AI Job Displacement: Who Will Adapt Best

37.1 million Americans (~23% of the workforce) work in jobs highly exposed / vulnerable to displacement by AI. A new paper from The Brookings Institution investigates, “If AI does cause job displacement, who is best positioned to adapt, and who will struggle most?” It’s a worthwhile read. https://lnkd.in/ePPustew Brookings introduces the concept of ‘adaptive capacity’ into the AI impact discussion to evaluate the worker's ability to adjust to a potential job loss. They conclude that: Of the 37 million Americans in highly AI-exposed jobs (~23% of the workforce), about 71% (~26.5 million) are best positioned to weather a potential job transition. While software developers, financial managers, and lawyers may face high AI exposure, they typically have savings, transferable skills, and strong networks and should be able to land on their feet, that’s not to say such adaptation would be easy or without stress and personal cost. However, 6.1 million workers (~4% of the workforce) face a double threat. According to Brookings these workers are likely to be faced with both high AI exposure AND low adaptive capacity: primarily office clerks, secretaries, receptionists. About 86% are women. They often lack the financial cushion, diverse skill sets, or local job opportunities that make transitions manageable. It should also be noted that two workers in equally exposed occupations can face wildly different outcomes based on their age, savings, location, and skill transferability. I am left with a couple of questions: 1.    Are these numbers actually the best-case scenario? AI capabilities are improving quickly, could the definition of ‘jobs at risk’ be far broader and the impact much higher than the numbers envisaged? 2.    Over what timeframe does the transition occur? If AI's reach expands faster than workers can adapt, could we see additional vulnerability due to a timing mismatch? i.e. similar effect to everyone trying to sell their favorite stock at the same time? What's your take on AI's pace of advancement and impact on the workforce? #AI #FutureOfWork #ArtificialIntelligence

𝗕𝗿𝗼𝗼𝗸𝗶𝗻𝗴𝘀 𝘀𝘁𝘂𝗱𝘆 𝘀𝗵𝗼𝘄𝘀 𝗔𝗜 𝗷𝗼𝗯 𝗿𝗶𝘀𝗸 𝗶𝘀𝗻’𝘁 𝗲𝗾𝘂𝗮𝗹...𝗮𝗱𝗮𝗽𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗶𝘀 𝘁𝗵𝗲 𝗴𝗮𝗽. 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 𝘁𝗼 𝗺𝗲: When I work with companies on their AI strategy and transformation efforts, durable AI skills development for their employees is a top 3 priority. Training is key to supporting the company, but more importantly, it’s key to supporting the employees stay relevant if and when the company ever evolves away from a human workforce. 𝗢𝗻𝗲 𝗯𝗶𝗴 𝘁𝗵𝗶𝗻𝗴: Brookings Institution argues we’re over-indexing on “AI exposure” and under-measuring something more predictive of real pain: workers’ capacity to adapt if displacement hits. 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: If you’re building workforce strategy (government or enterprise), the priority isn’t “who’s exposed?” — it’s who can realistically land on their feet (and who can’t) so support dollars don’t miss the mark. 𝗧𝗵𝗲 𝗱𝗲𝘁𝗮𝗶𝗹𝘀: • The study pairs AI exposure with an “adaptive capacity” index built from savings, age, local job-market density, and skill transferability. • 37.1M workers sit in the top quartile of AI exposure; about 70% (26.5M) of them have above-median adaptive capacity. • 6.1M workers face the double bind: high exposure + low adaptive capacity — concentrated in clerical/administrative roles; 86% are women. • Some of the largest vulnerable occupations include office clerks (2.5M) and secretaries/administrative assistants (1.7M). • Geography matters: vulnerable roles show up more in college towns and state capitals, especially in the Mountain West and Midwest (examples cited include Laramie, WY; Stillwater, OK; Carson City, NV). 𝗬𝗲𝘀, 𝗯𝘂𝘁: This is an occupation-level snapshot. Two people with the same job title can have very different savings, networks, and local options — and large-scale AI shifts could change the playing field fast. 𝗚𝗼 𝗱𝗲𝗲𝗽𝗲𝗿: Measuring US workers’ capacity to adapt to AI-driven job displacement Research by Sam Manning, Tomás Aguirre, Mark Muro, and Shriya Methkupally - find it here. https://lnkd.in/gEVpub4n #AIStrategy #AITransformation #AI #ArtificalIntelligence #AITransformationCoach

Researchers from the Brookings Institution, have published compelling research that reframes how we should think about AI's labor market impacts. The study introduces an "adaptive capacity index" that goes beyond simple AI exposure measures. While 37 million U.S. workers are in highly AI-exposed occupations, the research reveals a surprising pattern: most of these workers (26.5M) actually possess strong adaptive capacity—financial resources, transferable skills, and professional networks that position them well for potential job transitions. However, the research identifies a vulnerable cohort: 6.1M workers face both high AI exposure and low adaptive capacity. These workers, 86% of whom are women, are concentrated in clerical and administrative roles. They often have limited savings, narrower skill sets, and work in smaller metro areas, particularly college towns and midsized markets in the Mountain West and Midwest - Check out the tables in the Appendix section. AI exposure alone does not tell us who is truly at risk. A software developer and an office clerk may face similar AI exposure, but their capacity to navigate displacement differs dramatically—financial analysts score 99% for adaptive capacity while office clerks score just 22%. Policymakers concerned about AI’s job displacement potential may wish to focus attention on workers with the weakest adaptive capacity, who are likely to face the highest welfare costs if displaced. How will AI-driven drug discovery and clinical trial optimization reshape lab technician and research associate roles? Are biotech hubs like Boston and San Francisco creating enough pathways for displaced administrative staff in pharma to transition into AI-augmented roles? What adaptive capacity do clinical, medical and commercial specialists possess as AI automates documentation and compliance tasks? #AI #FutureOfWork #WorkforceDevelopment #LaborMarket #AIPolicy #EconomicInequality #WorkforcePlanning #SkillsGap #WorkforceTransition #LifeSciences #Biotech #Pharma #HealthcareAI https://lnkd.in/eTBucXbv

A new approach to measuring exposure to AI-driven job loss finds that as many as 6.1 million American workers may have difficulty adapting after displacement, especially those in administrative and clerical roles, where skills are harder to transfer and new job opportunities are more limited. Mark Muro and Shriya Methkupally show that these vulnerable workers are heavily concentrated in smaller metro areas and college towns in the Mountain West and Midwest. Their research points to specific regions and occupations where policymakers may need to focus resources so that workers facing AI disruption are not left behind.

Very interesting new The Brookings Institution report summarizing early analyses of a key workforce question - If AI does cause job displacement, who is best positioned to adapt, and who will struggle most? Some points that stood out to me: The methodology “combines estimates of AI exposure with a novel measure of “adaptive capacity” that takes into account workers’ varied individual characteristics. Along these lines, the new work supplements occupation-level exposure analysis with relevant measures of workers’ savings, age, labor market density, and skill transferability in order to assess their varied capacity to weather job displacement and transition to new work.” 6.1 million workers (4.2% of the workforce in the sample) will likely contend with both high AI exposure and low adaptive capacity. These workers tend to be concentrated in clerical and administrative roles, and about 86% are women (gender shares are calculated using Lightcast data.) The AI disruptions that may befall higher-income, white collar workers may be partly mitigated by those workers’ savings, skills, and networks; while on the other hand, downside risks for less adaptive workers may be harder to manage. Transferable skills—those that can be applied across many different jobs—offer more occupational mobility than highly specialized skills. As workforce areas begin to develop strategies to mitigate the impact of AI disruption and seek to demonstrate the ROI for how programs meet current needs, I see several immediate areas of opportunity: ·       Use and scale of new AI related measures in the analysis of labor markets and implementation of career pathway and sector strategy programming ·       Define those durable, transferrable and human intelligence related skills and ensure  they are included in program and policy development – especially as Workforce Pell implementation moves forward ·       Partner with industry to ensure ongoing training and upskilling invest in both technical and resilient skills. ·       Quantify and recognize the employment value of those skills in hiring. Would welcome other thoughts and reactions! #workforce #AI #humanintelligence

AI is disruptive to the job marketplace. We don't yet know how bad it's going to be, but whatever happens AI is clearly here to stay for the foreseeable future and companies are going use AI (and automation and robotics) as much as they can to replace human workers.

Our new The Brookings Institution brief on workers' adaptive capacity in the face of #AI has a number of interesting findings. One is that women in clerical and administrative roles may tend to struggle to locate new work when displaced. Beyond that, though, one of the most suggestive takeaways is the most encouraging one: that most workers appear relatively resilient when you look at adaptivity factors such as their skills and pay. Notwithstanding significant vulnerability among admin and clerical workers, we find that AI exposure and adaptive capacity are positively correlated. That is to say, many of the occupations (say in information, finance, or legal) that are the most highly exposed to AI also contain workers with relatively strong means to manage a job transition if displacement occurs. For example, of the 37.1 million workers in the top quartile of AI exposure, 26.5 are in occupations with above-median adaptive capacity, leaving them comparatively well-equipped to adapt and find new work if necessary. They are as such some of the workers in the economy who are best able to roll with the punches of AI. This isn't to say these workers won't undergo a lot of disruption, meanwhile. Instead, the finding simply reminds us that many people have a lot of ingenuity and may well be able to ride out at least some of the first rounds of spreading AI. There's a lot of resilience out there, along with the precarity. If this is halfway true, it's one more piece of the AI riddle and a check on pessimism. * Check out the brief from Sam Manning Tomás Aguirre Shriya Methkupally and myself here: https://lnkd.in/exUcEZSu Brookings Metro Xavier de Souza Briggs Gad Levanon Francesca Gabriella Ioffreda Joe Parilla Molly Kinder Nicholas Thompson Avi Goldfarb

The impacts of AI disruption will not be evenly distributed. For example: 86% of the workers most likely to be impacted by AI-driven job displacement are women. "Capacity to adapt after job loss is not evenly distributed across the workforce. Financial security, age, skills, union membership, and the state of local labor markets are just some of the many factors that can influence the real-life consequences of job loss." Studies like this that look at "adaptive capacity" of various occupations and communities can help us understand how to prioritize resources to support those most at risk in the coming waves of change. https://lnkd.in/gcQdcwDr

New research w/ Tomás Aguirre: If AI leads to displacement, which AI-exposed workers will struggle to land on their feet after job loss? And which workers are best positioned to adapt on their own? We find that AI exposure and adaptive capacity are positively correlated. Many occupations that are highly exposed to AI also contain workers with relatively strong means to manage a job transition if displacement occurs. At the same time, 6.1 million workers are in occupations that are both highly exposed to AI and have low expected adaptive capacity. These workers are disproportionately concentrated in clerical and administrative roles, where savings tend to be lower and required skillsets are more narrow and less transferable. >80% of workers in these occupations are female. Thread here: https://lnkd.in/emgG43rc Full National Bureau of Economic Research paper here: https://lnkd.in/e6wBtbxZ And The Brookings Institution brief, written with Mark Muro and Shriya Methkupally here: https://lnkd.in/erkUrTzm

New analysis shows the U.S. labor market is both more resilient—and more uneven—than many assume when it comes to AI-driven job disruption. While 37.1 million workers sit in the highest quartile of AI exposure, the majority (26.5 million) also have above-median adaptive capacity, meaning they’re relatively well positioned to transition if displacement occurs. The concern lies with a smaller but significant group: about 6.1 million workers (4.2% of the workforce analyzed) face both high AI exposure and low adaptive capacity. These roles are largely clerical and administrative, are predominantly held by women, and are concentrated in smaller metro areas, including university towns and midsized markets across the Midwest and Mountain West. The real question isn’t whether AI will impact jobs—but who is equipped to adapt and who will need the most support. This kind of insight can help policymakers and employers focus reskilling efforts where they’re needed most. P&P Talent Group