{"id":221413,"date":"2025-10-13T11:49:09","date_gmt":"2025-10-13T11:49:09","guid":{"rendered":"https:\/\/www.newsbeep.com\/us\/221413\/"},"modified":"2025-10-13T11:49:09","modified_gmt":"2025-10-13T11:49:09","slug":"report-finds-genai-could-highly-transform-a-quarter-of-u-s-jobs","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/us\/221413\/","title":{"rendered":"Report finds GenAI could “highly transform” a quarter of U.S. jobs"},"content":{"rendered":"

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A new report<\/a> from Indeed finds that a quarter of U.S. jobs could be \u201chighly\u201d transformed by generative artificial intelligence (GenAI), but only 1% of skills can be independently executed by GenAI.\u00a0<\/p>\n

The \u201cAI at Work\u201d report, published by Indeed Hiring Lab<\/a>, concludes that the majority of the 53.5 million job postings analyzed are poised to be \u201cmoderately transformed\u201d by GenAI. That means these jobs are unlikely to change drastically overnight, but will likely evolve meaningfully as the adoption of GenAI rises. The successful transformation of these jobs will depend on how employers adopt GenAI models and how employees adapt to new skills.\u00a0<\/p>\n

\u201cWhat we are witnessing now is not a temporary phase; it\u2019s the structural shift that underpins how GenAI is beginning to rewire the DNA of jobs,\u201d reads the report.<\/p>\n

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Indeed\u2019s GenAI Skill Transformation Index\u00a0<\/p>\n

The report\u2019s authors developed the GenAI Skill Transformation Index (GSTI) to measure GenAI\u2019s potential to change the way workers use their skills or perform their jobs.\u00a0The index is able to measure GenAI\u2019s likelihood to transform a skill by capturing the relationship between a skill\u2019s cognitive and physical demands.<\/p>\n

This approach can help workforce development leaders think about GenAI\u2019s impact on jobs and skills along a spectrum of transformation rather than taking a binary view. In other words, the GSTI provides insight on how specific jobs and skills within occupations could transform in the future \u2014 not just whether or not GenAI will fully replace an employee.<\/p>\n

To account for cognitive demands, the index measures problem-solving ability by looking at what the report describes as \u201cthe degree to which a skill requires cognitive reasoning, applied knowledge, and practical judgment, and how well GenAI can replicate it.\u201d The index also accounts for each skill\u2019s physical demands, measuring \u201cwhether a skill requires physical execution and thus lies outside the current scope of GenAI.\u201d<\/p>\n

Indeed economists applied the GSTI to 2,884 common job skills extracted from 53.5 million U.S. job postings listed on Indeed between May 2024 and April 2025. Their assessment surfaced four areas of potential GenAI-driven skill transformation, and each job skill was placed within one of these four transformation zones.\u00a0<\/p>\n

Minimal transformation (40%): Job skills where either necessary human physical requirements or GenAI\u2019s limited reasoning capabilities mean it\u2019s likely that these job skills will remain unchanged. Examples include patient care, employee relations, and network administration.\u00a0<\/p>\n

Assisted transformation (19%): Job skills where GenAI can offer generic support, but where humans need to intervene to practically apply the skill. Examples include teaching, writing, and interpreting law.<\/p>\n

Hybrid transformation (40%): Job skills where GenAI can perform most routine work, but human oversight is still essential to the job being done correctly. Examples include medical coding, proofreading copy, and travel planning.\u00a0\u00a0\u00a0<\/p>\n

Full transformation (Less than 1%): Job skills where GenAI could independently execute well-structured tasks. Examples include basic math, prompt engineering, and image classification.<\/p>\n

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\nScreenshots from Indeed\u2019s AI at Work report. Courtesy of Indeed<\/p>\n

This analysis reveals that many of the almost 2,900 common job skills are \u201cstill out of GenAI\u2019s reach,\u201d as 40% are poised for minimal transformation and less than 1% \u2014 19 skills \u2014 are expected to fully transform.<\/p>\n

However, in Indeed\u2019s initial 2024 analysis<\/a>, zero skills were categorized as \u201cfull transformation.\u201d The increase in the number of skills in this category highlights that GenAI models have become more sophisticated in a relatively short period of time, and that more skills will likely cross the threshold into deeper transformation categories (e.g., \u201cfull\u201d and \u201chybrid\u201d transformation) as GenAI continues to develop.<\/p>\n

Transformation varies across types of jobs<\/p>\n

The report also used GSTI to measure the share of transformed skills across occupations.\u00a0<\/p>\n

In a typical job posting, 46% of necessary skills listed fell into \u201chybrid\u201d and \u201cfull\u201d transformation zones. This means that \u201cunder optimal conditions, GenAI could potentially profoundly reshape almost half the skills needed by a typical worker.\u201d\u00a0<\/p>\n

The jobs most highly exposed to GenAI are those in software development, data and analytics, and accounting. On the other end of the continuum, nursing, child care, and construction occupations have the lowest share of skills that fall into the deep transformation categories. More specifically, 81% of skills in a typical software development job posting fell into the hybrid transformation category, while 68% of skills in a typical nursing position fell into minimal transformation.\u00a0<\/p>\n

\u201cBy analyzing the core skills within these occupations and their relative exposure to GenAI, we can gain insight into those skills and tasks expected to remain more person-forward vs. those which may be taken over by GenAI, and, ultimately, how jobs may change going forward,\u201d reads the report.\u00a0<\/p>\n

Businesses, schools, and universities are in different stages of integrating GenAI into their workflows, lessons, and courses, and their decisions have the ability to shape what future jobs might look like.\u00a0<\/p>\n

The graph below shows how many job postings are highly exposed to GenAI transformation, revealing a \u201cmiddle majority\u201d \u2014 54% of job postings fall into the moderate transformation category.<\/p>\n

\"\"<\/a>Screenshot from Indeed\u2019s AI at Work report. Courtesy of Indeed<\/p>\n

This \u201cmiddle majority\u2019s\u201d importance, according to the report, is the fact that it is comprised of mainstream jobs that make up a large portion of the labor force.\u00a0\u00a0<\/p>\n

\u201cUnlike high- or low-exposure roles, where the trajectory is relatively straightforward, moderate-exposure jobs are more sensitive to decisions made by employers, policymakers, and technology providers,\u201d the report reads. \u201cWhether these roles shift toward greater automation or remain primarily human-led will depend on how organizations adopt GenAI tools, how quickly workers are reskilled, and how job design evolves.\u201d\u00a0<\/p>\n

State and federal shifts<\/p>\n

In North Carolina, the 2024 NC Chamber Education and Workforce conference, an annual convening of the state\u2019s key stakeholders in education, business, government, and nonprofit sectors, focused on the future of work<\/a> relative to AI\u2019s impact on the workforce. This year\u2019s conference encouraged collaboration<\/a> between education and business leaders as they navigate AI-induced transformations.\u00a0<\/p>\n

Efforts to prepare North Carolina\u2019s workforce for the future of AI have already begun. Many of the state\u2019s 58 community colleges, for example, have added AI-related courses and degrees<\/a> to their offerings in response to technology changes.\u00a0<\/p>\n

Multiple federal efforts are also underway to embed AI\u00a0as a core objective of workforce education and programming.<\/p>\n

Weeks after taking office, President Donald Trump called<\/a> for the creation of America\u2019s AI Action Plan<\/a>. Released in July 2025, the action plan<\/a> outlines policies around three pillars that will \u201csustain and enhance America\u2019s global AI dominance in order to promote human flourishing, economic competitiveness, and national security.\u201d Under the second pillar, \u201cBuild American AI Infrastructure,\u201d the action plan details recommended policy actions to train the skilled workforce needed to build, operate, and maintain AI infrastructure.<\/p>\n

Also in April 2025, Trump signed an executive order titled \u201cAdvancing Artificial Intelligence Education for American Youth<\/a>.\u201d Its purpose is to promote AI literacy and proficiency by promoting its integration into education, providing comprehensive AI training for teachers, and encouraging the future workforce\u2019s early exposure to AI concepts and technology. The executive order directs the secretary of labor to increase participation in AI-related registered apprenticeships and encourage states to use Workforce Innovation and Opportunity Act<\/a>\u00a0(WIOA) funding to develop AI skills and support work-based learning opportunities within occupations that use AI. The U.S. Department of Labor issued<\/a> that guidance<\/a> in August 2025.<\/p>\n

The same executive order also directed U.S. Department of Education Secretary Linda McMahon to issue guidance on the use of federal grant funds to improve education outcomes using AI. The department published its guidance in July 2025<\/a>, and it included McMahon\u2019s announcement that advancing AI in education would be her fourth grantmaking priority.<\/p>\n

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