPTs at a fraction of what it would have cost earlier. Repetitive tasks and those requiring mediocre skills are prime candidates for automation, meaning products and services will employ greater automation going forward. The need of the hour is to recognize what's happening around us rather than complaining. It will be prudent to be on the right side of AI. During fireside chats and discussions, I'm often asked how we can prepare ourselves for an AI-first world. Here are my key suggestions for thriving in this new era: 1. Recognize the need for change and embrace it proactively 2. Understand workflows and the value chain of your work processes 3. Upskill in specialized areas you believe will remain irreplaceable. Step outside your comfort zone and pivot to new skills and job profiles if required 4. Master Generative AI, especially prompt engineering (it's much more sophisticated than forming a Google search query) 5. Create and practice use cases—start simple and progress to complex scenarios using different LLMs 6. Leverage professional groups on LinkedIn and other networking platforms to learn and seek help (many are willing to assist if you reach out with genuine intent) I am happy to share my learning and experience in AI and Machine Learning to help you get started. If you'd like me to conduct a webinar to help you begin or clarify doubts, please write "Webinar" in the comments below. So, how prepared are you currently to excel in an AI-first world? What tips would you like to share with the community here? This is a discussion that would benefit many, and I look forward to collaborating with you on this. Together we can! Follow Amer Nizamuddin for more insights on leadership, strategy, career management, professional development, AI, and more. --- P.S. If you find this valuable, please share it to help one person in your network ♻️ #wisdomquant #AI #careerskills

I remember the days when the only solution was to throw more bodies at the problem. Hiring more people, Spending more time, and still feeling like we were never caught up. And then came technology. AI, Machine Learning, Big data, (*insert buzzword*) They all promised us a smoother ride. They're quick, they're intelligent. But is it really a choice between human intelligence or more tech? Clearly, neither is the perfect solution. When every minute counts, the last thing you want is to waste time on tasks that could be automated. Here’s how you can start: 1: Identify Repetitive Tasks Start with the easy stuff. Look at your daily tasks. Are there repetitive actions that take up time? These are prime candidates for automation. The mistake many make is trying to automate complex processes right away. But starting simple gives you quick wins. 2: Choose the Right Tools The right tool can make all the difference. Not all tools are created equal. Some are too complex for what you need; others don’t integrate well with your existing systems. The key is to choose tools that match your specific needs and are user-friendly. 3: Set Clear Goals Goals give you direction. Without clear goals, automation efforts can drift. You need to know what you’re aiming for. Whether it’s reducing manual reviews by 50% in three months or cutting review time by half, make your goals specific and measurable. 4: Start with Low-Risk Processes Start small, think big. Don’t try to automate everything at once. Begin with low-risk tasks that won’t cause major issues if something goes wrong. This allows you to test your automation approach and make adjustments without significant consequences. 5: Test and Monitor Automation is not a set-it-and-forget-it solution. Just because something is automated doesn’t mean it’s perfect. Regular testing and monitoring are crucial to ensure that the automation is functioning correctly. Without it, you risk overlooking errors that can snowball into bigger problems. 6: Train Your Team Your team needs to be on board. Automation tools are only as good as the people who use them. Training your team on how to use these tools is essential. It reduces resistance, increases adoption, and ensures that everyone knows how to handle the automated processes. 7: Integrate with Existing Systems Keep everything connected. Your automation tools should work seamlessly with your existing systems. If they don’t, you’ll end up with silos of information that create more problems than they solve. Integration is crucial for a smooth workflow. 8: Measure Success Data drives decisions. You need to track the performance of your automated processes. Without data, you won’t know if your automation is effective or not. Measuring success allows you to make informed decisions about what to tweak, scale, or scrap.

Did you know … by 2030, AI is expected to automate 45% of current work activities? How will this shape the future of YOUR workforce? I recently sat with a client—a senior leader in a mid-sized logistics firm—who confided, “We know AI is coming. But our people are nervous. Honestly, so are we.” Their fear isn’t unusual. Across industries, the reaction to AI often oscillates between awe and avoidance. We either overhype it or we skirt around the real conversation by distracting ourselves with power points. In both cases, we miss the most important part: Preparation! We’re waiting too long! And so the Real Risk of AI is 😔Lack of preparation, which leads to 🤨It happening TO US, rather than WITH US which leads to 🤢Intellectual Atrophy® Let me explain. AI isn’t here to replace us. It’s here to amplify us. But if we don’t adapt, reskill, or rethink how we work alongside these tools, we fall into what I’ve been call “intellectual atrophy” since 2013 — the slow erosion of curiosity, creativity, and capability. It happens when: 😱We rely on AI without understanding how it works 😱We avoid it because it feels “too technical.” 😱We train once and expect long-term transformation. So How Can Organizations Prepare for the Future of Work? Start with these 3 pillars: 1. Assess Skills Honestly—Not Just Roles! What skills will this change, enhance, or eliminate? Map existing capabilities. Identify the gaps. And most importantly, recognize the human skills that remain timeless—critical thinking, empathy, adaptability. 2. Continuous Learning is underestimated! This isn’t just about offering courses on prompt engineering or data analytics. It’s about creating a workplace where experimentation is safe, where curiosity is rewarded, and where “I don’t know” becomes an invitation to learn—not a source of shame. 3. Use AI Right! 🤢The wrong way: Using AI as a shortcut for deep thinking. Replacing employees before reskilling them. Relying on AI without oversight. 😊The right way: Co-piloting: letting AI support, not supplant, human work. Personalizing development pathways through smart tools. Making data-driven decisions with ethical and human oversight. The Bottom Line AI is not the enemy of work. Intellectual Atrophy® is. The companies that will thrive in the future aren’t the ones with the flashiest tech. They’re the ones that invest in people just as much as platforms. So I’ll leave you with this - What steps are you taking to prepare your team? Share below! #FutureOfWork #AI #Leadership #DigitalTransformation #WorkplaceInnovation