How Generative AI Is Changing Workforce Automation

Harvard just dropped a study on AI and the workforce: "Generative AI as Seniority-Biased Technological Change: Evidence from U.S. Resume and Job Posting Data." It perfectly complements Stanford’s report, published only a a few days earlier. Together, these are the clearest signals yet of how Generative AI is not just changing productivity; it’s reshaping the very architecture of careers. Stanford (ADP payroll data): Since late 2022, employment among 22–25 year-olds in AI-exposed jobs has fallen ~13%, while 35–49 year-olds in the same roles have grown ~9%. Automation-heavy AI uses cut junior jobs; augmentation-heavy ones sustain or even expand them. Harvard (62M workers, 285K firms): At firms that adopt AI (measured via “AI integrator” hires), junior headcount falls 7.7% within six quarters. Hiring slows by ~10% per quarter, even as promotions rise 5%. In Wholesale & Retail, junior hiring contracts by nearly 40%. And graduates from mid-tier universities are the hardest hit. The message is clear: AI is shrinking the base of the career ladder; fewer entry roles, faster promotions for those already inside, and a premium on tacit, senior-level capabilities. The opportunity is differentiation. Companies that design AI-augmented apprenticeships, run talent impact diagnostics, and adopt augmentation-first operating models will not only protect their pipelines but also build the next generation of leaders faster. It seems like AI isn’t just an efficiency story. It’s a career architecture story. Those who act intentionally now will set the tone for an AI-powered workforce that is leaner, smarter, and more resilient. 🔗 Link to Harvard's report ("Generative AI as Seniority-Biased Technological Change: Evidence from U.S. Resume and Job Posting Data"): http://bit.ly/47SyfTC 🔗 Link to Stanford's report ("Canaries in the Coal Mine?"): http://bit.ly/45Ttgzo

Just a thought before the weekend. With the introduction of new technologies certain tasks traditionally performed by junior staff are being automated. In many cases the junior position is eliminated, and residual task is redistributed to more senior employees, actually increasing their workload. Historically, the roles of secretaries and accounting clerks exemplify this transition. With the advent of personal computers and advanced software, routine tasks like typing, scheduling, and basic correspondence management, once the domain of secretaries, have been automated. Consequently, these tasks have increasingly been incorporated into the responsibilities of professionals themselves, including managers and executives. In accounting, sophisticated software has made the data entry and basic bookkeeping roles of accounting clerks redundant. These tasks are now often handled directly by accountants and finance managers, adding to their comprehensive role. In creative and technical fields, such as graphic design and engineering, advanced tools have automated tasks that were typically handled by junior staff. Senior professionals in these areas now directly engage with tools like CAD software, reducing the need for junior drafting roles. The future, shaped by GAI, will likely see an expansion of these trends. In industries like marketing and advertising, AI’s capacity to generate basic creative content might reduce the need for certain junior roles. Instead, senior marketing professionals might oversee the refinement and strategic integration of AI-generated materials. Likewise, legal services might witness AI automating document drafting and basic research, once the remit of junior staff, shifting oversight and strategic refinement to senior lawyers. Moreover, GAI is expected to make complex business platforms more accessible to a broader range of employees. This will enable senior employees without deep technical expertise to perform tasks that were previously the preserve of specialists. Consequently, the skill requirements for senior roles may grow. The result is that many professionals and managers will be responsible for a long list of simple and quick tasks, that once took much longer to perform, and were the responsibility of more junior workers. #generativeai #ai #tasks #automation

The biggest AI impacts won’t be borne out in a calculus of jobs but rather in seismic shifts in the level of expertise required to do them. In our article in Harvard Business Review, Joseph Fuller, Michael Fenlon, and I explore how AI will bend learning curves and change job requirements as a result. It’s a simple concept with profound implications. In some jobs, it doesn’t take long to get up to speed. But in a wide array of jobs, from sales to software engineering, significant gaps exist between what a newbie and an experienced incumbent know. In many jobs with steep learning curves, our analysis indicates that entry-level skills are more exposed to GenAI automation than those of higher-level roles. In these roles, representing 1 in 8 jobs, entry-level opportunity could evaporate. Conversely, about 19% of workers are in fields where GenAI is likely to take on tasks that demand technical knowledge today, thereby opening up more opportunities to those without hard skills.   Our analysis suggests that, in the next few years, the better part of 50 million jobs will be affected one way or the other. The extent of those changes will compel companies to reshape their organizational structures and rethink their talent-management strategies in profound ways. The implications will be far reaching, not only for industries but also for individuals and society. Firms that respond adroitly will be best positioned to harness GenAI’s productivity-boosting potential while mitigating the risk posed by talent shortages.   I hope you will take the time to explore this latest collaboration between the The Burning Glass Institute and the Harvard Business School Project on Managing the Future of Work. I am grateful to BGI colleagues Benjamin Francis, Erik Leiden, Nik Dawson, Harin Contractor, Gad Levanon, and Gwynn Guilford for their work on this project. https://lnkd.in/ekattaQA #ai #artificialintelligence #humanresources #careers #management #futureofwork