Impact of Automation

The expansion of robots and automation is poised to significantly transform the job market and has complex implications for inequality. What do you think? Impact on Jobs: 1. Job Displacement: Robots and automation are likely to replace repetitive, manual, and routine jobs (e.g., manufacturing, logistics, and data entry). Some middle-skill jobs may also be at risk as automation technologies become more sophisticated. 2. Job Creation: New roles will emerge in robotics maintenance, programming, AI development, and other tech-focused fields. Demand for human-centric jobs, such as healthcare, education, and creative industries, may increase as these areas are harder to automate. 3. Job Evolution: Many jobs will change in scope, requiring workers to collaborate with robots or leverage automation tools for productivity. Impact on Inequality: 1. Widening Skill Gap: Workers with higher education and tech-savvy skills are more likely to benefit, while those in low-skill jobs may struggle to adapt. This divergence could exacerbate income inequality if reskilling programs are not widespread. 2. Geographic Disparities: Advanced economies with resources to invest in automation could benefit more than developing countries, increasing global inequality. 3. Ownership of Technology: Concentration of robot and AI ownership among corporations and wealthy individuals might widen wealth disparities unless equitable policies (e.g., profit sharing, taxes) are implemented. Mitigating Inequality: 1. Education and Reskilling: Governments and companies need to invest in upskilling and reskilling workers to prepare them for the jobs of the future. 2. Universal Basic Income (UBI): UBI or similar safety nets could help address income gaps caused by job displacement. 3. Fair Policies: Regulations around labor, taxation, and profit sharing could ensure that the economic benefits of automation are distributed more equitably. 4. Support for Vulnerable Sectors: Strengthening social welfare systems and providing targeted support for industries and workers most at risk. Video: @discover_our_planet_ #Innovation #Technology #Inequality

🚨 The AI Layoffs Begin – But What’s Really Behind the Headlines? Over 50,000 tech workers have been laid off in just the first six months of 2025. Microsoft. Google. Meta. IBM. Duolingo. Klarna. These aren’t startups tightening budgets — they’re the AI giants. So what’s driving this? It’s not just about cost-cutting. It’s not even purely about automation. It’s about AI alignment. A redefinition of what productivity looks like in an AI-first economy. 🔍 Microsoft is letting go of veteran engineers — including one who made TypeScript 10x faster — while investing $80B into AI this year. 30% of their code is now written by machines. 🛠️ IBM is cutting HR roles while hiring more engineers and salespeople — pivoting the workforce to AI-ready profiles. This is not about replacing humans. It’s about making space for algorithms. For scalable solutions. For a different kind of workforce. But as we celebrate efficiency, let’s pause and ask: What happens when we lose human mentorship, judgment, and creativity in the process? ⚠️ We’re entering an era where efficiency may win over empathy. And that has consequences — for culture, inclusion, and leadership. Let’s flip the narrative. AI doesn’t have to be the villain. But we must adapt. ✅ Upskill in AI collaboration — prompt engineering, oversight, ethics. ✅ Double down on human strengths — empathy, strategy, leadership. ✅ Build inclusive programs — like our AI Leadership Roadmap at net4tec | 4 WoMen Careers in Technology — that close the gender gap and prepare diverse talents for AI-driven futures. Because AI won’t replace all jobs. Just the ones that don’t evolve. This moment is not the end — it’s a call to lead. 👉 Are you future-proofing your role? Or waiting until it’s your turn? #FutureOfWork #AI #Leadership #AIAlignment #TheNewFaceOfLeadership #DigitalTransformation #Upskilling #Inclusion #AILeadershipRoadmap #net4tec

Over the past 10 weeks, I’ve interviewed 35 talent and learning leaders at Fortune 1000 companies for a report I’ll be releasing this fall. One of my favorite questions has been the very first one: 𝐖𝐡𝐚𝐭 𝐚𝐫𝐞 𝐲𝐨𝐮𝐫 𝐭𝐨𝐩 𝐭𝐡𝐫𝐞𝐞 𝐩𝐫𝐢𝐨𝐫𝐢𝐭𝐢𝐞𝐬 𝐫𝐢𝐠𝐡𝐭 𝐧𝐨𝐰?” With 105 priorities and counting, the responses vary widely given differences in industry, scope, and role (VP of Learning, talent, talent management, leadership development) but here is a slice of what has been shared so far: ➡️ AI and work transformation: Clarify what AI means for the workforce, its implications for roles, and how teams can adopt it to accelerate development and efficiency. ➡️ AI Coaching Pilot: Launch an AI-powered coaching pilot program across the organization to scale leadership development support. ➡️ Generative AI Upskilling: Upskill employees and leaders to effectively use generative AI in day-to-day work ➡️ Future of Work & Workforce Planning: Prepare for disruptions to job architecture by integrating human and digital workforces. Rethink responsibilities, structures, and collaboration models. ➡️ Change management: Embed change management capabilities at all levels, particularly around AI adoption. ➡️ New leadership Behaviors: Equip leaders with new capabilities to thrive in a changing environment, including adaptability, resilience, and the ability to lead in an AI-augmented workplace. ➡️ Skills and Career Paths - Creating paths by prioritized skills in our organization ➡️ Rethinking the Function: Redesign the talent and learning function to reflect disruption caused by AI ➡️ Change Leadership: Navigate a period of executive turnover and transition by stabilizing the leadership team, clarifying roles, and building confidence with functional business leaders. ➡️ Facilitating Connection: Partnering with our employee experience and workplace teams to use in-office team days for learning and connection ➡️ Linking Performance and Development: Redesign performance processes to connect directly to development, helping employees understand what growth means in practical and tangible terms. ➡️ Manager Development: Continue to strengthen manager capability and resources, ensuring managers are equipped to drive performance and support employee development ➡️ VP and SVP Development: Support and accelerate the growth of new vice presidents and senior vice presidents as they step into expanded leadership roles. ➡️ Building a Leadership Bench : Develop and execute a strategy for strengthening the leadership bench, with a focus on preparing our Top 200 leaders ➡️ AI/Learning : Using AI internally within the learning function and focusing on key skills in AI for client-facing practitioners ➡️ Academies For AI/Data Roles: Developing and rolling out an academy for our AI & Data Product Employees I’d love to hear your perspective: What stands out most to you about this list, or what themes are you seeing in this list?

The fastest-growing profession of this decade won't be creating AI, instead it will be: Managing the agents it spawns. Management has always evolved with technology: → Foremen directed the construction of buildings → Industrial supervisors organized factory production → Corporate managers optimized business operations → Agent Managers now orchestrate artificial intelligence This evolution marks a fundamental shift in how we organize work and create value. People who orchestrate workers are managers. People who orchestrate software are engineers. But what do we call those who orchestrate AI agents? While we figure out the terminology, this represents a new job category emerging from the advancement of AI. The distinction matters because: → Engineering builds systems with predictable outcomes → Management guides humans with emotions and incentives Agent management bridges these worlds, directing intelligence that scales like software but reasons unpredictably. What do agent managers actually do: → Provide strategic direction that AI still struggles with → Design frameworks for AI teams to operate within → Make high-level decisions about resource allocation → Create evaluation systems for quality and safety → Optimize collaboration across specialized agents This role will explode in demand because: → Enterprises are deploying specialized agent teams → Powerful AI will require more sophisticated oversight → AI is becoming a mission-critical business function → Orchestration becomes a competitive edge → Returns from effective AI management exceeds costs The most effective agent managers will: → Communicate with exceptional precision → Design robust feedback systems → Think systemically about agent interactions → Learn to anticipate how AI "thinks" differently → Balance innovation with appropriate guardrails This isn't just another tech job. We are entering an era where algorithms and data are table stakes. The true competitive edge lies in developing capabilities others can't easily replicate. Agent management is exactly this, the bridge between human strategy and AI execution that will define tomorrow's market leaders.

Pointed statistics on the reskilling imperative. Leaders see substantial overcapacity in legacy roles due to AI, as well as dramatic AI skills shortages. The pace of the shift in workforce capabilities required means that organizational capacities for reskilling will be fundamental to success. Hiring will not be sufficient, not least due to the exceptional demand for relevant talent. Focusing on reskilling will be a massive enabler for attracting and retaining talent. I consistently argue that talent is becoming more - not less - important, and that this will be driven by explicit and implicit leadership attitudes. I'm very glad to see that "human-AI collaboration specialists" are specifically mentioned as being in demand. This points to the recognition that Humans + AI organizational redesign is critical. This is absolutely not just about changing the skills mix. It is about how human skills are applied and integrated with AI capabilities. I'm sure some will say that many of those who are in the "overcapacity" group are not able to be reskilled to develop the required AI skills. From a narrow view, not everyone will be readily able to shift into specific specialist roles. But if we look at the broader scope of the emerging high-value roles, the potential for reskilling is likely significantly higher than might be immediately evident. Work design and talent need to be reworked. Job roles, workforce planning structures, decision rights, accountability, training, reporting structures, and more need to evolve to enable more rapid shifts in developing and applying the skills required for the future organization.

As companies in South Africa begin to mirror global AI adoption trends, a quiet storm is brewing. The UK’s Big Four firms ( Deloitte, EY, KPMG, and PwC) have slashed graduate intakes by up to 29%, replacing entry-level positions with AI. And here at home, we’re not far behind. South African corporates are embracing automation at a faster pace than they’re preparing the next generation of minds to lead in this new world. According to Stats SA, over 270,000 graduates were unemployed in Q1 2024. Think about that. Thousands of freshly qualified minds locked out before they can even begin. We’re digitising tasks but not digitising mentorship. We’re automating process but not automating wisdom transfer. And then we wonder why there’s a widening skills gap and a silent erosion of leadership capacity. Here’s the inconvenient truth no one wants to say out loud
🔹 AI cannot replace strategic thinking… only routine execution.
🔹 A machine can do the job, but it cannot grow into the leader.
🔹 Skipping graduate development is a short-term gain, long-term collapse. We forget that many of today’s executives once started by fetching coffee and learning from mistakes that machines are now designed to never make. But if you remove the bottom rung of the ladder, how exactly are we expecting future leaders to climb? In 5–6 years, the impact of this oversight will hit like a punch we never trained for>
– A knowledge deficit
– A shortage of competent middle management
– A workforce unable to adapt to real-time crises without algorithms to follow. This is not an anti-AI argument. Far from it. This is a call for strategic balance. We need AI, but we also need apprenticeship models, hybrid development systems and AI-assisted learning curves that elevate humans, not sideline them. If South Africa wants to become a continental AI powerhouse, we must simultaneously become a talent powerhouse. Otherwise, we are just writing our economic obituary in binary code. The question is no longer “Can AI do it?”
The question is: “Who are we becoming if AI does it all?” Let’s not build systems that are so efficient they forget to be human.

Our article on GenAI and the psychology of work is the cover article of the latest issue of Trends in Cognitive Science from Cell Press: "GenAI is rapidly transforming the workplace, not only by automating routine tasks but also by taking on cognitive, creative, and interpersonal functions once thought to be uniquely human. In this issue of Trends in Cognitive Sciences, Erik Hermann and colleagues examine how GenAI is reshaping the psychological experience of work. The authors propose that while GenAI can boost worker productivity, creativity, and collaboration, it also poses psychological threats by undermining workers’ basic needs for competence, autonomy, and relatedness. They outline five coping strategies workers use to manage these threats and highlight the importance of human-centered approaches to GenAI integration. Cover image by Malte Mueller/Getty Images." (Link to article in comment.) With Erik Hermann and Carey Morewedge Wharton AI & Analytics Initiative

🚀 The World Economic Forum Future of Jobs Report 2025 has just been published 🌍 This essential read examines the major trends shaping the global labour market—technological change, economic uncertainty, demographic shifts, the green transition, &c —and what they mean for jobs, skills, and business transformation in the second half of this decade. Here's some key insights that struck me as important for those of us driving #digitaltransformation in organisations: 🔹 60% of employers expect broadening digital access to transform their businesses. We need to do more to integrate digital tools across processes and ensure equitable access for employees 🔹 Demand for AI, big data, cybersecurity, and technology literacy is skyrocketing 🔹 BUT we have to navigate the dual realities of job creation (eg, AI specialists) and displacement (eg clerical roles). Change isn't going to be good for everyone. 🔹 Two-fifths of skills and projected to become outdated by 2030 — a terrifying proportion for both employees and employers. Up-skilling and re-skilling are going to be critical 🔹 That doesn't mean everyone needs to become a techie. Arguably the opposite — it brings the human side of work to the fore, either in face-to-face occupations or shifting the focus to creativity, flexibility, and adaptability to complement technological skills 🔹 Upskilling 59% of the workforce by 2030 will require embedding training into day-to-day operations. Create systems that encourage continuous skill development, curiosity, and adaptability 🔹 Employee health and well-being will be increasingly important as a talent retention strategy. Similarly, while DEI's reputation is being trashed by tech bros, it's still vital to broaden talent pools and foster innovation 🔹 Climate change, economic uncertainty, and demographic shifts will redefine workforce priorities If you're shaping the #futureofwork, this report highlights a bunch of opportunities to align strategy with these transformative trends. Read the report here:

According to Bloomberg Intelligence, major Wall Street banks may cut up to 200,000 jobs over the next 3-5 years due to AI - primarily due to GAI's ability to perform historically human tasks more efficiently and accurately. What roles are at risk? Back-office, middle-office, and operational roles - roles that focus on repetitive tasks like data analysis, risk evaluation, and trend assessments are vulnerable. Even entry-level hiring could see a two-thirds reduction as AI tools replace many junior analyst functions. The Forbes article shares that, "This shift toward AI is expected to increase bank profitability, with projections suggesting a 12% to 17% rise in pre-tax profits by 2027, equating to an additional $180 billion in total profits." Given the advances in generative AI's ability to perform cognitive/white collar work, which will only continue and accelerate, I am left wondering where will the workers displaced by AI find their place in the job market? While upskilling and reskilling sound promising, there’s no guarantee the economy has the dynamic capacity to absorb this massive workforce shift. While unemployment figures remain low today, if they remain low in the next 3-5 years, I believe it will be more representative of people taking jobs they would not otherwise be interested in as a means of survival rather than a reflection of a thriving job market. This could mask deeper economic challenges, such as underemployment, stagnant wages, and a growing mismatch between available roles and the skills of displaced workers. How do we measure true economic health in an era where AI is reshaping the labor market, and are we prepared to address the quality of employment, not just the quantity? https://lnkd.in/e68Sqk5W #FutureOfWork #AI

Is this the most scary and exciting development for Safety Professionals this century? Today, I tested one of the most disruptive shifts coming to knowledge work: Computer Using Agents (CUAs). Using OpenAI’s new Operator capability, I asked my AI assistant to: A) Book a hire car for the upcoming NSW Mining Conference. B) Build a PowerPoint presentation on AI for Mining Professionals. I simply spoke the requests and while I sat back with a cup of tea the agent: ✅ Spun up a browser ✅ Navigated websites ✅ Clicked through forms ✅ Booked a car (after a bit of faffing because it was trying to book from a US server but got there in the end) ✅ Developed a slide deck This wasn’t a shortcut. It literally did the tasks for me, end-to-end. Now imagine this in a health and safety context. You could speak or type: “Create a hazard report in [your safety system]” “Show me the last 5 high-potential near-miss driving incidents in [your database]” Your CUA will log in, navigate the system, search, generate and even pre-fill reports... autonomously #mindblown No need to learn every system interface. No need to click 12 buttons to do a simple task. Just ask...and it does. For HSE professionals juggling reporting, assurance, analysis and admin this is bonkers automation. A digital co-worker. Is it scary? Yes! Is it exciting? Yes! We are at the front edge of a wave that I has significant potential to transform how we engage with digital systems; from doing through the computer, to delegating to the computer. Please experiment responsibly... and let me know your thoughts. #SafetyInnovation #SafetyTech