Skills Gap Analysis Techniques

I got fired twice because I had poor soft skills. Then, I became VP at Amazon, where my job was more than 80% based on soft skills. This was possible because I stopped being an outspoken, judgmental critic of other people and improved my soft skills. Here are 4 areas you can improve: Soft skills are one of the main things I discuss with my coaching clients, as they are often the barrier between being a competent manager and being ready to be a true executive. Technical skills are important, but soft skills are the deciding factor between executive candidates a lot more than technical skills are. Four “soft skill” areas in which we can constantly improve are: 1) Storytelling skills Jeff Bezos said, “You can have the best technology, you can have the best business model, but if the storytelling isn’t amazing, it won’t matter.” The same is true for you as a leader. You can have the best skills or best ideas, but if you can’t communicate through powerful storytelling, no one will pay attention. 2) Writing Writing is the foundation of clear communication and clear thinking. It is the main tool for demonstrating your thinking and influencing others. The way you write will impact your influence, and therefore will impact your opportunities to grow as a leader. 3) Executive Presence Executive presence is your ability to present as someone who should be taken seriously. This includes your ability to speak, to act under pressure, and to relate to your team informally, but it goes far beyond any individual skill. Improving executive presence requires consistently evaluating where we have space to grow in our image as leaders and then addressing it. 4) Public Speaking As a leader, public speaking is inevitable. In order the get the support you need to become an executive, you must inspire confidence in your abilities and ideas through the way you speak to large, important groups of people. No one wants to give more responsibility to someone who looks uncomfortable with the amount they already have. I am writing about these 4 areas because today’s newsletter is centered around how exactly to improve these soft skills. The newsletter comes from member questions in our Level Up Newsletter community, and I answer each of them at length. I'm joined in the newsletter by my good friend, Richard Hua, a world class expert in emotional intelligence (EQ). Rich created a program at Amazon that has taught EQ to more than 500,000 people! The 4 specific questions I answer are: 1. “How do I improve my storytelling skills?” 2. “What resources or tools would you recommend to get better in writing?” 3. “What are the top 3 ways to improve my executive presence?” 4. “I am uncomfortable talking in front of large crowds and unknown people, but as I move up, I need to do this more. How do I get comfortable with this?” See the newsletter here: https://lnkd.in/gg6JXqF4 How have you improved your soft skills?

The most important skills today and in the next years will be human capabilities: critical and analytic thinking, resilience, leadership and influence, overlaid with technological literacy and AI skills to amplify these human capacities. World Economic Forum's new Future of Jobs Report provides a deep and broad analysis of the drivers of labour market transformation, the outlook for jobs and skills, and workforce strategies across industries and nations. It's a really worthwhile deep dive if you're interested in the topic (link in comments). Here are some of the highlights from the Skills section, which to my mind is at the heart of it. 🧠 Analytical Thinking Leads Core Skills. Skills like analytical thinking (70%), resilience (66%), and creative thinking (64%) top the list of core abilities for 2025. By 2030, the emphasis shifts even more towards AI and big data proficiency (85%), technological literacy (76%), and curiosity-driven lifelong learning (79%). This shift underscores the critical role of technology and adaptability in future workplaces. 📉 Skill Stability Declines but at a Slower Rate. Employers predict that 39% of workers' core skills will change by 2030, slightly lower than 44% in 2023. This reflects a stabilization in the pace of skill disruption due to increased emphasis on upskilling and reskilling programs. Half of the workforce now engages in training as part of long-term learning strategies compared to 41% in 2023, showcasing the growing adaptation to technological changes . 🌍 Economic Disparities in Skill Disruption. Middle-income economies anticipate higher skill disruption compared to high-income ones. This disparity highlights the uneven challenges of transitioning labor forces across global regions, particularly in economies still grappling with structural changes. 🚀 Tech-Savvy Skills in High Demand. The adoption of frontier technologies, including generative AI and machine learning, is increasing the demand for skills like big data analysis, cybersecurity, and technological literacy. These trends indicate that businesses are aligning workforce strategies to integrate these advancements effectively. 📚 Upskilling Is the Norm, Not the Exception. By 2030, 73% of organizations aim to prioritize workforce upskilling as a response to ongoing disruptions. This reflects a shift in corporate investment priorities towards human capital enhancement to maintain competitiveness.

McKinsey & Company 𝗷𝘂𝘀𝘁 𝗿𝗲𝗹𝗲𝗮𝘀𝗲𝗱 𝗮 𝟱𝟬+ 𝗽𝗮𝗴𝗲 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝗼𝗻 𝘁𝗵𝗲 𝗲𝗰𝗼𝗻𝗼𝗺𝗶𝗰 𝗶𝗺𝗽𝗮𝗰𝘁 𝗼𝗳 𝗔𝗜, 𝗲𝘀𝘁𝗶𝗺𝗮𝘁𝗶𝗻𝗴 𝘁𝗵𝗮𝘁 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝗰𝗼𝘂𝗹𝗱 𝘂𝗻𝗹𝗼𝗰𝗸 $𝟮.𝟵 𝘁𝗿𝗶𝗹𝗹𝗶𝗼𝗻 𝗯𝘆 𝟮𝟬𝟯𝟬. There is no doubt that work in the future will not be human-only or machine-only, but a coordinated system of people, agents, and robots operating together. This matters because the structure of work - not the number of jobs - is what will shift first, as core skills are redeployed and new forms of human-machine collaboration become central to productivity. 𝗔𝘁 𝗮 𝗴𝗹𝗮𝗻𝗰𝗲, 𝗠𝗰𝗞𝗶𝗻𝘀𝗲𝘆 𝗵𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀 𝗳𝗶𝘃𝗲 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝘀𝗵𝗶𝗳𝘁𝘀: ↓ 1 - 𝗪𝗼𝗿𝗸 𝗶𝗻 𝘁𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗮 𝗽𝗮𝗿𝘁𝗻𝗲𝗿𝘀𝗵𝗶𝗽 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝗽𝗲𝗼𝗽𝗹𝗲, 𝗮𝗴𝗲𝗻𝘁𝘀, 𝗮𝗻𝗱 𝗿𝗼𝗯𝗼𝘁𝘀 - 𝗮𝗹𝗹 𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗯𝘆 𝗔𝗜: ➜ McKinsey notes that today’s technologies could theoretically automate more than half of current US work hours. This shows how profoundly work may change, but it is not a forecast of job losses. Adoption will take time. As it progresses, some roles will shrink, others will grow or shift, and new ones will emerge - with work increasingly centered on collaboration between humans and intelligent machines. 2 - 𝗠𝗼𝘀𝘁 𝗵𝘂𝗺𝗮𝗻 𝘀𝗸𝗶𝗹𝗹𝘀 𝘄𝗶𝗹𝗹 𝗲𝗻𝗱𝘂𝗿𝗲, 𝘁𝗵𝗼𝘂𝗴𝗵 𝘁𝗵𝗲𝘆 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗮𝗽𝗽𝗹𝗶𝗲𝗱 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁𝗹𝘆: ➜ The reports stats that more than 70 percent of the skills sought by employers today appear in both automatable and non-automatable work. Most skills remain relevant, but how and where they are used will evolve. 3 - 𝗠𝗰𝗞𝗶𝗻𝘀𝗲𝘆’𝘀 𝗻𝗲𝘄 𝗦𝗸𝗶𝗹𝗹 𝗖𝗵𝗮𝗻𝗴𝗲 𝗜𝗻𝗱𝗲𝘅 𝘀𝗵𝗼𝘄𝘀 𝘄𝗵𝗶𝗰𝗵 𝘀𝗸𝗶𝗹𝗹𝘀 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗺𝗼𝘀𝘁 𝗮𝗻𝗱 𝗹𝗲𝗮𝘀𝘁 𝗲𝘅𝗽𝗼𝘀𝗲𝗱 𝘁𝗼 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝘁𝗵𝗲 𝗻𝗲𝘅𝘁 𝗳𝗶𝘃𝗲 𝘆𝗲𝗮𝗿𝘀: ➜ Digital and information-processing skills could be the most affected, while those related to assisting and caring are likely to change the least. 4 - 𝗗𝗲𝗺𝗮𝗻𝗱 𝗳𝗼𝗿 𝗔𝗜 𝗳𝗹𝘂𝗲𝗻𝗰𝘆 - 𝘁𝗵𝗲 𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝘁𝗼 𝘂𝘀𝗲 𝗮𝗻𝗱 𝗺𝗮𝗻𝗮𝗴𝗲 𝗔𝗜 𝘁𝗼𝗼𝗹𝘀 - 𝗵𝗮𝘀 𝗴𝗿𝗼𝘄𝗻 𝘀𝗲𝘃𝗲𝗻𝗳𝗼𝗹𝗱 𝗶𝗻 𝘁𝘄𝗼 𝘆𝗲𝗮𝗿𝘀: ➜ According to McKinsey, this growth is faster than for any other skill in US job postings. It is visible across industries and likely marks the beginning of much bigger changes ahead. 5 - 𝗕𝘆 𝟮𝟬𝟯𝟬, 𝗮𝗯𝗼𝘂𝘁 $𝟮.𝟵 𝘁𝗿𝗶𝗹𝗹𝗶𝗼𝗻 𝗼𝗳 𝗲𝗰𝗼𝗻𝗼𝗺𝗶𝗰 𝘃𝗮𝗹𝘂𝗲 𝗰𝗼𝘂𝗹𝗱 𝗯𝗲 𝘂𝗻𝗹𝗼𝗰𝗸𝗲𝗱 𝗶𝗻 𝘁𝗵𝗲 𝗨𝗻𝗶𝘁𝗲𝗱 𝗦𝘁𝗮𝘁𝗲𝘀:  ➜ If organizations prepare their people and redesign workflows - rather than individual tasks - around people, agents, and robots working together. More in the comments and report below! ↓ 𝗜𝗳 𝘆𝗼𝘂 𝘄𝗮𝗻𝘁 𝗱𝗲𝗲𝗽𝗲𝗿 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗼𝗻 𝗔𝗜, 𝗮𝗴𝗲𝗻𝘁𝘀, 𝗮𝗻𝗱 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻, 𝘆𝗼𝘂’𝗹𝗹 𝗳𝗶𝗻𝗱 𝘁𝗵𝗲𝗺 𝗶𝗻 𝗺𝘆 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿 𝗛𝘂𝗺𝗮𝗻 𝗶𝗻 𝘁𝗵𝗲 𝗟𝗼𝗼𝗽: https://lnkd.in/dbf74Y9E

I used to avoid extracurricular activities in my college days because I thought they would hamper my studies. But when I broke out of that trap and started participating, everything changed, I earned multiple certificates and even received the gold medal in my MBA batch. That experience taught me one thing clearly: 📌 Hard skills can get you in the room, but soft skills decide how far you go. Most people know this, but still don’t work on soft skills because they think it’s abstract and theoretical. Here are practical ways to build soft skills that don’t feel generic: 1. Communication : Record to improve, not to post Pick any topic and speak for 2 minutes while recording yourself. Watch it again and fix 3 things: filler words, confidence, clarity. Do this for 30 days, you’ll notice a transformation. 2. Networking : Give value before asking Instead of messaging strangers with “Can you help me?”, ask “How can I support you?” People remember those who contribute, not those who demand. 3. Problem-solving: Practice decision making, not perfection Pick any 2 choices, select one within 5 minutes, then evaluate the outcome later. Problem solvers are not those who are always right but they are those who can find clarity quickly. 4. Teamwork : Learn how to disagree respectfully Instead of saying “You’re wrong”, say “I see your point, but here’s another perspective.” Conflicts don’t break teams but disrespect does. ➡️ Soft skills aren’t built in classrooms, they’re built through curiosity, observation and daily practice. If hard skills sharpen your mind, soft skills strengthen your impact. Work on both. Your career will thank you. Follow Swati Mathur for more. #softskills

Singapore’s workforce is in a skills reset. What got you hired won’t keep you relevant by 2030. CORE (Double Down) Human skills no machine replicates: • Critical & Creative Thinking • Leadership & Influence • Empathy & Listening • Self-Management & Motivation • Learning Agility EMERGING (Upskill Now) Demand is exploding across Singapore’s digital-green economy: • AI & Data Literacy • Cyber & Network Fluency • Sustainability Intelligence • Talent & Capability Design OUT-OF-FOCUS (Deprioritise) Routine, rule-based, tool-specific skills — automate or move on. Reality Check The edge isn’t tech alone. It’s the fusion of human judgment with digital fluency. Those who can lead with empathy, think critically, and learn fast will own the future of work. What you can do: 1. Audit: list 6 skills you use weekly and tag each Core/Emerging/Out-of-Focus. 2. Close gaps: pick one Core to master and one Emerging to apply in a real project within 90 days. 3. Institutionalise: align learning to SkillsFuture/Jobs-Skills frameworks and employer demand data.  Outcomes you must measure (minimum) • Two demonstrable projects in 6 months that show a Core skill applied with an Emerging capability. • Evidence of impact (time saved, revenue enabled, risk reduced, stakeholder adoption). 

Your sales managers are drowning in data—but starving for clarity. I was on a call last week with a VP of Sales who showed me his dashboard. 47 different metrics. I asked him : "Which number, if it moved 20% this month, would change everything?" Silence. Here's what I see happening: Leaders know *something* is off. Pipeline isn't converting. Reps are busy but not productive. Deals are slipping. But they can't pinpoint the actual behavior or skill gap that's causing it. Here's how to actually diagnose what's broken (and fix it fast): —— Step 1: Pick ONE North-Star Metric Not 10. Not 5. One. What's the single number that, if improved, would cascade into revenue growth this quarter? Could be: → Connect rate → Discovery-to-demo conversion → Demo-to-proposal rate → Close rate Pick the constraint. Ignore the rest for now. —— Step 2: Work Backward to the Behaviors Metrics don't move themselves. Behaviors move metrics. Ask: What are the 3–5 specific actions that directly influence this number? Example—if your North-Star is close rate: • Multi-threading (are reps building champion + EB relationships?) • Next-step clarity (is every call ending with a concrete commitment?) • Objection handling (are reps folding on pricing or timeline pushback?) Now you have a target. You know exactly what behaviors to inspect and improve. —— Step 3: Inspect the Work, Not Just the Outcome Most managers live in lagging indicators. They see the deal lost, the pipeline gap, the missed forecast—after it's too late. Top leaders inspect leading behaviors weekly: → Listen to 2–3 discovery calls per rep. Score them on your behavior checklist. → Review pipeline hygiene: Are next steps clear? Are close dates realistic? → Check activity quality: Are reps reaching the right people, or just burning through volume? You'll spot the gap in week one. You can course-correct in week two. —— Step 4: Use BIPSY to Diagnose the Root Cause When a behavior isn't happening, most managers assume it's a skill problem and throw training at it. But the issue might be: B – Behavior: They don't know they should be doing it. I – Issue Diagnosis: We don't know the CAUSE of the problem. P – Process: There's no clear standard or it's not reinforced. S – Skill: They know what to do but can't execute it well. Y – You (Impact): YOU as the leader aren't doing the right things. Diagnose correctly, and your fix is 10x faster. Don't guess. Diagnose. —— Step 5: Coach the Behavior Until It Sticks One conversation won't change anything. Great managers build a weekly rhythm: Monday: Inspect the work (calls, pipeline, activity). Tuesday–Thursday: Coach the gap in 1:1s with real examples. Friday: Measure early proof (did the behavior improve?). Rinse and repeat. This is system force, not brute force. The Bottom Line: Your team doesn't need more dashboards, more meetings, or more motivation. They need clarity and specific actions.

⚖️Generative AI in EU law 🔍 This paper serves as a critical analysis of the AI Act, identifying gaps and challenges in addressing the rapidly advancing applications of Generative AI. It provides recommendations to ensure the safe and compliant deployment of LLMs. 🚀 Regarding liability: 🎯 Benefits The Product Liability Directive and AILD provide valuable structures for addressing liability in GenAI applications by recognizing the potential liability from post-deployment learning. This scope supports claims for damages, including rights violations, and addresses AI opacity and information asymmetry between providers and users. Both directives shift the burden of proof, requiring providers to disclose relevant information if harm is suspected. 🎯Gaps Both directives rely on the AI Act, which has limitations when applied to General-Purpose AI (GPAI) models. Initially, the AI Act classified GPAI as high-risk by default, but it has since adopted a 'systemic risk' approach. Yet, it lacks clear criteria for defining societal risks specific to GPAI, creating ambiguity around liability and making it challenging to determine the conditions under which GenAI falls within AILD’s scope. 🎯 Recommendations for a Tailored Code of Practice (CoP) The authors recommend establishing a CoP for GPAI models presenting systemic risks. This CoP would clarify the model’s compliance with the AI Act and provide a framework for risk management specific to GenAI. Extending the disclosure mechanism and rebuttable presumption of causation to all GPAI models would also enhance accountability, as GenAI developers typically possess incident-relevant information and should be obligated to share it. 🎯Clarifying Model Development and Data Intent The lack of a singular purpose in GenAI models complicates risk prediction and compliance assessments as required by the AI Act. To manage risks more effectively, the authors propose emphasizing criteria such as model scalability, input diversity, and transparent data usage objectives. For models trained on restricted datasets that rely on few/zero-shot learning capabilities, developers may need to disclose auxiliary information, thereby clarifying links between observed and unobserved object classes and aligning with transparency goals. 🎯Incorporating Ethical and Technical Safeguards The paper suggests combining conventional fault criteria with additional ethical and technical safeguards within the CoP. These would guide GenAI developers to: 🔸 Enhance Data Transparency: Document data intent and collection methods. 🔸 Ensure Data Quality: Construct representative datasets of sufficient quality, reducing risks of overfitting and increasing generalizability. 🔸 Implement (Pro)Active Monitoring: Includes reporting potential harm incidents and forming alliances with credible third-party organizations for validation and evidence access. 🔗 https://lnkd.in/dERy5n9u #AI #AIAct

Want to level up your career? Skip another certificate. Double down on these skills: Soft skills aren't "soft". They matter in every role, They don't lose value, And they're more and more what employers hire and promote for. Especially in an AI-driven world. Yet for some reason it's still much easier to find courses on hard skills. And soft skill training is rare. Let's fix that. Here are 16 of the most important soft skills, With do's and don'ts to help you build yours: 1) Strong Work Ethic ↳Do: Work hard without needing to be asked and without complaining ↳Don't: Think this is about hours - results matter most of all 2) Professional Conduct ↳Do: Earn trust by speaking and acting maturely at all times ↳Don't: Assume you can cross the line just because the setting feels relaxed 3) Growth-Oriented Mindset ↳Do: Invite feedback, stay open to learning, and apply both ↳Don't: Believe you already know it all 4) Dependability ↳Do: Do what you say you will do, by when you said you would do it ↳Don't: Make promises you won't keep 5) Flexibility ↳Do: Rework your plan when you get new information ↳Don't: Refuse to adjust after setbacks 6) Attentive Listening ↳Do: Listen to understand, not to reply, and validate what people say ↳Don't: Ignore the importance of body language 7) Self-Insight ↳Do: Know how others experience your words and actions ↳Don't: Avoid self-reflection or act like you're above critique 8) Managing Your Time ↳Do: Set priorities and stay organized, so you keep your work under control ↳Don't: Let distractions hijack your attention and drain your time 9) Emotional Control ↳Do: Learn to spot emotions and manage your responses ↳Don't: Skip the pause when things get heated 10) Being a Good Teammate ↳Do: Be someone people enjoy working with ↳Don't: Think this means being a pushover - you can still be yourself 11) Clear Communication ↳Do: Speak and write clearly and simply ↳Don't: Use complicated language, hide your point, or ramble 12) Reading People ↳Do: Notice reactions, body language, and other people's mood ↳Don't: Avoid asking when you're unsure how they're feeling 13) Self-Motivation ↳Do: Start projects fast and without being asked ↳Don't: Need constant hand holding or repeated encouragement 14) Team Collaboration ↳Do: Work well with others, sharing ideas and credit ↳Don't: Assume you'd be better off solo 15) Mental Toughness ↳Do: Treat every setback like a lesson ↳Don't: Stay down after you get knocked down 16) Personal Integrity ↳Do: Be honest and ethical, whether or not anyone will notice ↳Don't: Think you can cover things up Master these, and you'll succeed in any role. What skills am I missing? --- ♻️ Repost to help your network level up their careers. And follow me George Stern for more professional growth content.

LinkedIn's #GreenSkills report shows surging demand for green talent. Yet experienced sustainability professionals I know, can't find work. The disconnect? It's not about skills. It's about systems. Three reasons LinkedIn data misses this gap: 1. Hiring systems haven't evolved. Companies want "green talent" but recruit through industrial-age filters. They ask for credentials that don't exist yet. Scope that doesn't match reality. Linear experience in non-linear roles. The result is that qualified people are stuck outside locked gates. 2. Green roles sit in the wrong place. Most sustainability positions hover at the organisational periphery; advisory rather than authoritative. But real transformation needs these roles at the decision making core. This sees inexperienced internal hires being moved incrementally, rather than outside experience brought in for strategic senior roles. 3. We're misreading the market. "Demand" isn't just open positions. "Supply" isn't just available people. The real gaps exist where job titles don't map to systems-level work. Companies seek green "generalists" when they need systems architects. Accountability structures neutralise green roles before they start. We need to stop adding green people to beige systems. Start redesigning systems for the green economy. The talent is ready. The systems aren't.

According to the LinkedIn 𝐆𝐥𝐨𝐛𝐚𝐥 𝐆𝐫𝐞𝐞𝐧 𝐒𝐤𝐢𝐥𝐥𝐬 𝐑𝐞𝐩𝐨𝐫𝐭 𝟐𝟎𝟐𝟓, green talent is growing 3.4 times faster than overall talent demand. Yet only 𝐨𝐧𝐞 𝐢𝐧 𝐞𝐢𝐠𝐡𝐭 𝐰𝐨𝐫𝐤𝐞𝐫𝐬 𝐭𝐨𝐝𝐚𝐲 𝐡𝐚𝐬 𝐚𝐭 𝐥𝐞𝐚𝐬𝐭 𝐨𝐧𝐞 𝐠𝐫𝐞𝐞𝐧 𝐬𝐤𝐢𝐥𝐥. This gap is reshaping what the future of work looks like. Between 2020 and 2024, global green talent grew by 27 percent, while India grew even faster at 32 percent. Green job postings on LinkedIn increased by 22 percent last year. Sectors like renewable energy and construction now show 40 percent higher demand for green skilled professionals, and finance and consulting have seen a 26 percent surge in ESG and sustainability related roles. Sustainability is no longer a specialised domain. It is becoming a foundational capability across industries. In Asia Pacific, where green upskilling demand is rising the fastest worldwide, India is among the top markets where the gap between green skills demand and supply is widening at the quickest pace. 𝐓𝐡𝐞 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝐢𝐬 𝐧𝐨𝐭 𝐰𝐡𝐨 𝐰𝐢𝐥𝐥 𝐠𝐞𝐭 𝐚 𝐠𝐫𝐞𝐞𝐧 𝐣𝐨𝐛. 𝐓𝐡𝐞 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝐢𝐬 𝐰𝐡𝐨 𝐰𝐢𝐥𝐥 𝐬𝐭𝐚𝐲 𝐫𝐞𝐥𝐞𝐯𝐚𝐧𝐭 𝐢𝐧 𝐚 𝐠𝐫𝐞𝐞𝐧 𝐞𝐜𝐨𝐧𝐨𝐦𝐲. From client work and observing teams, one pattern is consistent. Professionals who can translate sustainability into everyday decision making get invited into different conversations. Their work becomes strategic rather than transactional. 𝐁𝐚𝐬𝐞𝐝 𝐨𝐧 𝐭𝐡𝐞 𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧 𝐆𝐫𝐞𝐞𝐧 𝐒𝐤𝐢𝐥𝐥𝐬 𝐑𝐞𝐩𝐨𝐫𝐭, 𝐭𝐡𝐞 𝐦𝐨𝐬𝐭 𝐯𝐚𝐥𝐮𝐚𝐛𝐥𝐞 𝐬𝐤𝐢𝐥𝐥𝐬 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐧𝐞𝐱𝐭 𝐝𝐞𝐜𝐚𝐝𝐞 𝐢𝐧𝐜𝐥𝐮𝐝𝐞 Sustainability strategy Environmental management Circular economy thinking Carbon accounting Renewable energy systems ESG reporting Climate risk assessment People who start using language like “we optimise for resource efficiency” or “we evaluate material impact before execution” begin to stand out. They signal readiness for a future that is already here. Sustainability is becoming a marker of credibility, not a job title. 𝐀 𝐭𝐫𝐮𝐭𝐡 𝐭𝐡𝐞 𝐫𝐞𝐩𝐨𝐫𝐭 𝐫𝐞𝐢𝐧𝐟𝐨𝐫𝐜𝐞𝐬 Relevance in the coming decade will belong to those who embed green thinking into their current roles long before they apply for a green job. 𝐖𝐡𝐢𝐜𝐡 𝐠𝐫𝐞𝐞𝐧 𝐬𝐤𝐢𝐥𝐥 𝐰𝐢𝐥𝐥 𝐲𝐨𝐮 𝐟𝐨𝐜𝐮𝐬 𝐨𝐧 𝐢𝐧 𝐭𝐡𝐞 𝐧𝐞𝐱𝐭 𝐬𝐢𝐱 𝐦𝐨𝐧𝐭𝐡𝐬, 𝐚𝐧𝐝 𝐡𝐨𝐰 𝐰𝐢𝐥𝐥 𝐢𝐭 𝐬𝐡𝐚𝐩𝐞 𝐲𝐨𝐮𝐫 𝐩𝐫𝐨𝐟𝐞𝐬𝐬𝐢𝐨𝐧𝐚𝐥 𝐬𝐭𝐨𝐫𝐲? Source: LinkedIn Green Skills Report 2025 #LinkedInGreenSkills #COP30 #FutureOfWork #CareerGrowth #Sustainability #GreenSkills #GreenerTogether #LinkedInNewsIndia