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How are Americans using AI? Findings from a national survey.

The rapid emergence of AI increases the need to understand its social and economic adoption. A national survey shows extensive use both at home and at work, with greater adoption among people with higher education and concern about job
Graph illustrating AI adoption across personal and professional sectors.

La emergencia rápida de la tecnología de Inteligencia Artificial (IA) ha aumentado la necesidad de comprender mejor su adopción en diversas aplicaciones sociales y económicas. Esto incluye su uso en hogares, por parte de empleados en el lugar de trabajo y por parte de propietarios y trabajadores en pequeñas empresas. Para lograr una muestra creíble y representativa a nivel nacional, se agregaron preguntas sobre el uso de IA al encuesta AmeriSpeak Omnibus realizada por el Centro de Investigación de Opinión Nacional (NORC) en la Universidad de Chicago. El panel de la encuesta contiene información demográfica rica, lo que permite una mejor comprensión del uso de IA en categorías de edad, ingreso y raza, además de ocupación y tamaño del empleador.

Los resultados de la encuesta sugieren un uso generalizado de IA generativa, con un 57% de los encuestados que utilizan IA para fines personales y un 40% que informan un aumento en su uso de la tecnología en el último año. Se asociaron niveles más altos de educación con un uso aumentado de IA. Alrededor de uno de cada cinco encuestados utiliza IA en sus vidas profesionales, aunque la proporción es abruptamente aumentada por educación e ingreso. Los trabajadores también son algo pesimistas sobre IA y desplazamiento laboral, con más creyendo que IA reducirá el número de empleos que creyendo que aumentará las oportunidades. Los patrones de uso por tamaño de la empresa son sorprendentemente similares, ya que el uso en pequeñas empresas es virtualmente idéntico al de las grandes.

Conclusiones principales

Los resultados de la encuesta se prestan a tres conclusiones principales: Una, el uso de IA es sorprendentemente consistente en tamaño de la empresa. Dos, si bien el uso personal es común, el uso profesional de IA es lejos de ser universal y muchos encuestados expresaron escepticismo de que sería tan revolucionario como algunos expertos esperan. Y tres, hay diferencias importantes en el uso de IA por demografías, incluyendo un uso aumentado entre aquellos con educación más alta y un uso más bajo para encuestados de edad de jubilación.

Las encuestas anteriores sobre el uso de IA han examinado tendencias a nivel personal y de hogares, así como en diversas industrias estadounidenses. Los sectores más frecuentemente examinados incluyen atención médica, finanzas y gobierno. Colectivamente, estos estudios sugieren que la tasa y la naturaleza de la adopción de IA varían grandemente entre sectores, así como entre empresas dentro de sectores.

Uso de IA en el nivel individual

Las encuestas han encontrado que una parte significativa de la población utiliza herramientas de IA. Por ejemplo, una encuesta de YouGov de 2025 encontró que el 56% de adultos estadounidenses utilizaba herramientas de IA, y el 28% las utilizaba al menos una vez a la semana. Estas tasas fueron aún más altas entre adultos menores de 30 años, para quienes la tasa de uso general fue del 76% y el uso semanal fue del 50%. Una encuesta realizada por el Centro de Investigación Pew encontró que el 57% de los adultos estadounidenses encuestados dijo que interactuaba con IA al menos varias veces a la semana, aunque solo el 33% dijo que había utilizado alguna vez un chatbot de IA. Un estudio realizado por Gallup y Telescope reveló que aproximadamente el 99% de los estadounidenses utilizaba al menos un producto con características de IA a la semana, pero solo el 36% de los encuestados se daba cuenta de que estos productos utilizaban IA.

Adopción de IA en el sector empresarial

Los estudios han mostrado niveles variables de adopción de IA. McElheran et al. (2024) concluyeron que menos del 6% de las 850,000 empresas incluidas en la Encuesta Anual de Negocios de 2018 utilizaban tecnologías relacionadas con IA, con la mayor adopción en los sectores de manufactura e información. Bonney et al. (2024) encontraron que el uso de IA era más alto en la clase más grande de empresas, con una tasa de adopción ponderada por empleo del 20% en un período específico. Roberts y Candi (2024) encontraron que herramientas de IA como ChatGPT se estaban aplicando a más de la mitad de los proyectos de innovación de los gerentes de innovación encuestados en empresas estadounidenses. Sin embargo, se encontró una correlación negativa entre el uso de IA y la edad de la empresa. Baily et al. (2025) abordó la gran dispersión en las tasas de adopción reportadas al comparar las tasas de adopción reportadas por la Oficina del Censo y un informe de McKinsey & Company, atribuyendo la discrepancia al tamaño de las empresas encuestadas.

Uso de IA en pequeñas y medianas empresas

Las pequeñas y medianas empresas también han comenzado a utilizar herramientas de IA a altas tasas. Un informe de 2025 de la Cámara de Comercio de los Estados Unidos encontró que el 58% de las pequeñas empresas encuestadas dijeron que utilizaban IA generativa, aumentando desde el 40% en el año anterior. Las pequeñas empresas con las tasas de uso más altas fueron en los sectores de tecnología y servicios financieros. Otra encuesta reciente realizada por la Iniciativa para una Ciudadanía Competitiva Interna (ICIC) encontró que el 89% de los dueños de pequeñas empresas informaron que al menos un empleado utilizaba herramientas de IA. El tipo de empleado más común reportado como utilizando IA fue el de gerencia de alto nivel, y el uso más común fue el análisis de datos.

Adopción de IA en la atención médica

Los estudios han mostrado niveles variables de adopción de IA en la atención médica. Baten (2024) concluyó que el 18,7% de los hospitales había adoptado herramientas de IA en 2022, principalmente para predecir la demanda de atención y automatizar la programación y el flujo de trabajo. Zink et al. (2024) encontraron que el volumen de facturación de Medicare para un software de diagnóstico de enfermedad cardíaca habilitado por IA creció más de 11 veces entre 2018 y 2022. Nong et al. (2025) encontraron que, en 2023, el 65% de los hospitales estadounidenses utilizaba modelos predictivos, aunque menos de la mitad los evaluó por sesgo y solo el 61% los evaluó por precisión.

Surveys have also revealed high levels of AI adoption in finance. A late 2024 survey from the accounting firm KPMG found that 71% of 2,900 companies around the world applied AI to corporate finance tasks to some degree, and 41% did so to a moderate or large degree. Of 300 U.S. companies included in the survey, 88% were using AI for corporate finance and 62% to a moderate degree or more. A 2025 Deloitte Center for Controllership poll found that over 80% of finance and accounting workers polled believed that AI tools would become standard for the profession within five years. However, only 13.5% of the firms currently employing polled professionals were already using “agentic AI,” which refers to AI capable of making independent decisions to solve assigned tasks.

Government use of AI is also growing. A survey of the employees of unemployment insurance agencies found that 42.5% of unemployment agencies in the U.S. use AI to prevent fraud. A survey report by Ernst & Young LLP found that about half of public sector employees across all levels of government used AI applications at least several times a week.

The survey data analyzed in this report were obtained by commissioning questions in the AmeriSpeak Omnibus survey instrument, which was fielded in the last week of June 2025. The Omnibus is a biweekly, multi-client survey of over 1,000 adults, mainly conducted online and to a lesser extent over the phone. Omnibus participants are selected from the AmeriSpeak Panel using 48 sampling strata, including age, race, and education, and accounting for differences in population size and expected survey completion rates across strata, to form a representative sample of U.S. adults 18 years old and over.

Among the full sample of 1,163 respondents, 57% report using generative AI for at least one personal purpose, most of whom use it for internet searches or web browsing. The use of AI in a personal capacity is highest for more educated respondents. Sixty-seven percent of those with a bachelor’s degree or higher use these tools in a personal capacity; 60% of those with some college or an associate’s degree use AI; and 46% of those with a high school diploma or equivalent use AI.

Frequency of personal AI engagement also scales with education. Fully 20% of bachelor’s degree or higher respondents and 21% of respondents with some college or an associate’s degree engage with AI “daily or more,” versus 8% of high-school graduates and 8% of respondents without a diploma. Age-related differences in daily use parallel this trend but are not significant except for the contrast between 30-44 (18%) and 60+ (13%). Around 40% of all respondents report that their use of AI has increased at least slightly compared to one year ago. In contrast, just 4% of respondents report a decrease in AI use.

Notably, the 18-29 cohort is the age group with the highest proportion of respondents who say they use AI less frequently than they did a year ago, at 11%. This may be due to their higher AI use to begin with. Changes in AI use over the past year also differ between education levels. Over half of respondents with a bachelor’s degree or higher report some level of increased AI use in the past year. This is more than double the rate of increased use for respondents with no high school diploma and for those in the high school graduate or equivalent group.

Roughly one-in-five respondents report using generative AI in their professional role. This adoption rate follows a clear education gradient: 33% of those with a bachelor’s degree or higher currently use these tools compared to 20% of respondents with some college or an associate’s degree, 12% of high-school graduates, and only 5% of individuals without a high-school diploma. Age also matters: Usage peaks among 30-44 year-olds and remains high for those aged 45-59 and 18-29 but then plummets to 8% for adults aged 60 and above. AI use also varies across income levels, rising from 9% usage among earners below $30,000 to 34% among those making $100,000 or more. Men’s overall professional use slightly exceeds women’s. When it comes to institutional AI support on the job, usage is highest for document writing and editing and again follows the education gradient. Among bachelor’s degree or higher employees, 35% use AI for documents versus 16% of those with some college or an associate’s degree, 10% of high-school graduates, and only 2% of workers without a diploma. Men lead women in nearly every workplace-AI category except hiring and recruiting. Higher earners also report greater on-the-job AI adoption: 35% of respondents earning $100,000+ use AI for documents compared to 8% of those earning under $30,000.

The Impact of AI on Worker Productivity

Although a sizable minority of respondents say that over the last six months AI use in their workplace has increased, even more say that they are not sure or that the question is not applicable. Here, education drives the largest differences: 40% of bachelor’s degree or higher respondents report increased use in the workplace compared with just 19% of those with some college or an associate’s degree, 9% of high-school graduates, and 5% of respondents without a diploma. Age contrasts are more modest, though the youngest cohort (18-29) experienced an increase in AI use in the workplace more frequently than the oldest (60+). The impact of generative AI on worker productivity is often unclear, even to the workers themselves. Only 19% of all respondents report that AI increased their productivity in their daily tasks, and only 4% say it increased their productivity significantly. Even among respondents with a bachelor’s degree or more, just 28% say that AI increased their productivity in daily tasks. More than one in five respondents report that their daily productivity remained the same and over half of all respondents say they are either not sure about the effect of AI on their productivity or say it does not apply to them.

AI Use in the Healthcare Industry

Within the subset of health care professionals, 53% of respondents report AI use. The application of AI cited by the greatest percentage of respondents is “patient communication tools.” AI use is heavily skewed towards male health care professionals. Furthermore, high-income practitioners report AI use in their work at a rate of 77%, whereas lower-income staff report just 51% usage. The education level with the highest reported rate of AI use is the group with some college or an associate’s degree at 65%. This surpasses the use among bachelor’s degree or higher respondents, which is only 60%.

AI Use in the Finance Industry

Of the fewer than 50 respondents that work in the finance, insurance, or real estate industries, 62% said they use AI in their work. The most common use of AI by financial professionals is for customer service. The 18-29 and 30-44 age groups have use rates of 77% and 89%, respectively, which are much higher than the 48% use amongst the 45-59 cohort and the 59% use amongst respondents aged 60+. As in the health care field, male financial professionals in our sample use AI much more frequently than their female counterparts, with 79% of men in finance reporting AI use compared to only 39% of women. However, in contrast with health care, the income group that uses AI most heavily in our finance sample is the less than $30k of annual income bracket.

AI Use Across Firm Sizes

Comparing AI use of respondents by firm size reveals remarkably similar trends across small and large businesses. Approximately 29% of sampled small businesses respondents use generative AI professionally compared to 27% of respondents employed at larger firms. Furthermore, 59% of small business respondents report that their workplace’s use of AI has increased over the last six months, while 60% of larger business respondents said the same. These results could support the findings of earlier surveys which indicate that smaller firms have caught up to larger firms in AI adoption. The small business group contained a weighted base of 236 respondents, while the larger business group contained 627. Respondents who are not currently working are omitted from the comparison. Though use rates are similar across small and large firms, the data indicate that there is a gap between personal and professional AI use rates. Furthermore, respondents seem skeptical about the impact of AI; over two-thirds of respondents predict that AI will have no more than a slight impact on the number of jobs, and less than one in five respondents say that AI has improved their productivity even slightly.

Graph showing AI adoption rates by age, education, and firm