In the fiscal year of 2021, 7,622 children adopted with public agency involvement in the United States were two years old at the time of adoption. In that same fiscal year, about 6,015 children adopted in the country were one year old at the time of their adoption.

In the fiscal year of 2022, about 51.81 percent of children adopted from abroad in the United States were female. In that fiscal year, there were 1,517 intercountry adoptions completed in the United States.

The adoption and child welfare industry has experienced overall growth even during the pandemic years, as increased stress-related service needs boosted demand and federal funding boosted revenues. While some service providers relied on private donations, corporate profit was strong in 2021. Technology adoption enabled remote delivery of services and expanded market reach, which helped reduce costs and enhance efficiency. Online matching platforms, VR training systems and case management software are examples of how technology has reduced costs and differentiated services to incentivize niche entry into underserved markets. And because of the strong growth in the number of establishments meeting demand and ample funding support during the pandemic, industry-wide revenue is expected to climb at a CAGR of 4.3% to $30.5 billion through 2025, with revenue growth inching up an estimated 1.7% in 2025 alone. The diversity of services offered and the unique characteristics of funding lead to disparate growth in services. Revenue for many establishments depends on the combination of government funding and private donations, which change with economic and government policy fluctuations, while demographic and social stressors impact the need for services. The disconnect between payors and clients creates an imbalance of funding and demand, adding to revenue volatility. Regional factors impact the provision of services and shortfalls. While demand in some states is growing because of increasing population, the long lead time to entry has led to a shortfall in provision.

Reorganizing key agencies under the new Administration for a Healthy America will bring some volatility to the industry. Government funding, crucial to more than half of industry revenue, faces volatility as restructuring could disrupt services, staffing and program effectiveness. This realignment offers potential efficiency gains through improved collaboration, but details about governance and resources remain in flux. Because of the uncertain impact of federal changes, private funding and state initiatives are vital for near-term future revenue growth. For-profit providers can leverage technology to reduce costs and capitalize on economies of scale, entering markets where nonprofits dominate. Telehealth innovations and online platforms lead to a broader reach and service efficiency, intensifying competition. As demand increases in rapidly growing states, nonprofit providers should streamline operations and secure diverse funding sources to meet community needs effectively. But despite numerous policy, technology and demographic shifts, industry revenue is forecast to climb at a slower CAGR of 1.2% through 2030 to total $32.5 billion with profit holding steady at a slim 3.1%.

Among recent major technologies in the United States, generative artificial intelligence (AI) had a much steeper leap in users in year two from year one than the other major technologies. Nearly ten times the amount of people had used generative AI within a year of its making, compared to three times the amount of tablet users and barely twice the amount of smartphone users. This leap has not remained steady, however, and tablets had more users in year four since its release than is expected of generative AI.

U.S. citizens are skeptical

Adults in the United States were somewhat concerned with the development and growth of generative AI in 2023. While most were somewhat concerned another third was mostly concerned, and relatively few individuals were excited. This is understandable with the rapid growth of new technology, as change and unknown factors always cause concern among the wider population.

Investment in tech going strong

In the U.S. investment in new technologies and generative AI were among the highest in enterprises. These topped investments in hiring, cost-cutting, and outsourcing. This high rate of investment in new technologies and AI is likely driven by the whole-of-enterprise effect that these trends might have on companies.

Comprehensive dataset of 44 Adoption agencies in Alabama, United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

During a 2022 survey conducted among professionals in the United States, it was found that 29 percent of respondents belonging to Gen Z used generative AI tools. Moreover, 28 percent of Gen X and 27 percent of millennials respondents used such tools, respectively.

Generative AI

Generative artificial intelligence (AI) refers to algorithms that focus on producing new content, such as text, images, music, speech, code, or video. Generative AI is part of deep learning, the machine learning branch which aims to reduce the manual work of programming parameters for AI. Currently, researchers and developers use generative AI in various industries, like advertising and marketing, but rumors suggest that more businesses and consumers will adopt this technology in the near future to perform a wide range of tasks.

ChatGPT

An example of generative AI is ChatGPT, the famous chatbot software launched in November 2022 by the American startup OpenAI, which is also well known for its art generative AI program Dall-E. The chatbot can produce text based on given inputs, recognize mistakes, challenge incorrect premises, and reject inappropriate requests. ChatGPT has quickly gained popularity, becoming one of the major breakthroughs of the last few decades in the technology industry. Indeed, it was the fastest IoT service to accumulate a one-million user base, in only five days.

Market Size statistics on the Adoption & Child Welfare Services industry in United States

The National Foster Care & Adoption Directory (formerly the National Adoption Directory) offers adoption and foster care resources by State.

Comprehensive dataset of 45 Adoption agencies in Wisconsin, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

This study contains two data files. Data file one (Broadband Internet Availability, Speed, and Adoption by Census Tract) contains measures of broadband internet availability, speed, and adoption per United States census tract in 2014 through 2020. The data is derived from internet service providers' Form 477 reports to the Federal Communications Commission. Data file two (Broadband Internet Availability and Speed by ZIP Code Tabulation Area) contains measures of broadband internet access and usage per United States ZIP code tabulation area (ZCTA) in 2014 through 2020. The data is derived primarily from internet service providers' Form 477 reports to the Federal Communications Commission.

This data product summarizes the extent of adoption of herbicide-tolerant (HT), insect-resistant (Bt), and those with both traits ("stacked") genetically engineered (GE) crops in the United States. Data cover GE varieties of corn, cotton, and soybeans over the 2000-2013 period, for the U.S.

The Adoption and Foster Care Analysis and Reporting System (AFCARS) is a federally mandated data collection system intended to provide case specific information on all children covered by the protections of Title IV-B/E of the Social Security Act (Section 427). Under the Final 1993 AFCARS’ rule, states are required to collect and submit data on all children who are under the responsiblity of the title IV-B/IV-E agency for placement, care, or supervision.

Units of Response: Children in Foster Care

Type of Data: Administrative

Tribal Data: Unavailable

Periodicity: Semiannual

Demographic Indicators: Disability;Geographic Areas;Sex

SORN: https://www.federalregister.gov/documents/2016/12/14/2016-29366/adoption-and-foster-care-analysis-and-reporting-system

Data Use Agreement: https://www.ndacan.acf.hhs.gov/datasets/order_forms/termsofuseagreement.pdf

Data Use Agreement Location: https://www.ndacan.acf.hhs.gov/datasets/order_forms/termsofuseagreement.pdf

Granularity: Individual

Spatial: United States

Geocoding: FIPS Code

In 1987, the National Health Interview Survey (NHIS) questionnaire included a special section that queried female respondents aged 20 through 54 about adoption. Their responses to the supplement are recorded in this dataset, along with other information about them derived from the core 1987 questionnaire. The special section on adoption asked if any children had ever been adopted, the number that were adopted, and whether these children currently lived in the household. Additional questions in the supplement inquired about the two most recent adoptions: how the adoptions were arranged, the adoptive mother's relationship to the adopted children before adoption, when and how old the adopted children were when they began living with the adoptive mother, the date of birth of the adopted children, and whether the adopted children were born in the United States. Variables from the core questionnaire include height, weight, age, race, Hispanic origin, type of living quarters, region and metropolitan status of residence, marital status, veteran status, education, family income, health status, industry, occupation, activity limitation status, medical conditions, restricted activity days in the past two weeks, bed days in the past two weeks and past 12 months, time interval since the last doctor visit, and the number of doctor visits and short-stay hospital episodes in the past two months. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR09342.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

This dataset is imported from the US Department of Commerce, National Telecommunications and Information Administration (NTIA) and its "Data Explorer" site. The underlying data comes from the US Census

1. dataset: Specifies the month and year of the survey as a string, in "Mon YYYY" format. The CPS is a monthly survey, and NTIA periodically sponsors Supplements to that survey.

2. variable: Contains the standardized name of the variable being measured. NTIA identified the availability of similar data across Supplements, and assigned variable names to ease time-series comparisons.

3. description: Provides a concise description of the variable.

4. universe: Specifies the variable representing the universe of persons or households included in the variable's statistics. The specified variable is always included in the file. The only variables lacking universes are isPerson and isHouseholder, as they are themselves the broadest universes measured in the CPS.

5. A large number of *Prop, *PropSE, *Count, and *CountSE columns comprise the remainder of the columns. For each demographic being measured (see below), four statistics are produced, including the estimated proportion of the group for which the variable is true (*Prop), the standard error of that proportion (*PropSE), the estimated number of persons or households in that group for which the variable is true (*Count), and the standard error of that count (*CountSE).

DEMOGRAPHIC CATEGORIES

1. us: The usProp, usPropSE, usCount, and usCountSE columns contain statistics about all persons and households in the universe (which represents the population of the fifty states and the District and Columbia). For example, to see how the prevelance of Internet use by Americans has changed over time, look at the usProp column for each survey's internetUser variable.

2. age: The age category is divided into five ranges: ages 3-14, 15-24, 25-44, 45-64, and 65+. The CPS only includes data on Americans ages 3 and older. Also note that household reference persons must be at least 15 years old, so the age314* columns are blank for household-based variables. Those columns are also blank for person-based variables where the universe is "isAdult" (or a sub-universe of "isAdult"), as the CPS defines adults as persons ages 15 or older. Finally, note that some variables where children are technically in the univese will show zero values for the age314* columns. This occurs in cases where a variable simply cannot be true of a child (e.g. the workInternetUser variable, as the CPS presumes children under 15 are not eligible to work), but the topic of interest is relevant to children (e.g. locations of Internet use).

3. work: Employment status is divided into "Employed," "Unemployed," and "NILF" (Not in the Labor Force). These three categories reflect the official BLS definitions used in official labor force statistics. Note that employment status is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by work status, even if they are otherwise considered part of the universe for the variable of interest.

4. income: The income category represents annual family income, rather than just an individual person's income. It is divided into five ranges: below $25K, $25K-49,999, $50K-74,999, $75K-99,999, and $100K or more. Statistics by income group are only available in this file for Supplements beginning in 2010; prior to 2010, family income range is available in public use datasets, but is not directly comparable to newer datasets due to the 2010 introduction of the practice of allocating "don't know," "refused," and other responses that result in missing data. Prior to 2010, family income is unkown for approximately 20 percent of persons, while in 2010 the Census Bureau began imputing likely income ranges to replace missing data.

5. education: Educational attainment is divided into "No Diploma," "High School Grad,

According to a survey conducted in 2021, 46 percent of White Americans had a favorable opinion of private infant adoption in the United States. In comparison, 44 percent of Hispanic Americans and 32 percent of Black Americans shared this belief.

Users can get information related to child welfare in the United States. Background The Child Welfare Information Gateway is part of the Administration of Children and Families. It provides resources and statistics related to child welfare, child abuse, child neglect, adoption and more. Resources are grouped under the following topics: family-centered practice; child abuse and neglect; preventing child abuse and neglect; responding to child abuse and neglect; supporting and preserving families; out-of-home care; achieving and maintaining permanency; and adoption. User Functionality The Child Welfare Information Gateway provides a number of resources for users. Users can search for foster care and adoption agencies by state using the National Foster Care and Adoption Directory; search for relevant publications using the Online Catalog and Library Search tools; search for State Statutes; and link to external databases related to child and family well-being, child abuse and neglect, child welfare and foster care, or adoption. Data Notes Years and data sources are clearly identified for each resource.

States report information from two reporting populations: (1) The Served Population which is information on all youth receiving at least one independent living services paid or provided by the Chafee Program agency, and (2) Youth completing the NYTD Survey. States survey youth regarding six outcomes: financial self-sufficiency, experience with homelessness, educational attainment, positive connections with adults, high-risk behaviors, and access to health insurance. States collect outcomes information by conducting a survey of youth in foster care on or around their 17th birthday, also referred to as the baseline population. States will track these youth as they age and conduct a new outcome survey on or around the youth's 19th birthday; and again on or around the youth's 21st birthday, also referred to as the follow-up population. States will collect outcomes information on these older youth at ages 19 or 21 regardless of their foster care status or whether they are still receiving independent living services from the State. Depending on the size of the State's foster care youth population, some States may conduct a random sample of the baseline population of the 17-year-olds that participate in the outcomes survey so that they can follow a smaller group of youth as they age. All States will collect and report outcome information on a new baseline population cohort every three years.

Units of Response: Current and former youth in foster care

Type of Data: Administrative

Tribal Data: No

Periodicity: Annual

Demographic Indicators: Ethnicity;Race;Sex

SORN: Not Applicable

Data Use Agreement: https://www.ndacan.acf.hhs.gov/datasets/request-dataset.cfm

Data Use Agreement Location: https://www.ndacan.acf.hhs.gov/datasets/order_forms/termsofuseagreement.pdf

Granularity: Individual

Spatial: United States

Geocoding: FIPS Code

Key indicators of broadband adoption, service and infrastructure in New York City by State Senate District Data Limitations: Data accuracy is limited as of the date of publication and by the methodology and accuracy of the original sources. The City shall not be liable for any costs related to, or in reliance of, the data contained in these datasets.

As of March 2024, a significant share of connected TV (CTV) users in the United States are expected to adopt new streaming services, regardless of their political affiliation. More than one third of Democrats plan to add a subscription streaming service in the next 12 months. Furthermore, 28 percent of overall users are looking to adopt free ad-supported streaming services, suggesting an increased interest in streaming services with ads.

Between 2020 and 2023, a country ranking that estimates crypto adoption based on transaction volume consistently placed the U.S. in the top 10 of the world. The figure for 2022, especially, stands out as it broke a declining trend in 2021 and was likely caused by the change of the methodology to now include Decentralized Finance (DeFi) in the index. For example, the United States ranked second in the world when it comes to on-chain retail value received from DeFi protocols - or consumers who were buying certain DeFi protocols. This may refer to the growing use of OpenSea and other Web3 wallets within the U.S. particularly in the first months of 2022.