Impact of Technology on Workforce

Truong Van Dao is a highly skilled Vietnamese woodworker and content creator known for crafting life-sized, fully functional wooden replicas of popular cars. His work involves meticulous craftsmanship, from selecting and carving the wood to assembling each vehicle’s intricate details. Amazing creativity? Truong’s creations include replicas of famous cars like the Lamborghini, Bugatti, and Ferrari, which he builds with remarkable precision to mimic the look and sometimes even the basic functionalities of the originals. His videos showcase the building process, attracting millions of viewers worldwide who are fascinated by his dedication, skill, and creativity in transforming wood into automotive masterpieces. Technology could significantly enhance Truong Van Dao's woodworking projects in several ways: 3D Modeling and CAD Software: Using 3D modeling software (like AutoCAD, Blender, or SolidWorks), Truong could design and visualize his projects before he started carving. This would allow him to create accurate digital blueprints of car models, helping him refine proportions and details before working on the wood. Such software could also help him scale down or adjust designs to fit different specifications. CNC Machines and Laser Cutters: While he may enjoy the traditional carving process, CNC (Computer Numerical Control) machines could help Truong produce complex parts more precisely and efficiently. CNC machines can cut, engrave, or shape wood to exact measurements, saving time and reducing error. Laser cutters could be particularly useful for intricate detailing, especially for small or delicate parts like logos, grills, and interior features. Augmented Reality (AR) for Virtual Placement: AR tools could allow Truong to project his designs onto physical wood blocks, helping him see where specific cuts or shapes should be made. This would act as a guide, overlaying the design onto the material, reducing mistakes, and improving accuracy. High-Quality Digital Documentation: Using high-resolution cameras and drones, Truong could document the building process in a more dynamic way, allowing him to create visually engaging content. He could also incorporate 360-degree video, time-lapses, and VR experiences, giving his audience an immersive view of his projects. Enhanced Safety Equipment: Advanced dust collection systems, smart goggles, noise-canceling headphones, and protective gloves with motion sensors could make his work environment safer and more comfortable, especially for long, detailed projects. 3D Printing for Parts: Although he specializes in wood, 3D printing could allow him to create molds or add non-wood components where necessary, such as wheels, lights, and mechanical parts. This could make his replicas even more functional and closer to actual car mechanics. Watch till the end. #Innovation #Technology #Creativity

𝐓𝐡𝐞 𝐒𝐀𝐏 𝐣𝐨𝐛𝐬 𝐭𝐡𝐚𝐭 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐤𝐢𝐥𝐥𝐞𝐝, 𝐚𝐧𝐝 𝐒𝐀𝐏 𝐣𝐨𝐛𝐬 𝐭𝐡𝐚𝐭 𝐰𝐢𝐥𝐥 𝐭𝐡𝐫𝐢𝐯𝐞 𝐛𝐞𝐜𝐚𝐮𝐬𝐞 𝐨𝐟 𝐀𝐈. AI will have a profound impact on the workforce at both SAP itself and SAP consulting companies. Some jobs will likely become obsolete as AI proves to be faster, more efficient, and cost-effective. Other roles will not only survive but flourish, as AI enhances their scope and enables new levels of innovation and efficiency. 𝐑𝐨𝐥𝐞𝐬 𝐦𝐨𝐬𝐭 𝐚𝐭 𝐫𝐢𝐬𝐤 𝐨𝐟 𝐛𝐞𝐢𝐧𝐠 𝐧𝐞𝐠𝐚𝐭𝐢𝐯𝐞𝐥𝐲 𝐢𝐦𝐩𝐚𝐜𝐭𝐞𝐝 𝐢𝐧𝐜𝐥𝐮𝐝𝐞: 𝐌𝐚𝐧𝐮𝐚𝐥 𝐒𝐀𝐏 𝐓𝐞𝐬𝐭𝐢𝐧𝐠 𝐂𝐨𝐧𝐬𝐮𝐥𝐭𝐚𝐧𝐭𝐬 ❌ AI-powered test automation will eliminate most manual SAP testing. Who survives? Test engineers skilled in AI-assisted test automation. 𝐁𝐚𝐬𝐢𝐜 𝐀𝐁𝐀𝐏 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫𝐬 (𝐂𝐮𝐬𝐭𝐨𝐦 𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐦𝐞𝐧𝐭𝐬 𝐟𝐨𝐫 𝐄𝐂𝐂/𝐒/𝟒𝐇𝐀𝐍𝐀) ❌ AI can generate and optimize standard ABAP code automatically. Who survives? SAP BTP developers (working on event-driven architectures, AI-powered extensions). 𝐋𝐨𝐰-𝐋𝐞𝐯𝐞𝐥 𝐒𝐀𝐏 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 (𝐋𝟏 & 𝐋𝟐 𝐇𝐞𝐥𝐩𝐝𝐞𝐬𝐤) ❌ AI chatbots & predictive issue resolution will replace many support tickets. Who survives? AI-powered SAP support strategists. 𝐁𝐚𝐬𝐢𝐜 𝐂𝐨𝐧𝐭𝐞𝐧𝐭 𝐂𝐫𝐞𝐚𝐭𝐨𝐫𝐬 & 𝐂𝐨𝐩𝐲𝐰𝐫𝐢𝐭𝐞𝐫𝐬 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐜𝐨𝐧𝐭𝐚𝐜𝐭 ❌ AI tools (like ChatGPT, Jasper, and SAP AI Copilots) can generate marketing copy, blog articles, and product descriptions in seconds. Who survives? AI-enhanced content strategists who focus on brand differentiation, thought leadership & SAP-specific narratives. 𝐒𝐀𝐏 𝐉𝐨𝐛𝐬 𝐓𝐡𝐚𝐭 𝐖𝐢𝐥𝐥 𝐓𝐡𝐫𝐢𝐯𝐞 𝐚𝐧𝐝 𝐆𝐚𝐢𝐧 𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐜𝐞: 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐧𝐬𝐮𝐥𝐭𝐚𝐧𝐭𝐬 🚀 Why? AI-driven business processes require strategic alignment & implementation. Future-proof skills: AI-powered business process optimization, SAP AI integration, SAP AI ethics. 𝐒𝐀𝐏 𝐂𝐥𝐨𝐮𝐝 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐬 & 𝐄𝐑𝐏 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐬𝐭𝐬 🚀 Why? AI-driven SAP solutions are moving to cloud-native & hybrid environments. Future-proof skills: SAP BTP, AI-enhanced workflow automation 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 & 𝐇𝐲𝐩𝐞𝐫𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐄𝐱𝐩𝐞𝐫𝐭𝐬 🚀 Why? AI-driven RPA, intelligent workflows & autonomous supply chains will reshape SAP implementations. Future-proof skills: SAP Intelligent RPA, AI-driven BPM, process mining. 𝐖𝐡𝐚𝐭 𝐭𝐨 𝐃𝐨 𝐍𝐞𝐱𝐭? ✔ Learn AI-driven SAP tools (SAP Joule, Datasphere, AI Core, SAP AI API development). ✔ Shift from execution (configuration & support) to AI-powered strategy & process optimization. ✔ Develop hybrid skills (AI, cloud-native SAP, data analytics, cybersecurity). AI isn’t replacing SAP experts or eliminating consultant jobs—it’s shaping a new generation of 𝐀𝐈-𝐞𝐦𝐩𝐨𝐰𝐞𝐫𝐞𝐝 𝐄𝐑𝐏 𝐬𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐬𝐭𝐬. Those who adapt to this shift early will be leading the disruption, not just surviving it. Do you agree? #sap #ai #technology #jobs

🏗️🤖 A robot is laying tiles faster than any human ever could. But here’s the real question: what happens to the humans? In construction, speed matters. So does accuracy. But so do people — their health, their jobs, their future. At first glance, a robot that lays thousands of tiles a day looks like it’s replacing workers. And let’s be honest — for many, that’s a scary thought. Because change like this doesn’t just threaten tasks — it threatens identities. But what if we looked deeper? 💡 This isn’t just about machines doing labor. It’s about rethinking the role of labor altogether — and refusing to believe that progress and people are enemies. Here’s what’s possible when we lead with empathy and intention: ✅ Workers avoid chronic pain and long-term injury ✅ Teams shift into roles that require thinking, planning, and creativity ✅ Projects run faster without burning people out ✅ Skilled builders move up — not out Because dignity in work isn’t just about sweat. It’s about being trusted with more — not less. 🔨 The hammer didn’t replace the carpenter. It made them more precise, more efficient, more impactful. 🤖 This robot isn’t here to erase people. It’s here to challenge us to build a smarter future — where no one gets left behind. ✔️ The truth is–we don’t have all the answers regarding workers. But we know this: if automation is coming, then so should training, upskilling, and job redesign — built with the people it affects. Progress without people isn't progress. It’s displacement. 👇 What part of construction do you think should be automated next — and what shouldn’t? 👉 Follow me for more honest conversations about tech, dignity, and the future of work. 👥 Tag a builder, tech leader, or trades educator who should join this conversation 🔁 Repost if you believe progress should lift people up, not push them out #ConstructionInnovation #SmartConstruction #TechWithEmpathy #HumanCenteredAutomation #FutureOfWork #ConstructionTech #WorksiteSafety #BuildersAndMachines #AutomationWithPurpose #DigitalTransformation #ToolsNotReplacements #BuildSmarter

As GenAI becomes more ubiquitous, research alarmingly shows that women are using these tools at lower rates than men across nearly all regions, sectors, and occupations.   A recent paper from researchers at Harvard Business School, Berkeley, and Stanford synthesizes data from 18 studies covering more than 140k individuals worldwide.   Their findings:   • Women are approximately 22% less likely than men to use GenAI tools • Even when controlling for occupation, age, field of study, and location, the gender gap remains • Web traffic analysis shows women represent only 42% of ChatGPT users and 31% of Claude users   Factors Contributing the to Gap:   - Lack of AI Literacy: Multiple studies showed women reporting significantly lower familiarity with and knowledge about generative AI tools as the largest gender gap driver. - Lack of Training & Confidence: Women have lower confidence in their ability to effectively use AI tools and more likely to report needing training before they can benefit from generative AI.   - Ethical Concerns & Fears of Judgement: Women are more likely to perceive AI usage as unethical or equivalent to cheating, particularly in educational or assignment contexts. They’re also more concerned about being judged unfairly for using these tools.   The Potential Impacts: - Widening Pay & Opportunity Gap: Considerably lower AI adoption by women creates further risk of them falling behind their male counterparts, ultimately widening the gender gap in pay and job opportunities. - Self-Reinforcing Bias: AI systems trained primarily on male-generated data may evolve to serve women's needs poorly, creating a feedback loop that widens existing gender disparities in technology development and adoption.   As educators and AI literacy advocates, we face an urgent responsibility to close this gap and simply improving access is not enough. We need targeted AI literacy training programs, organizations committed to developing more ethical GenAI, and safe and supportive communities like our Women in AI + Education to help bridge this expanding digital divide.   Link to the full study in the comments. And a link also to learn more or join our Women in AI + Education Community. AI for Education #Equity #GenAI #Ailiteracy #womeninAI

A prospect ghosted me last month. Demo went great. Pricing seemed fine. Technical review passed. Then... silence. I did what most reps do: Called. Emailed. LinkedIn messaged. Called again. Nothing. Two months later, I ran into their VP at a conference. "What happened to our deal?" I asked. His response shocked me: "Our team couldn't agree on implementation. Half thought it would take too long." I was like WTF... That objection never came up on our calls. I could have easily addressed it. The deal died silently. This is the reality of modern selling: For every objection you hear... There are 3 you never will. The real sales conversations happen when you're not in the room. I changed my approach with the next prospect: After our demo, I created a digital room with: - Implementation timeline showing exact steps - FAQ section addressing common concerns - Space for anonymous questions - Engagement tracking on every resource What I discovered was eye-opening: The CFO visited the pricing page 7 times. The IT team kept returning to security documentation. Three stakeholders I'd never spoken to viewed the implementation plan. One left a comment: "Will this integrate with our current workflow?" A objection I would have never heard otherwise. Traditional sales process: You present. They evaluate privately. You guess what's happening. Modern sales process: You present. They evaluate transparently. You see their concerns in real-time. The truth about "ghosted" deals: Your prospects aren't ignoring you. They're stuck in internal debates you can't see. Stop focusing solely on the conversations you're in. Start creating spaces for the conversations happening without you. The deals you save will be the ones you never knew were at risk. Agree?

In my conversations with leaders, the debate around AI often centers on how it will impact traditional desk-based work. But today, as we release Randstad's latest global labor market research, a very different reality is clear: AI cannot build its own data centers. 🏗️🔋 The digital revolution underway has a massive foundation in the physical economy. Our new analysis of over 50 million global job postings reveals a significant shift in the labor market as companies race to build the infrastructure that makes AI possible: 📈 Hiring for skilled trades is now growing 3x faster than for professional roles. 🤖 Demand for robotics technicians has surged by 107% since the rise of generative AI. ❄️ Vacancies for HVAC engineers are up 67%. The real constraint on global economic growth isn't only about a shortage of chips, energy, or capital. It is the severe scarcity of specialized talent in the skilled trades. Today’s trades are highly specialized, digital-first positions. You cannot be a modern electrician or robotics technician without strong digital fluency. To secure our digital future, we must fundamentally re-rate the skilled trades as a premier career track and recognize them as the new knowledge workers. I invite you to dive into our new data to see why this physical bottleneck is the defining workforce challenge—and opportunity—of the AI era: https://lnkd.in/ez86jjVg

I don't think most people realize how rare this moment in history is. You can get founder-level upside (equity) without taking founder-level risk. Pick the right company to work at in the next three to five years, and it could make your entire career. Tech companies are staying private longer, but employees no longer always have to wait for an IPO or acquisition to turn their equity into cash. In the last few years: OpenAI created liquidity for more than 600 current and former employees at a $500 billion valuation. SpaceX ran an employee share sale at $350 billion. Stripe offered liquidity at $65 billion. Databricks raised a massive round that was used in large part to give current and former employees liquidity. Canva, Figma, Rippling, Revolut, ByteDance and Ramp have done versions of the same thing. At the reported transaction valuations, a 0.01% stake would theoretically have been worth: - $50 million at OpenAI - $35 million at SpaceX - $22.35 million at ByteDance - $6.5 million at Stripe - $6.2 million at Databricks Of course, nobody starts with exactly 0.01% and keeps all of it (dilution, vesting, exercise costs, etc.) And most startups fail. But the larger point stands You can get a slice of founder-level upside without taking the full founder-level risk. Picking where to work in the next three to five years may be one of the most important decisions of your career.

The Hidden AI Bottleneck No One’s Talking About: It’s Not GPUs — It’s Human Hands We’ve been told the #AI race is all about chips, models, and PhDs. But here’s the uncomfortable truth: AI’s physical infrastructure buildout is hitting a real bottleneck — a shortage of skilled tradespeople. Real stat you should see: As of late 2025, the U.S. construction industry is facing a shortage of roughly 439,000 workers, most of whom are skilled trades like electricians, plumbers, and pipe layers — the very people who build and power data centers that are the backbone of AI infrastructure. This gap isn’t a footnote — it’s a strategic vulnerability in our national AI capacity. Here’s what that means for AI leaders: 🔹 AI leadership isn’t just about algorithms — it’s about infrastructure leadership. You can train the best ML models but if you can’t wire, cool, and power the facilities, that compute sits idle. 🔹 The “AI talent war” is no longer just for coders and researchers. Trades like electricians and HVAC techs — roles once overlooked — are now critical AI talent. We must redefine talent strategy for the AI era: • Skills pipelines. • Apprenticeships. • Cross-sector career pathways. • Partnerships with unions and trade schools. • Corporate investment in human development. AI doesn’t replace jobs that require human dexterity and judgment — it amplifies the demand for them. What the market forgot: humans build AI infrastructure — machines don’t. Your AI Leadership Action Plan: 1. Integrate physical infrastructure capacity into your AI readiness strategy. 2. Invest in skills-first workforce development (trades + technology). 3. Advocate for structured apprenticeships tied to AI ecosystem growth. You can’t scale AI without scaling the humans who build it. What do you think?

Who is architecting the future of Denmark? Right now, the data says it isn’t women … While we’ve focused on representation in boards and leadership, a new divide has emerged: a stark gender divide in who is actually building and using AI, leaving Denmark with one of the most imbalanced talent pools in the region. We are at risk of trading the old glass ceiling for a new, digital one. AI is right now reshaping business models and how decisions are made, how companies are led, and how value is created. If you are not proactively engaging with AI, you are not part of architecting the future. The numbers tell the story of the divide: 🤔 AI Development: Only 21.3% of Denmark’s AI workforce are women. That’s one out of five! 🤔 AI Usage: At the moment, women in Denmark use AI 20% less than men. 🤔 AI Skills: Looking at this platform, LinkedIn, In Denmark only a mere 27% of those listing AI skills in their profile are women, compared to 73 percent men. This is by far the biggest gap, even if we measure against our neighbors (Finland, for example, is more equalled out at 39%-61%) It is also what I experience in my ongoing engagements across the Danish business landscape: There are way too few women engaging in AI development and adoption. We, in Denmark, have set ourselves the goal of becoming an AI front-runner - officially aiming at upskilling 1 million Danes by 2028 - but we cannot achieve this goal unless we engage our entire talent pool. Closing the gap starts with changing the status quo - reimagining! That’s why, in collaboration with some incredible partners, we’ve launched @Reimagine, aiming to break down the usual stereotypes and using Google’s Nano Banana for women to engage with AI and portray themselves as pilots, firefighters, race drivers. Or, like in this post, university professors … an encouragement to just experiment and play with AI. Try yourself: https://reimagine.nu/ A very special thanks to our partners and supporters behind the campaign, including roccamore, DiverseEksperter.dk, Kvindeøkonomien, Ladies First, Above & Beyond Group, Hello Ada, Women In Tech Denmark, Inspiring DAC, Connected Women in AI. #ReImagine #Google #InternationalWomensDay #IWD #WomensDay

This International Women's Day, I want to share data that stopped me cold. Anthropic published research this week measuring which workers face the highest AI displacement risk. The answer is not who anyone expected. The most AI-exposed workers in the US are: → 16 percentage points more likely to be female → 4x more likely to hold a graduate degree → Earning 47% more than the least-exposed group We spent years building the narrative that automation threatens low-wage work. Factory floors. Delivery drivers. Retail cashiers. AI walked straight past them. It sat down at the desk of the woman who spent two decades forcing her way into finance, tech, and analytics. The most exposed jobs? Computer programmers. Financial analysts. Customer service managers. 75% task coverage. Already. Right now. These aren't entry-level roles that women "settled for." These are the careers women fought their way into — often against the odds, often without a roadmap. Here's the part that should make us angry. The job losses aren't visible yet. No unemployment spike. No headlines. Because it's not happening through layoffs. It's happening through closed doors. Young women aged 22–25 entering these fields are seeing hiring rates fall 14% since ChatGPT launched. Not fired. Never offered the job. That is how structural exclusion works. Silently. Before the data is undeniable. Before anyone has to answer for it. On International Women's Day, we celebrate how far women have come. But I want to ask a harder question: Who is protecting where they are now? The same industries that championed gender diversity in tech and finance — are they mapping which female-dominated roles are most AI-exposed? Are they funding transition programmes ahead of this curve, or waiting to react? If we only act once the data screams, we didn't protect progress. We delayed the fall. Infrastructure beats innovation. But infrastructure that ignores equity isn't infrastructure — it's a trap. What is your organisation doing TODAY to protect its most exposed workforce?