Workforce Automation Impact

New! We analyzed a billion job postings globally, and the results may surprise you: job numbers and wages are rising. Let’s dive in. For the second year running, the 2025 Global AI Jobs Barometer from PwC shows that productivity and wages are not just rising, they’re accelerating, even in roles that are most amenable to automation. Our research spans six continents and includes data from 24 countries and territories. 💭 100% of industries are expanding their usage of AI (even industries less obviously exposed to AI such as mining and construction) 📊 Since 2022 when awareness of AI's power surged, productivity growth in industries best positioned to adopt AI has nearly quadrupled (while falling slightly in industries least exposed to AI) 3️⃣ Industries most able to use AI have 3x higher growth in revenue generated by each employee  🪙 Workers with AI skills command a 56% wage premium (up from 25% last year) ⚒️ Skills sought by employers are changing 66% faster in occupations most exposed to AI (like financial analyst) versus least exposed (like physical therapist) – up from 25% last year . AI continues to act as an amplifier of human expertise — not a replacement for it, despite what the headlines might suggest. The prime example being that job growth is occurring even in roles where "automation" is playing the biggest role (like customer service and software engineering). Job cuts and doomerism make headlines, but job creation takes longer to materialize and to be recognized. It’s the difference between weather and climate, and why we call this report a "barometer". As the shifting sands of the past two years begin to settle into clearer patterns, there’s never been a better time to dive in, get hands-on, and lead your teams through this transformation. Link to the full report below.

While I’m seeing more commentary about nascent improvement in return to office and office leasing, a reversion to “normal” is still a long way off. Unfortunately, changes in the way we work are, at least significantly, structural in nature – meaning much of the shift to remote and hybrid work that was accelerated by COVID is probably here to stay. But a lower long-run average level of office space usage per worker is not the only demand headwind ailing office. There is also the issue of anemic job growth in many office-using sectors. Year-over-year as of November 2024, employment in the finance & insurance and management of companies sectors grew by just 0.4% and 0.3%, respectively. Employment declined in the information (-0.4%) and administrative & support services (-1.0%) sectors, during the same period. This weak hiring trend began in 2023. Growth has been better in the professional, scientific & technical services sector over the past year, but even this sector has seen limited growth over the past six months. So, the big question is whether weaker office-using job growth is a symptom of a tight labor market and cyclical headwinds related to the higher interest rate environment or whether there is something more structural going on here as well. Are technology-driven productivity gains beginning to materially impact headcount? and if so, is slower job growth set to linger? or will more productive and profitable companies lead to an acceleration in hiring over the medium- to long-term? The answers to these questions, and resultant investment outcomes for office property owners, are likely to vary greatly by market, location, and asset quality.

How we saved 10+ hours weekly by giving finance a simple interface. Our finance team was processing invoices the same way for years: 1. Email attachments → 2. Manual download → 3. Print → 4. Physical signature → 5. Scan → 6. Manual data entry The entire cycle took 3-5 days. The request to "build a proper approval system" kept getting deprioritized—it felt like a multi-month project. We reframed the problem: We didn't need a complex system. We just needed to connect two things: the data from our accounting software's API and a simple list where the right people could click "Approve" or "Reject." What actually got built: • A single-page app that pulls unpaid invoices automatically • Logic that routes invoices over $5k to directors, others to managers • A comment field for rejections • A basic audit log showing who approved what and when What changed: ✅ Approvals now happen in under 24 hours ✅ The finance team stopped chasing paper trails ✅ Vendors get paid faster ✅ Every decision is logged automatically The takeaway: Sometimes "digital transformation" isn't about big platforms. It's about giving a team one less PDF to manage by building a simple, focused tool that sits on top of the data they already use. What's the most stubborn, repetitive task in your team's workflow? Often the highest-impact tools are the smallest ones that remove a single point of friction. https://uibakery.io/ #ProcessAutomation #FinanceTech #OperationalEfficiency #DigitalTransformation

In my experience, there's a LOT of tacit knowledge about how organizations operate that an AI simply won't know and can't effectively use without workers who are digitally literate and understand computational thinking. The reality is that, despite the rapid advancements in AI, the digital skills of many office workers remain, frankly, abysmal. This represents not a challenge but a tremendous opportunity for disruption in the workplace, if the right talent development strategy is employed. Enabling workers to not only use but also to enhance AI tools through their own deep expertise in the business can transform these threats into allies. AI's potential to displace jobs may have served as a wakeup call, for better or worse. However, the most effective strategy isn't to compete against this wave but to ride it. Integrating AI with the tacit knowledge of subject matter experts, those who understand the intricacies of the business, ensures an organization where technology enhances human capability, not replaces it. This blend of technical science and communicative art is the winning combo for crafting machine-readable prompts and processes for the business.

Entire professions are experiencing automation-driven displacement at unprecedented speed - and most professionals remain unaware until their role becomes obsolete. After 25 years in executive recruitment, I'm witnessing systematic workforce transformation that's eliminating traditional job categories across industries. Customer service, data analysis, content creation, and administrative functions are being automated faster than workers can adapt. However, the professionals successfully navigating this transition aren't resisting technological change - they're strategically positioning themselves as automation enablers. The survival strategy for automation-resistant careers: 1. Skill stacking: combining uniquely human capabilities with AI amplification 2. Technology partnership: becoming the strategic director of automated processes 3. Value migration: shifting focus to high-level strategy while delegating execution to AI 4. Relationship cultivation: building trust-based connections that require human judgment 5. Continuous capability development: maintaining learning velocity that exceeds automation adoption The fundamental shift: viewing AI as a productivity multiplier rather than a job threat. Organizations need professionals who can maximize their technology investments, not workers who compete with their systems. Career security in an automated world requires becoming indispensable through strategic technology collaboration. The professionals thriving in this environment position themselves as essential bridges between human decision-making and automated execution. Your career resilience depends on adaptation speed, not resistance intensity. Sign up to my newsletter for more corporate insights and truths here: https://vist.ly/32bji #automation #ai #futureofwork #careeradvice #careerstrategy #executiverecruiter #eliterecruiter #jobmarket2025 #profoliosai #digitaltransformation

A new paper from David Autor, in collaboration with Neil Thompson, makes an important contribution to explaining how AI is likely to impact labor markets. Based on a rigorous model, confirmed with an analysis of 40 years of data, they provide a nuanced perspective on how automation impacts job employment and wages. Essentially, this depends on the extent to which easy tasks are removed from a role and expert ones are added, and how specialized a role becomes as a result. When jobs gain inexpert tasks but lose expertise, wages decline, but employment may increase. Think of how taxi driving became less specialized, and well-paid, but more common, due to Uber. In contrast, when technology automates the easy tasks inside a job, the remaining work becomes more specialized. Employment falls because fewer people now qualify, but the scarcity of expertise drives wages up. This is what seems to be happening with proofreading, which is now less about spell-checking and more about helping people to write, leading to lower job numbers but higher average wages. Their model helps us to understand the impacts of AI on labor markets. For instance, why AI tools can raise wages for senior software engineers, but decrease employment, while simultaneously reducing earnings, and increasing employment, for more entry level software engineering roles.

AI is fundamentally reshaping our workforce, but the impacts are nuanced. The latest report, “Potential Labor Market Impacts of Artificial Intelligence: An Empirical Analysis,” by The White House Council of Economic Advisers, provides critical insights for leaders that will impact everyone's future.. 📊 Key Findings: ✅ 𝐆𝐫𝐨𝐰𝐭𝐡 𝐢𝐧 𝐇𝐢𝐠𝐡-𝐂𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲, 𝐀𝐈-𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐑𝐨𝐥𝐞𝐬 Roles requiring advanced AI skills have increased by 30% over the last five years. Positions such as AI ethics officers and data scientists are on the rise, indicating a shift toward more complex, creative work. Occupations that integrate AI effectively are growing twice as fast as average, suggesting AI's role in complementing human skills rather than replacing them. ❌ 𝐇𝐢𝐠𝐡 𝐑𝐢𝐬𝐤 𝐨𝐟 𝐉𝐨𝐛 𝐃𝐢𝐬𝐩𝐥𝐚𝐜𝐞𝐦𝐞𝐧𝐭 𝐢𝐧 𝐋𝐨𝐰-𝐒𝐤𝐢𝐥𝐥 𝐑𝐨𝐥𝐞𝐬 40% of current jobs are at risk due to high AI exposure but low skill requirements, particularly in administrative and routine manual tasks. These jobs are declining at a rate of 2% annually. Sectors like customer service and data entry are vulnerable, raising concerns about job security and economic stability in these fields. 📍 Regional Disparities: ✅ 𝐎𝐩𝐩𝐨𝐫𝐭𝐮𝐧𝐢𝐭𝐢𝐞𝐬 𝐢𝐧 𝐓𝐞𝐜𝐡 𝐇𝐮𝐛𝐬 Tech-centric regions like Silicon Valley show a high concentration of new, AI-driven job creation, reflecting significant economic opportunities for those regions. Urban centers with strong tech clusters are emerging as key players in AI employment, driving innovation and growth. ❌ 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 𝐟𝐨𝐫 𝐑𝐮𝐫𝐚𝐥 𝐚𝐧𝐝 𝐒𝐦𝐚𝐥𝐥𝐞𝐫 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐢𝐞𝐬 Rural areas and smaller towns are facing increased risks of job losses due to AI, without comparable opportunities for new AI-driven roles. This geographic imbalance could exacerbate regional economic disparities. 👉 Here are my questions for Leaders: 1️⃣ Are we ready to leverage AI’s potential while minimizing risks? How are we preparing our teams for a future where AI enhances human capability? 2️⃣ What is our reskilling strategy? With 40% of jobs potentially vulnerable, how are we investing in upskilling our workforce to transition into growth-oriented roles? 3️⃣ How can we balance geographic and economic disparities? Are we focusing enough on regional strategies to ensure inclusive growth? As leaders, our role is to harness AI's potential to foster a resilient, inclusive, and dynamic workforce. Are we ready to lead this change and shape the future of work?

Is AI creating new jobs for construction workers? Absolutely. Because AI doesn’t build itself. People do. While headlines fixate on AI “taking jobs,” what operators are seeing on the ground tells a different story. AI is accelerating demand for frontline work – construction, skilled trades, and the physical infrastructure powering data centers. This shift is colliding with a hard reality: nearly 20% of the construction workforce is nearing retirement. The gap isn’t theoretical, it’s operational. The industry will need 349,000 new workers this year, and 456,000 by 2027. At the same time, Gen Z, the toolbelt generation, is stepping in. They’re choosing trades for financial security, flexibility, and careers they know will remain essential and increasingly tech-enabled. They already represent nearly 30% of the global workforce, and that share is growing. Here’s the uncomfortable truth: this isn’t a labor shortage. It’s an operating model problem. The companies that win won’t just hire faster. They’ll run hourly work better: rapid onboarding, flexible scheduling, and systems designed for multi-job, multi-site workers. That’s where AI’s real workforce impact shows up: on the front lines and inside daily operations. At Deputy, we see this every day across thousands of operators. The leaders pulling ahead are the ones treating workforce infrastructure as a strategic advantage, not an afterthought. https://lnkd.in/guiZAUQK

Here’s what the headlines are missing: AI isn’t just taking entry-level jobs. It’s reinventing them. Yes, recent research suggests a decline in some traditional entry-level roles in coding, customer service, and beyond. But that’s not the whole story. We’re also seeing AI create something new: the chance for people to learn faster and step into bigger responsibilities much earlier in their careers. Take Jessica Moran, a young associate at KPMG featured in a recent Washington Post article. A task that once consumed 6–8 hours of her day now takes one minute with AI. More importantly, she's using that reclaimed time for risk assessments, project management, and strategic work—responsibilities that used to take years to reach. When AI is a collaborator from day one, entry-level no longer means “waiting your turn.” It becomes a launchpad for creativity, problem-solving, and leadership opportunities. The future of work isn't about fewer opportunities—it's about redesigning them into better ones.   https://lnkd.in/ekxziz8A

Case Tuesday: Workflow Optimization It’s a typical morning in a large hospital radiology department: Dozens of CT, MRI, and X-ray studies waiting to be read Some cases are routine follow-ups, others are life-threatening emergencies Radiologists must balance speed, accuracy, and communication with busy clinical teams The challenge: Critical cases can get buried in a growing worklist Reporting bottlenecks delay clinical decision-making Communication gaps slow down patient care across departments #AI is stepping in to help beyond diagnosis itself: Automatically prioritizing urgent cases (e.g., suspected stroke, hemorrhage, PE) Routing studies to the right subspecialist radiologist Streamlining reporting and reducing administrative burden Integrating with hospital systems to ensure faster handoff to clinicians The radiologist is still at the center of the process but now supported by an ecosystem that reduces friction and ensures patients get the right care, faster. The impact: More efficient workflows that free up radiologists to focus on complex cases Shorter turnaround times for critical findings Improved collaboration across multidisciplinary teams As Chief Medical Officer at GE HealthCare, I see workflow optimization as the “hidden superpower” of AI; less visible than detecting a tumor or a clot, but just as vital for ensuring patients get the care they need at the moment they need it. Where do you see the greatest potential for AI in radiology helping with diagnosis, or transforming the workflow itself? #CaseTuesday #RadiologyWorkflow #AIinHealthcare #FutureOfMedicine #GEHealthcare