In 2025, it was the United States that led the world in research capacity on AI. And led with a lead of nearly ** points beyond its nearest competitor, China. Across the globe, no other nation comes close to the U.S. research capacity in AI.

Computer science still male-driven Research requires educated and skilled individuals to do it and in the modern world, computer science education is still male-dominated. Both in Europe and the United States, it is males that trend far more towards bachelor’s degrees in computer science. However, females had a higher trend toward masters in this field in Europe, whereas, in the United States, their share was similar to their share of bachelor's degrees. U.S. tech giants play a significant role One primary driver of the United States' significant lead over other nations is the fact that it houses the largest tech companies on earth. Counting giants such as Microsoft, Google, Apple, and Amazon, the country has ample funds in private hands to drive AI research even without the enormous budget of the U.S. government.

Combined, China had the highest rate of exploring and deploying artificial intelligence (AI) globally in 2022. It was followed closely by India and Singapore. This lead was also marked when accounting only for the deployment of AI in organizations in China, with India following. Both nations had a nearly ** percent deployment rate. When accounting only for exploration, however, the leading nations were Canada and the United States. AI in Europe on the rise Europe contains an exceptionally vibrant technology sector. This is particularly true in the field of AI, where funding for startups specializing in this high-demand technology stood at more than *** billion U.S. dollars in late 2022. Many of Europe’s major economies are leaders in the exploration and deployment of AI and are ahead of the global curve. Opportunities for early adopters Those businesses that begin using AI early will find it easier to reap the benefits. The most desirable effect, or at least the one that directly affects most businesses, is a revenue increase as it underpins the whole of their business model. The most important benefit of AI usage in enterprises is in supply chain management and human resources. Major improvements to supply chains provide a major boost to revenue by using AI to map out idiosyncrasies and problematic stops. When it comes to human resources, the use of AI can drastically reduce time in hiring cycles by enabling AI-driven algorithms to select those candidates whose resume most aligns with the job requirements.

We tracked the use of AI around elections in 14 countries.

AI-Powered Knowledge Graph Market Outlook

According to our latest research, the AI-Powered Knowledge Graph market size reached USD 3.1 billion in 2024 globally, registering a robust growth trajectory. The market is expected to maintain a strong momentum, growing at a CAGR of 23.5% from 2025 to 2033. By the end of the forecast period in 2033, the global market size is projected to reach approximately USD 24.3 billion. The surge in market demand is primarily attributed to the increasing adoption of AI-driven data management solutions across industries seeking to harness the power of semantic search, automated reasoning, and real-time analytics for business intelligence and decision-making.

A primary growth factor for the AI-Powered Knowledge Graph market is the exponential rise in data volume and complexity across all sectors. Organizations worldwide are confronted with unprecedented data silos, unstructured information, and the need for real-time insights. AI-powered knowledge graphs address these challenges by providing a semantic layer that enables intelligent data integration, context-aware search, and relationship mapping. This capability is particularly critical as enterprises strive to improve operational efficiencies, enhance customer experiences, and accelerate innovation cycles. The adoption of knowledge graphs is further propelled by advancements in natural language processing (NLP), machine learning, and automated reasoning, which collectively empower organizations to extract actionable intelligence from vast and disparate data sources.

Another significant driver for the AI-powered knowledge graph market is the growing demand for personalized digital experiences and intelligent recommendation engines. In sectors such as retail, e-commerce, and media, knowledge graphs are instrumental in delivering tailored product recommendations, content discovery, and contextual advertising. The ability to map user preferences, behaviors, and interactions within a knowledge graph framework enables hyper-personalization at scale, leading to improved customer engagement and loyalty. Simultaneously, the BFSI and healthcare industries are leveraging AI-powered knowledge graphs for fraud detection, risk management, and regulatory compliance, further expanding the market's application landscape. The convergence of AI, big data analytics, and graph technologies is thus fostering rapid market expansion and innovation.

The proliferation of cloud computing and the shift toward hybrid and multi-cloud architectures are catalyzing the deployment of AI-powered knowledge graphs. Cloud-based solutions offer scalability, flexibility, and cost-efficiency, making them attractive to both large enterprises and small and medium-sized businesses (SMEs). As organizations migrate their workloads to the cloud, they seek robust knowledge graph platforms that can seamlessly integrate with existing data lakes, data warehouses, and analytical tools. This trend is also supported by the growing ecosystem of cloud-native AI services, APIs, and pre-trained models, which simplify the development and deployment of knowledge graph applications. Consequently, cloud deployment is expected to capture a significant share of the market during the forecast period.

From a regional perspective, North America currently dominates the AI-powered knowledge graph market, accounting for over 38% of the global revenue in 2024. The region's leadership is driven by high digital adoption rates, strong investments in AI research and development, and the presence of leading technology vendors. Europe and Asia Pacific are also witnessing rapid growth, fueled by digital transformation initiatives, regulatory support for data-driven innovation, and the expansion of cloud infrastructure. In particular, Asia Pacific is expected to register the highest CAGR during the forecast period, as enterprises in countries such as China, India, and Japan accelerate their adoption of AI-powered knowledge graph solutions to stay competitive in the digital economy.

Component Analysis

The Component segment of the AI-powered knowledge graph market encompasses software, services, and hardware, each playing a pivotal role in the ecosystem. Software forms the backbone of knowledge graph solutions, providing the core functionalities for data ingestion, semantic modeling, relationship mappi

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In 2024, consumers based in Germany, Australia, United Kingdom, and the United States expressed their opinions on privacy risks posed by artificial intelligence. Only ** percent of them believed retailers could ensure data privacy when setting up AI-powered tools. Almost ** percent of surveyed shoppers thought retailers had to prioritize ethical use of AI.

Our most comprehensive database of AI models, containing over 800 models that are state of the art, highly cited, or otherwise historically notable. It tracks key factors driving machine learning progress and includes over 300 training compute estimates.

The graph presents the leading Latin American countries in share of paid TV streaming accounts in 2017. That year, Mexicans subscribers represented **** percent of all TV streaming accounts in Latin America, followed by Brazil with a market share of **** percent.

SafeGraph Places provides baseline information for every record in the SafeGraph product suite via the Places schema and polygon information when applicable via the Geometry schema. The current scope of a place is defined as any location humans can visit with the exception of single-family homes. This definition encompasses a diverse set of places ranging from restaurants, grocery stores, and malls; to parks, hospitals, museums, offices, and industrial parks. Premium sets of Places include apartment buildings, Parking Lots, and Point POIs (such as ATMs or transit stations).

SafeGraph Places is a point of interest (POI) data offering with varying location data coverage depending on the country. Note that address conventions and formatting vary across countries. SafeGraph has coalesced these fields into the Places schema.

SafeGraph provides clean and accurate geospatial datasets on 51M+ physical places/points of interest (POI) globally. Hundreds of industry leaders like Mapbox, Verizon, Clear Channel, and Esri already rely on SafeGraph POI data to unlock business insights and drive innovation.

This graph displays the total population size of citizens aged from between 60 and 64 years old in Europe in 2015, by country. That year there were roughly 5.38 million inhabitants of this age group in Germany, which was followed by France and Italy at 4.07 million and 3.78 million inhabitants respectively.

This graph displays the total population size of citizens aged from between 45 and 49 years old in Europe in 2018, by country. That year there were roughly 5.94 million inhabitants of this age group in Germany, which was followed by Italy and France with approximately 4.87 million and 4.55 million inhabitants respectively.

This graph shows the 15 countries in the world that have made the fastest progress in the time from 1990 to 2010 against child malnutrition and consequently child stunting. Measurements displayed are the annual average percentage change in child stunting rates. China has, on average, seen a 6.3 percent decrease in the rate of child stunting from 1990 to 2010.

This statistic shows the results of a global survey among 14,030 people regarding the source of their personal values and ethics in December 2009, by selected countries. Hover over the respective graph to see the exact figures. 30.32 percent of surveyed Americans state that they derive their personal values from their faith or religion.

Figure 1. Co-invention Network across Countries and Technological DomainsThis network visualisation depicts cross-border co-invention ties in Bosch’s AI-related patents filed between 2017 and 2023. Each node represents a country, coloured by dominant technological domain (e.g., propulsion, embedded systems). Directed edges indicate co-patenting flows from subsidiaries to the German headquarters (DE). Node size reflects centrality in the network, and edge thickness indicates the frequency of co-invention ties. The network highlights Germany’s role as the central hub integrating diverse regional contributions, especially in transversal technologies such as artificial intelligence and advanced manufacturing.Figure 2. Hierarchical Clustering of Inventor Home Countries Based on Co-invention PatternsThis dendrogram shows a hierarchical clustering of inventor home countries based on their involvement in Bosch’s AI-related co-invention activity from 2017 to 2023. The clustering uses Ward’s linkage and rescaled distance metrics to identify similarities in national co-patenting profiles. Each country represents the residence of inventors rather than patent ownership or filing location. The results indicate distinct groupings, with countries such as Germany, Austria, and France forming a tightly connected core, while others like Japan, Vietnam, and Israel appear more peripheral. The analysis captures how geographically distributed inventors are integrated into the firm’s internal innovation network.This dataset contains structured patent and inventor information used in the analysis of transnational co-invention and patent integration strategies within Robert Bosch GmbH’s innovation network. It includes 380 patents filed between 2017 and 2023 that are classified under artificial intelligence and related transversal technologies.Variables include:Patent ID (anonymised)Filing YearJurisdiction of Filing (e.g. EPO, WIPO)IPC Technological Classification (e.g. Artificial Intelligence, Embedded Systems)Inventor ID (anonymised)Inventor Country (home country based on affiliation at filing time)Number of Inventors per PatentCo-inventor Ties (binary format for network construction)Filing AuthorityAssignment Location (corporate entity receiving ownership)R Script for Estimating Exponential Random Graph Models (ERGM) in Co-Inventor NetworksDescription:This script contains the R code used to construct and analyse co-inventor networks based on patent data. It includes procedures for:Importing and formatting adjacency matrices and inventor attribute dataBuilding network objects using the network and igraph packagesAssigning node-level attributes such as inventor affiliation, technological classification, and team sizeEstimating Exponential Random Graph Models (ERGM) using the ergm packageTesting the significance of network structure, inventor-level effects, and filing-related covariatesRunning diagnostics to evaluate model fit and convergence

The graph presents a forecast of European countries ranked by eHealth market revenue in 2018. According to the estimates, eHealth revenue will be highest in Germany, with a market value of approximately 652 million U.S. dollars. An overview of all Digital Markets can be found here. Statista’s Digital Market Outlook offers forecasts, detailed market insights and essential performance indicators of the most significant areas in the “Digital Economy”, including various digital goods and services. Alongside revenue forecasts for 50 countries worldwide, Statista offers additional insights into consumer trends and demographic structure of digital consumer markets.

As of March 2025, there were a reported 5,426 data centers in the United States, the most of any country worldwide. A further 529 were located in Germany, while 523 were located in the United Kingdom. What is a data center? A data center is a network of computing and storage resources that enables the delivery of shared software applications and data. These facilities can house large amounts of critical and important data, and therefore are vital to the daily functions of companies and consumers alike. As a result, whether it is a cloud, colocation, or managed service, data center real estate will have increasing importance worldwide. Hyperscale data centers In the past, data centers were highly controlled physical infrastructures, but the cloud has since changed that model. A cloud data service is a remote version of a data center – located somewhere away from a company's physical premises. Cloud IT infrastructure spending has grown and is forecast to rise further in the coming years. The evolution of technology, along with the rapid growth in demand for data across the globe, is largely driven by the leading hyperscale data center providers.

The graph presents a forecast of selected European countries ranked by eHealth hypertension solutions penetration rate in 2016. According to the estimates, penetration of the eHealth hypertension segment will be highest in Denmark, with a rate of 0.9 percent. An overview of all Digital Markets can be found here. Statista’s Digital Market Outlook offers forecasts, detailed market insights and essential performance indicators of the most significant areas in the “Digital Economy”, including various digital goods and services. Alongside revenue forecasts for 50 countries worldwide, Statista offers additional insights into consumer trends and demographic structure of digital consumer markets.

The graph presents a forecast of European countries ranked by eHealth diabetes market revenue in 2016. According to the estimates, eHealth revenue of the diabetes segment will be highest in Germany, with a market value of 30.9 million U.S. dollars. An overview of all Digital Markets can be found here. Statista’s Digital Market Outlook offers forecasts, detailed market insights and essential performance indicators of the most significant areas in the “Digital Economy”, including various digital goods and services. Alongside revenue forecasts for 50 countries worldwide, Statista offers additional insights into consumer trends and demographic structure of digital consumer markets.

The graph presents a forecast of European countries ranked by eHealth solutions for heart failure revenue in 2016. According to the estimates, eHealth revenue of the heart failure segment will be highest in Germany, with a market value of 164 million U.S. dollars. An overview of all Digital Markets can be found here. Statista’s Digital Market Outlook offers forecasts, detailed market insights and essential performance indicators of the most significant areas in the “Digital Economy”, including various digital goods and services. Alongside revenue forecasts for 50 countries worldwide, Statista offers additional insights into consumer trends and demographic structure of digital consumer markets.

The global number of AI tools users in the 'AI Tool Users' segment of the artificial intelligence market was forecast to continuously increase between 2025 and 2031 by in total ***** million (+****** percent). After the tenth consecutive increasing year, the number of AI tools users is estimated to reach *** billion and therefore a new peak in 2031. Notably, the number of AI tools users of the 'AI Tool Users' segment of the artificial intelligence market was continuously increasing over the past years.Find more key insights for the number of AI tools users in countries and regions like the market size in the 'Generative AI' segment of the artificial intelligence market in Australia and the market size change in the 'Generative AI' segment of the artificial intelligence market in Europe.The Statista Market Insights cover a broad range of additional markets.