人工智能与未来工作：重塑人类工作图景

AI and thefuture of work Reshaping thelandscape of Contents Executive summary4Introduction6Anticipated workforce disruptions7Job impact distribution8Job automation8Job augmentation9Skills evolution11Reskilling and upskilling12Growth areas13Business function applications13Supplement: How can HR leadersplan and drive change in the face of AI?14Training and development priorities15Demographic considerations16Implementation strategy15Organizational change requirements15Conclusion16References17 Executive summary The TIAA Institute initiated research to explore AI’s impact on work through a human-centeredlensIn this context, human-centered AI prioritizes human well-being and agency throughoutthe AI lifecycleThe objective was to understand how AI, a transformation comparable tothe Industrial Revolution, is reshaping workforce structures and capabilities, with a focus onproviding actionable insights for workforce development and organizational planning thatcenters on human workThe study examined implications across industries, skills, businessfunctions, and ethicsThe research brief was compiled using publicly available information from Skills evolution Scale of impact Artificial intelligence (AI) represents a transformationcomparable to the Industrial Revolution, with the WorldEconomic Forum (2023) projecting that AI and informationprocessing will drive 86% of labor market transformation by2030Transamerica reported that in the United States, morethan 70% of private sector companies either currently use or McKinsey predicts a workforce skill evolution would impact59% of the workforce by 2030Of that, 29% would beupskilled in their current role, 19% would be upskilled andredeployed, but 11% would be unlikely to upskill and vulnerableto unemploymentAccording to WEF, by 2030, 39% ofworkers’ core skills will need updatingEmployee participation Business function applications Human resources departments stand poised to realizesubstantial operational transformations through AIintegration, with potential productivity enhancements of AI adoption varies across business functions, with 71%of organizations now using generative AI in at least onearea, up from 65% in early 2024IT and marketing/saleslead adoption, according to McKinsey (Singla et al, 2025)Key applications include customer service chatbots andpersonalization engines, finance and accounting toolsfor fraud detection and bookkeeping, and various HR Anticipated workforce disruptions By 2030, WEF predicts 170 million jobs will be createdand 92 million jobs will be displacedCurrently, humansperform 47% of work tasks independently, while technologyhandles 22%, and human-technology collaborationaccounts for 30%By 2030, these proportions areexpected to equalize across all three categories of human-only tasks, technology-only tasks, and human-technology Human resources specific impact The proportion of technology skills listed in HR jobpostings rose to 52% in March 2025, a 23% increasefrom the previous year (Popera, 2024)Administrativeand professional HR roles face significant transformationpotentialWhile these efficiencies are significant, 73% Job impact distribution Up to 30% of hours worked today could be automated by2030 (Ellingrud et al, 2023), and roughly half of existingwork tasks could be automated (Kinder et al, 2024)Globally, this forces at least 14% of the global workforce toswitch careers due to the impacts of AI (Illanes et al, 2018) AI IS ON THE RISE More than 70% of private companiesin the USuse or plan to use it tosupport their workforce Training and development prioritiesBusiness leaders’ expectation for on-the-job skill acquisition Implementation strategy has increased from 65% in 2018 to 94% in 2025 (WEF, 2025)The majority of USworkers face some degree of impact by AIMcKinsey reports that although 48% of employees prioritizeAI training, nearly half report receiving inadequate supportAs technology outpaces policy development, leaders mustimplement transparent, human-centered design approaches As technology races ahead of policy development, successrequires transparent communication, phased trainingprograms, and inclusive implementation strategies that Organizational change requirements Successful AI implementation requires tailored changemanagement that builds internal champions, establishes clearcommunication, and aligns metrics with organizational valuesHuman-centered AI deployment recognizes that technologyadoption is fundamentally a human and organizationalchallenge, not merely a technical oneOrganizations mustestablish robust risk protocols, including ethical reviews and Demographic considerations Interestingly, higher-educated workers are more exposed butalso better positioned to benefit from AI, while older workersface greater challenges in adaptation and reemployment(Richardson, 2025)Furthermore, women show higherexposure to AI impacts in most countries (ILO, 2023), whilemillennials (35–44) show highest AI expertise across