As of April 2024, search engines powered by artificial intelligence (AI) results were the preferred search tools among the majority of teens in the United States, with 20 percent of them using them every day. Around 27 percent of U.S. teens reported using chatbots for online search daily, while around 20 percent of survey respondents stated that they use AI tools for image generation each day. Overall, seven percent reported using image generators multiple times in a week, while five percent used video generators as often.

This statistic shows the result of a survey conducted in 2018 and 2020 on people's expectations of usage of artificial intelligence in their every-day lives. As of 2020, ** percent of the respondents expected to use AI daily and the minority, or **** percent of the respondents, expected to use it a few times a year.

The market for artificial intelligence (AI) in epidemiology is rapidly expanding, driven by the increasing availability of data, the development of more sophisticated AI algorithms, and the growing need for more efficient and effective ways to track and respond to disease outbreaks. The global AI in epidemiology market is expected to reach $XXX million by 2033, growing at a CAGR of XX% from 2025 to 2033. Key drivers of this growth include the increasing prevalence of chronic diseases, the rising cost of healthcare, and the growing need for personalized medicine. AI can be used to improve the accuracy and efficiency of disease diagnosis, predict the spread of epidemics, and develop more effective treatments. As a result, AI is expected to play an increasingly important role in the field of epidemiology in the coming years. Artificial intelligence (AI) is rapidly transforming the field of epidemiology, enabling researchers to gather, analyze, and interpret vast amounts of data to improve public health outcomes. This report provides a comprehensive overview of the AI in epidemiology industry, including market size, growth drivers, challenges, emerging trends, and key players.

The size of the Artificial Intelligence in Epidemiology market was valued at USD XXX million in 2024 and is projected to reach USD XXX million by 2033, with an expected CAGR of XX% during the forecast period.

The AI in Epidemiology Market Report is Segmented by Deployment (Cloud-Based and Web-Based/On-Prem), Application (Infection Prediction & Forecasting, and More), End User (Pharmaceutical & Biotechnology Companies, and More), AI Technology (Machine-Learning Algorithms, and More), and Geography (North America, Europe, Asia-Pacific, Middle East & Africa, South America). The Market Forecasts are Provided in Terms of Value (USD).

BCC Research Market Report says AI in epidemiology market is projected to grow from $310.7 million in 2021 to over $1.3 billion in 2027, at a (CAGR) of 27.7%.

Dataset 1. List of 112 urology journals with information about their generative artificial intelligence guidance statements, including manuscript content generation, manuscript writing, and manuscript editing, and journal data, region, subspecialty, society affiliations, and impact factor.

In 2021, with ** percent, improving customer experience represents the top artificial intelligence and machine learning use cases. The deployment of machine learning and artificial intelligence can advance a variety of business processes.

Context

Analyses of text corpora over time can reveal trends in beliefs, interest, and sentiment about a topic. We focus on views expressed about artificial intelligence (AI) in the New York Times over a 30-year period. General interest, awareness, and discussion about AI has waxed and waned since the field was founded in 1956. We present a set of measures that captures levels of engagement, measures of pessimism and optimism, the prevalence of specific hopes and concerns, and topics that are linked to discussions about AI over decades. We find that discussion of AI has increased sharply since 2009, and that these discussions have been consistently more optimistic than pessimistic. However, when we examine specific concerns, we find that worries of loss of control of AI, ethical concerns for AI, and the negative impact of AI on work have grown in recent years. We also find that hopes for AI in healthcare and education have increased over time. This is joint work with E. Fast and E. Horvitz published at AAAI 2017.

Content

What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too.

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Artificial Intelligence in Precision Medicine Market Outlook

The Artificial Intelligence in Precision Medicine Market is projected to grow exponentially, achieving a valuation of USD XX billion by 2032, driven by the increasing demand for personalized healthcare solutions and technological advancements in AI. The market is poised for a significant CAGR of X% during the forecast period from 2024 to 2032.

One of the primary growth factors of the Artificial Intelligence (AI) in Precision Medicine Market is the increasing prevalence of chronic diseases such as cancer, diabetes, and cardiovascular disorders. These conditions require highly individualized treatment plans, which AI can help develop with a high degree of accuracy. AI's ability to analyze large datasets quickly and provide insights into patient-specific factors facilitates more effective and targeted treatments, thus driving the market's growth. Additionally, AI technologies enable the identification of novel biomarkers and therapeutic targets, further enhancing the precision of medical interventions.

Another significant driver is the advancement in AI technologies, particularly in machine learning, deep learning, and natural language processing. These technologies are revolutionizing the healthcare industry by providing tools that can predict disease progression, recommend personalized treatment options, and even discover new drugs. For example, AI algorithms can process vast amounts of genomic data to identify genetic mutations associated with specific diseases. This capability not only accelerates the drug discovery process but also improves the design of personalized treatment plans, thereby enhancing patient outcomes and reducing healthcare costs.

The growing investment in healthcare infrastructure and increasing adoption of electronic health records (EHRs) also contribute to the market's expansion. EHRs store extensive patient data, which AI systems can analyze to glean valuable insights into patient health trends and treatment responses. Governments and private enterprises are investing heavily in healthcare digitization, which is expected to provide a significant boost to the AI in Precision Medicine Market. Moreover, the COVID-19 pandemic has underscored the need for advanced healthcare solutions, further accelerating the adoption of AI in precision medicine.

Regionally, North America is expected to dominate the market due to its advanced healthcare infrastructure, significant healthcare expenditure, and strong presence of key market players. However, the Asia Pacific region is anticipated to witness the highest growth rate, driven by increasing healthcare investments, a growing patient population, and rising awareness of personalized medicine. Europe, Latin America, and the Middle East & Africa are also expected to contribute to the market's growth, albeit at varying rates depending on their respective healthcare landscapes and adoption of AI technologies.

Component Analysis

The AI in Precision Medicine Market by component is segmented into software, hardware, and services. The software segment is expected to hold the largest share due to the critical role AI algorithms and platforms play in analyzing complex healthcare data. Software solutions are essential for interpreting genomic data, predicting disease outcomes, and recommending personalized treatment plans. Companies are continually developing advanced AI software that can integrate seamlessly with existing healthcare systems, enhancing their utility and adoption.

The hardware segment, although smaller compared to software, is also crucial. This segment includes advanced computing systems, data storage solutions, and specialized devices required to run complex AI algorithms. With the increasing complexity of AI models and the growing volume of healthcare data, there is a rising demand for high-performance computing hardware. Innovations in chip technology and the development of AI-specific processors are expected to drive growth in this segment.

The services segment encompasses various support and consultancy services that facilitate the implementation and maintenance of AI systems in precision medicine. This includes services such as data management, system integration, training, and technical support. As healthcare providers and pharmaceutical companies adopt AI solutions, the need for expert services to ensure the smooth operation and optimization of these systems is growing. Service providers play a vital role in helping organizations navigate the complexities of AI techn

The rapid advancement and proliferation of generative artificial intelligence (AI) tools such as ChatGPT are reshaping the educational landscape, with students integrating these technologies into learning practices faster than curricula and institutional policies can adapt. This study presents the results of a large-scale national survey conducted in Estonia in 2024, involving 15,631 students from grades 6 to 12, to map the prevalence, purposes, and perceptions of AI use among school-aged learners. Estonia provides a unique context as one of the first countries in Europe to formally introduce AI literacy into its national curriculum. The study examined (1) the extent and purposes of AI tool usage, and (2) how students’ attitudes toward AI’s usefulness, risks, and ethical implications differ across educational levels. Results show that most students have already used at least one AI tool, primarily for completing school assignments such as homework and essay writing. While upper secondary students reported greater awareness of both benefits and risks and higher engagement with AI, lower secondary students showed less exposure and may need more structured support. The findings suggest a potential implementation gap: students’ practices are evolving ahead of pedagogical frameworks, which could be associated with uncritical use and challenges for metacognitive engagement. The study highlights the urgent need for pedagogically grounded, age-appropriate AI integration strategies and emphasizes the importance of future research to examine AI’s associations with learning outcomes, motivation, and critical thinking. These findings provide a foundational baseline for future policy and practice as AI education becomes institutionalized.

Artificial Intelligence in Healthcare Diagnosis Market Size, Trends, and Forecast The global artificial intelligence (AI) in healthcare diagnosis market size was valued at USD XXX million in 2025 and is projected to expand at a compound annual growth rate (CAGR) of 5% from 2025 to 2033. The increasing adoption of AI-powered diagnostic tools in healthcare facilities, rising prevalence of chronic diseases, and growing demand for personalized medicine are key factors driving market growth. Technological advancements, such as deep learning and natural language processing, have enabled AI algorithms to analyze vast amounts of medical data, including medical images, electronic health records, and genetic information, with high accuracy. This capability makes AI-powered diagnostic systems invaluable in detecting and diagnosing diseases earlier and more accurately than traditional methods. Additionally, AI algorithms can assist healthcare professionals in making informed treatment decisions, reducing healthcare costs, and improving patient outcomes. Artificial intelligence (AI) is rapidly transforming the healthcare industry, and its impact is particularly significant in the field of diagnosis. AI-powered tools are being used to analyze medical images, identify patterns, and predict outcomes, which is leading to more accurate and timely diagnoses. This is having a major impact on patient care, as it allows doctors to make better decisions and provide more personalized treatment plans. The AI in healthcare diagnosis market is expected to grow from USD 1.5 billion in 2023 to USD 9.4 billion by 2028, at a CAGR of 39.1% during the forecast period. The growth of this market is attributed to the increasing adoption of AI in healthcare, the rising prevalence of chronic diseases, and the growing need for accurate and timely diagnosis. The AI in healthcare diagnosis market is segmented into the following types:

Medical imaging tools, used to analyze medical images and identify patterns. Automated detection systems, used to detect and classify diseases based on medical images. Others, such as natural language processing tools and predictive analytics tools.

The AI in healthcare diagnosis market is also segmented into the following applications:

Hospitals and clinics Diagnostic laboratories Home care Others, such as research and development

The AI in healthcare diagnosis market is concentrated in North America, with the United States being the leading market. Europe is the second largest market, followed by Asia Pacific. The market is expected to grow rapidly in Asia Pacific, due to the increasing adoption of AI in healthcare and the rising prevalence of chronic diseases. Major players in the AI in healthcare diagnosis market include:

Koninklijke Philips N.V. (Netherlands) General Electric Company (United States) Aidoc (Israel) Arterys Inc. (United States) Icometrix (United States) IDx Technologies Inc. (United States) MaxQ AI Ltd. (United Kingdom) Caption Health, Inc. (United States) Zebra Medical Vision Inc. (Israel) Siemens Healthineers AG (Germany)

These companies are investing heavily in research and development, and they are launching new products and services to meet the growing demand for AI in healthcare diagnosis. The AI in healthcare diagnosis market is facing a number of challenges, including the lack of regulatory clarity, the need for large amounts of data, and the potential for bias in AI algorithms. However, the benefits of AI in healthcare diagnosis are significant, and the market is expected to continue to grow rapidly in the coming years.

Epidemiology Analytics AI Market Outlook

According to our latest research, the global Epidemiology Analytics AI market size reached USD 2.8 billion in 2024, reflecting the rapidly growing adoption of artificial intelligence in public health and epidemiological research. The market is anticipated to expand at a robust CAGR of 22.4% from 2025 to 2033, which will propel the market to an estimated USD 21.1 billion by 2033. This exponential growth is primarily driven by the urgent need for advanced data analytics to manage infectious diseases, optimize healthcare resources, and support real-time decision-making in public health. As per the latest research, the increasing prevalence of emerging diseases and the global shift toward digital healthcare infrastructure are acting as significant catalysts for the market’s expansion.

One of the primary growth factors for the Epidemiology Analytics AI market is the mounting pressure on global healthcare systems to respond swiftly to disease outbreaks and pandemics. The COVID-19 pandemic highlighted the critical need for real-time analytics and predictive modeling to track infection rates, allocate resources, and inform policy decisions. AI-powered epidemiology analytics solutions offer unparalleled capabilities in processing vast datasets, identifying patterns, and providing actionable insights for disease surveillance and outbreak prediction. This has led to widespread investments by governments, healthcare providers, and research institutions in AI-driven epidemiological tools, further fueling market growth.

Another significant driver is the rapid advancement of AI technologies, including machine learning, natural language processing, and advanced data visualization. These technologies enable more accurate risk assessment, early detection of disease clusters, and improved clinical research outcomes. The integration of AI with existing epidemiological databases and electronic health records (EHRs) has enhanced the ability to analyze patient-level data, track disease progression, and forecast healthcare demands. Additionally, the proliferation of wearable devices and IoT-enabled health monitoring systems has generated massive volumes of real-time data, which can be leveraged by AI analytics platforms to deliver more precise epidemiological insights.

The increasing adoption of cloud-based solutions and the expansion of digital health infrastructure across both developed and emerging markets are also propelling the growth of the Epidemiology Analytics AI market. Cloud deployment offers scalability, flexibility, and cost-effectiveness, enabling organizations to access powerful analytics tools without significant upfront investments in hardware. This democratization of access to advanced analytics is particularly beneficial for low- and middle-income countries, where resource constraints have traditionally limited the adoption of sophisticated epidemiological tools. The convergence of AI, big data, and cloud computing is thus creating new opportunities for innovation and market penetration.

Regionally, North America holds the largest share of the Epidemiology Analytics AI market, driven by substantial investments in healthcare IT, a strong presence of leading technology providers, and robust government initiatives in disease surveillance. Europe follows closely, benefiting from collaborative research projects and stringent regulatory frameworks that promote data interoperability and patient safety. The Asia Pacific region is expected to witness the fastest growth during the forecast period, fueled by rising healthcare expenditures, increasing digitalization, and a growing burden of infectious and chronic diseases. Meanwhile, Latin America and the Middle East & Africa are gradually embracing AI analytics, primarily through pilot projects and international collaborations, setting the stage for future market expansion.

Component Analysis

The Epidemiology Analytics AI market by component is segmented into software, hardware, and services, each playing a pivotal role in the overall ecosystem. Software solutions dominate the market, accounting for the largest revenue share in 2024. These include AI-powered analytics platforms, data visualization tools, and predictive modeling applications that enable real-time disease surveillance and outbreak forecasting. The continuous evolution of software capabilities, such as integration with electronic health records (EHRs) and intero

Artificial Intelligence In Epidemiology Market Size was valued at USD 0.70 Billion in 2024 and is expected to reach USD 4.27 Billion by 2032, growing at a CAGR of 27.3% from 2026 to 2032.Global Artificial Intelligence In Epidemiology Market DriversThe market drivers for the artificial intelligence in epidemiology market can be influenced by various factors. These may include:Demand for Real-Time Disease Surveillance: The use of AI tools for continuous monitoring and early outbreak detection is anticipated to be driven by the need for timely public health responses.Volume of Health Data Generation: Massive amounts of epidemiological and patient-level data being produced by hospitals, labs, and digital health platforms are expected to require AI-based tools for processing and analysis.

Artificial Intelligence Microscopy Market Outlook

The global artificial intelligence microscopy market size was valued at $870 million in 2023 and is projected to reach $2.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 13.8% during the forecast period. The primary growth factors for this market include advancements in AI technologies, an increasing focus on precision medicine, and the rising prevalence of chronic diseases that necessitate better diagnostic tools.

One significant growth factor for the artificial intelligence microscopy market is the rapid advancements in AI technologies, particularly in machine learning and deep learning. These technologies enable more precise and accurate image analysis, which is crucial for diagnosing complex medical conditions. The integration of AI in microscopy enhances the ability to identify and quantify cellular structures, leading to more accurate diagnoses and better patient outcomes. Moreover, AI-powered microscopes can process vast amounts of data quickly, making them invaluable in research environments where time and accuracy are critical.

Another key driver is the increasing focus on precision medicine. As healthcare moves towards more personalized treatment plans, the need for tools that can provide detailed, accurate analyses of biological samples becomes paramount. AI microscopy offers the capability to analyze samples at a microscopic level with high precision, aiding in the development of targeted therapies. This is particularly important in fields like oncology, where understanding the minute details of tumor cells can lead to more effective treatments. The ability of AI to provide insights that were previously unattainable through traditional methods is a significant boon for precision medicine.

The rising prevalence of chronic diseases such as cancer, diabetes, and cardiovascular diseases is also propelling the market forward. These conditions often require meticulous diagnostic procedures, and AI-enhanced microscopy provides the necessary accuracy and speed. For instance, in cancer diagnostics, AI can help pathologists detect malignant cells more accurately and quickly, leading to faster and more effective treatment decisions. The growing demand for such advanced diagnostic tools in hospitals and diagnostic laboratories is expected to drive market growth significantly.

The role of Microscopy Analysis Software is becoming increasingly pivotal in the artificial intelligence microscopy market. These software solutions are designed to enhance the capabilities of microscopes by providing advanced image analysis tools that leverage AI technologies. They allow for the automation of complex image processing tasks, which significantly reduces the time and effort required by researchers and healthcare professionals. By integrating machine learning algorithms, these software solutions can identify patterns and anomalies in microscopic images that might be missed by the human eye. This capability is particularly beneficial in medical diagnostics, where early and accurate detection of diseases can greatly improve patient outcomes. As the demand for precision medicine grows, the need for sophisticated microscopy analysis software that can provide detailed insights into biological samples is expected to rise, driving further advancements in this field.

Regionally, North America is expected to hold the largest share of the artificial intelligence microscopy market, followed by Europe and Asia Pacific. The presence of leading biotechnology and pharmaceutical companies, coupled with substantial investments in healthcare infrastructure, makes North America a significant player in this market. Europe is also experiencing growth due to increased funding for research and development projects. Asia Pacific is anticipated to grow at the highest CAGR during the forecast period, driven by rising healthcare expenditures, increasing adoption of advanced technologies, and growing awareness about the benefits of AI in medical diagnostics.

Component Analysis

The artificial intelligence microscopy market by component is segmented into software, hardware, and services. Each component plays a crucial role in the functionality and efficiency of AI-enhanced microscopes. The software segment is expected to dominate the market, driven by advancements in AI algorithms and machine learning models. These software solutions are essential for analyzing and interpreting microscopic images with hig

Overview

New York, NY – April 10, 2025 – The Global AI in Epidemiology Market size is expected to be worth around USD 6,041.0 million by 2033 from USD 549.1 million in 2023, growing at a CAGR of 27.1% during the forecast period 2024 to 2033.

Artificial Intelligence (AI) is rapidly transforming the field of epidemiology by improving how diseases are tracked, predicted, and controlled. AI tools can analyze vast amounts of health data from multiple sources such as hospitals, public records, and even social media to identify patterns, detect outbreaks early, and support faster decision-making in public health responses.

By using machine learning algorithms, AI can model the spread of infectious diseases, forecast future outbreaks, and assist in real-time monitoring of disease transmission. This technology has proven especially valuable during global health crises like COVID-19, where AI helped track virus variants, predict case surges, and guide resource allocation.

AI also supports contact tracing, vaccine distribution planning, and the identification of vulnerable populations. It enables researchers and health authorities to make more accurate, data-driven decisions and respond more quickly to emerging health threats.

As healthcare systems seek to become more proactive and preventive, the integration of AI in epidemiology is expected to grow. This development not only strengthens disease surveillance but also enhances global health security. The future of epidemiology will likely rely heavily on AI to ensure faster, smarter, and more effective responses to both existing and emerging public health challenges.

Global AI in Epidemiology Market size is expected to be worth around USD 6,041.0 million by 2033 from USD 549.1 million in 2023

According to a survey from September 2024 that was conducted among people in Japan who had used generative artificial intelligence (AI) at work, **** percent of those respondents who worked in the mass media industry stated that they used generative AI at work on a daily basis. The share was almost equally high among people working at trading companies and those working in retail and finance.

The size of the AI In Epidemiology Market market was valued at USD 0.66 Million in 2023 and is projected to reach USD 3.52 Million by 2032, with an expected CAGR of 26.99% during the forecast period. Recent developments include: June 2024: EPAM Systems Inc., a digital transformation services and product engineering company, reported the acquisition of Odysseus Data Services Inc., which offers artificial intelligence and data analytics solutions used for drug safety and efficacy epidemiological research.April 2023: Cerner Enviza, an Oracle company, and John Snow Labs collaborated to develop a new methodology to enhance computerized queries, or phenotyping, of digital patient data and clinical notes to support pharmacoepidemiology.. Key drivers for this market are: Rising Technological Advancement in Epidemiology, Increasing Clinical Advantages Offered by AI in Epidemiology. Potential restraints include: Rising Technological Advancement in Epidemiology, Increasing Clinical Advantages Offered by AI in Epidemiology. Notable trends are: The Disease and Syndromic Surveillance Segment is Expected to Hold a Significant Market Share Over the Forecast Period.

The AI in Epidemiology market is booming, projected to reach $0.66 billion by 2025 with a 26.99% CAGR. Discover key drivers, trends, and restraints shaping this rapidly expanding sector, including infection prediction, disease surveillance, and key players like Clarivate and Cerner. Learn more about market segmentation and regional growth forecasts. Recent developments include: June 2024: EPAM Systems Inc., a digital transformation services and product engineering company, reported the acquisition of Odysseus Data Services Inc., which offers artificial intelligence and data analytics solutions used for drug safety and efficacy epidemiological research.April 2023: Cerner Enviza, an Oracle company, and John Snow Labs collaborated to develop a new methodology to enhance computerized queries, or phenotyping, of digital patient data and clinical notes to support pharmacoepidemiology.. Key drivers for this market are: Rising Technological Advancement in Epidemiology, Increasing Clinical Advantages Offered by AI in Epidemiology. Potential restraints include: Rising Technological Advancement in Epidemiology, Increasing Clinical Advantages Offered by AI in Epidemiology. Notable trends are: The Disease and Syndromic Surveillance Segment is Expected to Hold a Significant Market Share Over the Forecast Period.