100+ datasets found
  1. Most used AI technologies among retail businesses in the United States 2024

    • statista.com
    • davegsmith.com
    Updated Jun 25, 2025
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    Statista (2025). Most used AI technologies among retail businesses in the United States 2024 [Dataset]. https://www.statista.com/statistics/1384355/most-used-ai-technologies-among-retail-businesses-united-states/
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    Dataset updated
    Jun 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Dec 2023 - Feb 2024
    Area covered
    United States
    Description

    In the United States, most retail companies are likely to use artificial intelligence (AI) for marketing purposes. Nearly ** percent of professionals from retail companies answering a survey in 2024 stated that their enterprises will be using AI to handle marketing automation. Chatbots and virtual shopping assistants follow in the ranking, with **** percent of answers.

  2. AI usage among employees in organizations globally in 2023

    • statista.com
    Updated Jun 30, 2025
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    Statista (2025). AI usage among employees in organizations globally in 2023 [Dataset]. https://www.statista.com/statistics/1449268/worldwide-ai-use-in-organizations-department/
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    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 2023
    Area covered
    Worldwide
    Description

    Most organizations have not adapted AI to a great degree, with only a select number of employees within an organization using it in 2023. This is in all likelihood because the technology is still maturing and a select amount of employees might be running pilot programs or test programs for AI usage within companies. What is notable is more than a ******* of companies did not use any AI within their enterprise in 2023.

  3. Share of companies using AI in CEE 2023, by country

    • statista.com
    Updated Oct 8, 2024
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    Statista (2024). Share of companies using AI in CEE 2023, by country [Dataset]. https://www.statista.com/statistics/1385443/cee-artificial-intelligence-use-in-enterprises-by-country/
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    Dataset updated
    Oct 8, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    CEE
    Description

    Slovenia had the largest share of enterprises using artificial intelligence (AI) technology among Central and Eastern European (CEE) countries, at over 11 percent in 2023. To compare, in Croatia, which ranked second, almost eight percent of businesses used any AI technology, while in Romania this figure stood at only 1.5 percent.

  4. Use of artificial intelligence (AI) by businesses or organizations in...

    • open.canada.ca
    • www150.statcan.gc.ca
    csv, html, xml
    Updated Aug 28, 2024
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    Statistics Canada (2024). Use of artificial intelligence (AI) by businesses or organizations in producing goods or delivering services over the next 12 months, third quarter of 2024 [Dataset]. https://open.canada.ca/data/dataset/5c92242b-8c75-4ff0-9e2f-fd97a2ce1248
    Explore at:
    xml, html, csvAvailable download formats
    Dataset updated
    Aug 28, 2024
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    Use of artificial intelligence (AI) by businesses or organizations in producing goods or delivering services over the next 12 months, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, third quarter of 2024.

  5. E

    AI In Healthcare Statistics 2023 By Market Share, Users and Companies

    • enterpriseappstoday.com
    Updated Nov 6, 2023
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    EnterpriseAppsToday (2023). AI In Healthcare Statistics 2023 By Market Share, Users and Companies [Dataset]. https://www.enterpriseappstoday.com/stats/ai-in-healthcare-statistics.html
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    Dataset updated
    Nov 6, 2023
    Dataset authored and provided by
    EnterpriseAppsToday
    License

    https://www.enterpriseappstoday.com/privacy-policyhttps://www.enterpriseappstoday.com/privacy-policy

    Time period covered
    2022 - 2032
    Area covered
    Global
    Description

    AI in Healthcare Statistics: AI in healthcare has been a hot topic for the past few years, and the report says that the industry is expected to reach $187.95 billion by the end of 2030. The fact of this platform in 2023 suggests a huge boom in the market size worldwide, with a compound annual increase rate (CAGR) of 40.1% from 2023 to 2030. The worldwide Artificial intelligence in the healthcare marketplace length changed into worth $20.65 billion in 2023 which has increased from last year. These AI in Healthcare Statistics include insights from various aspects and sources that will provide effective light on the importance of AI in the healthcare industry around the world in recent times. In 2023, the Market share records the gradual adoption of AI which is advancing the sector, and has been observed that 85% of organizations have already implemented AI. Additionally, 1/2 of the executives claimed that AI is indicating a tremendous shift inside and outside the industry. Aid of AI-based healthcare companies used solutions like telemedicine and remote tools and sensors backed by means of large information that can reduce healthcare charges improve access, and promote better outcomes, and performance. Key Takeaways According to AI in Healthcare Statistics, the platform when implemented Artificial Intelligence has experienced a huge increase, with a CAGR of 40.1% from 2023 to 2030 and a global market size expected to attain $187.95 billion by 2030. Around the world, approximately 40% of healthcare industries are regularly using AI and Machine Language in the sector. In 2023, Healthcare executives are increasingly adopting AI in their techniques, and nearly 1/2 of the executives surveyed are already using it. This is being adopted globally, with answers like telemedicine and faraway tools and sensors backed through huge information that could lessen healthcare charges and equitably improve admission to, results, and performance.

  6. Usage of artificial intelligence (AI) by construction companies in the U.S....

    • statista.com
    Updated May 28, 2025
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    Statista (2025). Usage of artificial intelligence (AI) by construction companies in the U.S. 2023-2025 [Dataset]. https://www.statista.com/statistics/1465973/usage-of-artificial-intelligence-in-construction-us/
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    Dataset updated
    May 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Nearly ***** percent of construction companies in the United States used artificial intelligence (AI) in the first half of 2025. Although those figures are still very low, the percentage of companies using AI has been increasing. In the first half of 2025, over *** percent of construction firms thought that they would use some type of AI technology in the next six months.

  7. Artificial Intelligence in Big Data Analysis Market Report | Global Forecast...

    • dataintelo.com
    csv, pdf, pptx
    Updated Sep 5, 2024
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    Dataintelo (2024). Artificial Intelligence in Big Data Analysis Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-artificial-intelligence-in-big-data-analysis-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Sep 5, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Artificial Intelligence in Big Data Analysis Market Outlook



    The global market size for artificial intelligence in big data analysis was valued at approximately $45 billion in 2023 and is projected to reach around $210 billion by 2032, growing at a remarkable CAGR of 18.7% during the forecast period. This phenomenal growth is driven by the increasing adoption of AI technologies across various sectors to analyze vast datasets, derive actionable insights, and make data-driven decisions.



    The first significant growth factor for this market is the exponential increase in data generation from various sources such as social media, IoT devices, and business transactions. Organizations are increasingly leveraging AI technologies to sift through these massive datasets, identify patterns, and make informed decisions. The integration of AI with big data analytics provides enhanced predictive capabilities, enabling businesses to foresee market trends and consumer behaviors, thereby gaining a competitive edge.



    Another critical factor contributing to the growth of AI in the big data analysis market is the rising demand for personalized customer experiences. Companies, especially in the retail and e-commerce sectors, are utilizing AI algorithms to analyze consumer data and deliver personalized recommendations, targeted advertising, and improved customer service. This not only enhances customer satisfaction but also boosts sales and customer retention rates.



    Additionally, advancements in AI technologies, such as machine learning, natural language processing, and computer vision, are further propelling market growth. These technologies enable more sophisticated data analysis, allowing organizations to automate complex processes, improve operational efficiency, and reduce costs. The combination of AI and big data analytics is proving to be a powerful tool for gaining deeper insights and driving innovation across various industries.



    From a regional perspective, North America holds a significant share of the AI in big data analysis market, owing to the presence of major technology companies and high adoption rates of advanced technologies. However, the Asia Pacific region is expected to exhibit the highest growth rate during the forecast period, driven by rapid digital transformation, increasing investments in AI and big data technologies, and the growing need for data-driven decision-making processes.



    Component Analysis



    The AI in big data analysis market is segmented by components into software, hardware, and services. The software segment encompasses AI platforms and analytics tools that facilitate data analysis and decision-making. The hardware segment includes the computational infrastructure required to process large volumes of data, such as servers, GPUs, and storage devices. The services segment involves consulting, integration, and support services that assist organizations in implementing and optimizing AI and big data solutions.



    The software segment is anticipated to hold the largest share of the market, driven by the continuous development of advanced AI algorithms and analytics tools. These solutions enable organizations to process and analyze large datasets efficiently, providing valuable insights that drive strategic decisions. The demand for AI-powered analytics software is particularly high in sectors such as finance, healthcare, and retail, where data plays a critical role in operations.



    On the hardware front, the increasing need for high-performance computing to handle complex data analysis tasks is boosting the demand for powerful servers and GPUs. Companies are investing in robust hardware infrastructure to support AI and big data applications, ensuring seamless data processing and analysis. The rise of edge computing is also contributing to the growth of the hardware segment, as organizations seek to process data closer to the source.



    The services segment is expected to grow at a significant rate, driven by the need for expertise in implementing and managing AI and big data solutions. Consulting services help organizations develop effective strategies for leveraging AI and big data, while integration services ensure seamless deployment of these technologies. Support services provide ongoing maintenance and optimization, ensuring that AI and big data solutions deliver maximum value.



    Overall, the combination of software, hardware, and services forms a comprehensive ecosystem that supports the deployment and utilization of AI in big data analys

  8. Use of artificial intelligence by businesses and organizations in producing...

    • www150.statcan.gc.ca
    • open.canada.ca
    Updated May 27, 2024
    + more versions
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    Government of Canada, Statistics Canada (2024). Use of artificial intelligence by businesses and organizations in producing goods or delivering services over the last 12 months, second quarter of 2024 [Dataset]. http://doi.org/10.25318/3310082501-eng
    Explore at:
    Dataset updated
    May 27, 2024
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Use of artificial intelligence (AI) by businesses and organizations in producing goods or delivering services over the last 12 months, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.

  9. s

    What Are The Challenges That Can Stop Companies From Investing In AI?

    • searchlogistics.com
    Updated Apr 1, 2025
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    (2025). What Are The Challenges That Can Stop Companies From Investing In AI? [Dataset]. https://www.searchlogistics.com/learn/statistics/artificial-intelligence-statistics/
    Explore at:
    Dataset updated
    Apr 1, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Here are the top 3 most significant challenges that companies worry about:.

  10. E

    AI In Business Statistics By Industry, Region And Facts (2025)

    • electroiq.com
    Updated Jun 27, 2025
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    Electro IQ (2025). AI In Business Statistics By Industry, Region And Facts (2025) [Dataset]. https://electroiq.com/stats/ai-in-business-statistics/
    Explore at:
    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Electro IQ
    License

    https://electroiq.com/privacy-policyhttps://electroiq.com/privacy-policy

    Time period covered
    2022 - 2032
    Area covered
    Global
    Description

    Introduction

    AI In Business Statistics: In today’s world, global businesses are rapidly transforming with Artificial Intelligence (AI), and as a result, overall operations are becoming easier in almost every industry. From automating regular tasks to enabling smarter decision-making, AI is also helping companies boost efficiency, increase productivity, reduce costs, enhance software development, improve customer experiences, and increase overall output.

    This article includes several statistical analyses from different sources that elaborate on the overall AI-enhancing business sectors, along with their advantages and disadvantages.

  11. G

    Generative AI Market Report

    • marketresearchforecast.com
    doc, pdf, ppt
    Updated Jan 2, 2025
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    Market Research Forecast (2025). Generative AI Market Report [Dataset]. https://www.marketresearchforecast.com/reports/generative-ai-market-1667
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    doc, pdf, pptAvailable download formats
    Dataset updated
    Jan 2, 2025
    Dataset authored and provided by
    Market Research Forecast
    License

    https://www.marketresearchforecast.com/privacy-policyhttps://www.marketresearchforecast.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The Generative AI Market size was valued at USD 43.87 USD Billion in 2023 and is projected to reach USD 453.28 USD Billion by 2032, exhibiting a CAGR of 39.6 % during the forecast period. The market's expansion is driven by the increasing adoption of AI in various industries, the growing demand for personalized experiences, and the advancement of machine learning and deep learning technologies. Generative AI is a form of AI technology that come with the capability to generate content in several of forms such us that include text, images, audio data, and artificial data. In the latest trend of the use of generative AI, fingertip friendly interfaces that allow for the creation of top-quality text design, and videos in a brief time of only seconds have been the leading cause of the hype around it. The AI technology called Generative AI employs a variety of techniques that its development is still being improved. Fundamentally, AI foundation models are based on training on a wide spate of unlabelled data that can be used for many tasks; working primarily on specific areas where additional fine-tuning finds its place. Over-simplifying the process, huge amounts of maths and computer power get used to develop AI models. Nevertheless, at its core, it is the predictions amplified. Generative AI relies on deep learning models – sophisticated machine learning models that work as neural networks and learn and take decisions just the human minds do. Such models are based on the detection and emission of codes of complex relationships or patterns in huge information volumes and that data is used to respond to users' original speech requests or questions with native language replies or new content. Recent developments include: June 2023: Salesforce launched two generative artificial intelligence (AI) products for commerce experience and customized consumers –Commerce GPT and Marketing GPT. The Marketing GPT model leverages data from Salesforce's real-time data cloud platform to generate more innovative audience segments, personalized emails, and marketing strategies., June 2023: Accenture and Microsoft are teaming up to help companies primarily transform their businesses by harnessing the power of generative AI accelerated by the cloud. It helps customers find the right way to build and extend technology in their business responsibly., May 2023: SAP SE partnered with Microsoft to help customers solve their fundamental business challenges with the latest enterprise-ready innovations. This integration will enable new experiences to improve how businesses attract, retain and qualify their employees. , April 2023: Amazon Web Services, Inc. launched a global generative AI accelerator for startups. The company’s Generative AI Accelerator offers access to impactful AI tools and models, machine learning stack optimization, customized go-to-market strategies, and more., March 2023: Adobe and NVIDIA have partnered to join the growth of generative AI and additional advanced creative workflows. Adobe and NVIDIA will innovate advanced AI models with new generations aiming at tight integration into the applications that significant developers and marketers use. . Key drivers for this market are: Growing Necessity to Create a Virtual World in the Metaverse to Drive the Market. Potential restraints include: Risks Related to Data Breaches and Sensitive Information to Hinder Market Growth . Notable trends are: Rising Awareness about Conversational AI to Transform the Market Outlook .

  12. Success.ai | B2B Company & Contact Data – 28M Verified Company Profiles -...

    • datarade.ai
    + more versions
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    Success.ai, Success.ai | B2B Company & Contact Data – 28M Verified Company Profiles - Global - Best Price Guarantee & 99% Data Accuracy [Dataset]. https://datarade.ai/data-products/success-ai-b2b-company-contact-data-28m-verified-compan-success-ai
    Explore at:
    .json, .csv, .bin, .xml, .xls, .sql, .txtAvailable download formats
    Dataset provided by
    Area covered
    United Republic of, Solomon Islands, Poland, Hungary, Côte d'Ivoire, Burundi, Somalia, India, Niger, Greenland
    Description

    Success.ai’s Company Data Solutions provide businesses with powerful, enterprise-ready B2B company datasets, enabling you to unlock insights on over 28 million verified company profiles. Our solution is ideal for organizations seeking accurate and detailed B2B contact data, whether you’re targeting large enterprises, mid-sized businesses, or small business contact data.

    Success.ai offers B2B marketing data across industries and geographies, tailored to fit your specific business needs. With our white-glove service, you’ll receive curated, ready-to-use company datasets without the hassle of managing data platforms yourself. Whether you’re looking for UK B2B data or global datasets, Success.ai ensures a seamless experience with the most accurate and up-to-date information in the market.

    Why Choose Success.ai’s Company Data Solution? At Success.ai, we prioritize quality and relevancy. Every company profile is AI-validated for a 99% accuracy rate and manually reviewed to ensure you're accessing actionable and GDPR-compliant data. Our price match guarantee ensures you receive the best deal on the market, while our white-glove service provides personalized assistance in sourcing and delivering the data you need.

    Why Choose Success.ai?

    • Best Price Guarantee: We offer industry-leading pricing and beat any competitor.
    • Global Reach: Access over 28 million verified company profiles across 195 countries.
    • Comprehensive Data: Over 15 data points, including company size, industry, funding, and technologies used.
    • Accurate & Verified: AI-validated with a 99% accuracy rate, ensuring high-quality data.
    • Real-Time Updates: Stay ahead with continuously updated company information.
    • Ethically Sourced Data: Our B2B data is compliant with global privacy laws, ensuring responsible use.
    • Dedicated Service: Receive personalized, curated data without the hassle of managing platforms.
    • Tailored Solutions: Custom datasets are built to fit your unique business needs and industries.

    Our database spans 195 countries and covers 28 million public and private company profiles, with detailed insights into each company’s structure, size, funding history, and key technologies. We provide B2B company data for businesses of all sizes, from small business contact data to large corporations, with extensive coverage in regions such as North America, Europe, Asia-Pacific, and Latin America.

    Comprehensive Data Points: Success.ai delivers in-depth information on each company, with over 15 data points, including:

    Company Name: Get the full legal name of the company. LinkedIn URL: Direct link to the company's LinkedIn profile. Company Domain: Website URL for more detailed research. Company Description: Overview of the company’s services and products. Company Location: Geographic location down to the city, state, and country. Company Industry: The sector or industry the company operates in. Employee Count: Number of employees to help identify company size. Technologies Used: Insights into key technologies employed by the company, valuable for tech-based outreach. Funding Information: Track total funding and the most recent funding dates for investment opportunities. Maximize Your Sales Potential: With Success.ai’s B2B contact data and company datasets, sales teams can build tailored lists of target accounts, identify decision-makers, and access real-time company intelligence. Our curated datasets ensure you’re always focused on high-value leads—those who are most likely to convert into clients. Whether you’re conducting account-based marketing (ABM), expanding your sales pipeline, or looking to improve your lead generation strategies, Success.ai offers the resources you need to scale your business efficiently.

    Tailored for Your Industry: Success.ai serves multiple industries, including technology, healthcare, finance, manufacturing, and more. Our B2B marketing data solutions are particularly valuable for businesses looking to reach professionals in key sectors. You’ll also have access to small business contact data, perfect for reaching new markets or uncovering high-growth startups.

    From UK B2B data to contacts across Europe and Asia, our datasets provide global coverage to expand your business reach and identify new markets. With continuous data updates, Success.ai ensures you’re always working with the freshest information.

    Key Use Cases:

    • Targeted Lead Generation: Build accurate lead lists by filtering data by company size, industry, or location. Target decision-makers in key industries to streamline your B2B sales outreach.
    • Account-Based Marketing (ABM): Use B2B company data to personalize marketing campaigns, focusing on high-value accounts and improving conversion rates.
    • Investment Research: Track company growth, funding rounds, and employee trends to identify investment opportunities or potential M&A targets.
    • Market Research: Enrich your market intelligence initiatives by gain...
  13. A

    Artificial Intelligence Statistics

    • searchlogistics.com
    Updated Apr 1, 2025
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    Search Logistics (2025). Artificial Intelligence Statistics [Dataset]. https://www.searchlogistics.com/learn/statistics/artificial-intelligence-statistics/
    Explore at:
    Dataset updated
    Apr 1, 2025
    Dataset authored and provided by
    Search Logistics
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    AI has already changed and will continue to change the way that we live. These are the latest Artificial Intelligence statistics you need to know.

  14. Companies using AI tech and services South Korea 2020-2023

    • statista.com
    Updated May 8, 2025
    + more versions
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    Statista (2025). Companies using AI tech and services South Korea 2020-2023 [Dataset]. https://www.statista.com/statistics/1386513/south-korea-companies-aware-of-artificial-intelligence/
    Explore at:
    Dataset updated
    May 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    South Korea
    Description

    In 2023, around 30.3 percent of companies in South Korea were actively using artificial intelligence (AI) technology and services. The majority of domestic companies were not utilizing AI in their business.

  15. E

    Technology In Business Statistics By Country, AI And Automation (2025)

    • electroiq.com
    Updated Jul 2, 2025
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    Electro IQ (2025). Technology In Business Statistics By Country, AI And Automation (2025) [Dataset]. https://electroiq.com/stats/technology-in-business-statistics/
    Explore at:
    Dataset updated
    Jul 2, 2025
    Dataset authored and provided by
    Electro IQ
    License

    https://electroiq.com/privacy-policyhttps://electroiq.com/privacy-policy

    Time period covered
    2022 - 2032
    Area covered
    Global
    Description

    Introduction

    Technology in Business Statistics: In today’s rapidly advancing world, technology significantly plays a crucial role in operating and growing global businesses. Technological systems, such as cloud computing, automation, data analytics, and artificial intelligence, are now implemented in small, medium, and large enterprises to improve efficiency, reduce costs, stay competitive, enable smarter decisions, and connect with customers in new ways. As technology evolves, it shapes how work is done, making it faster, more accurate, and more innovative than ever before.

    This article includes several statistical analyses from different insights that will help you understand the effectiveness of technology in global business.

  16. Data Intelligence Platform Market Report | Global Forecast From 2025 To 2033...

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Data Intelligence Platform Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/data-intelligence-platform-market
    Explore at:
    pdf, pptx, csvAvailable download formats
    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Data Intelligence Platform Market Outlook



    The global data intelligence platform market size was valued at approximately $10 billion in 2023, with an anticipated growth to reach $25.2 billion by 2032, growing at a robust CAGR of 11%. The market's growth is predominantly driven by the increasing demand for data-driven decision-making processes and the need for advanced analytics tools across various industries.



    The surge in the adoption of data intelligence platforms is largely influenced by advancements in big data technologies and the growing importance of data governance and security. Organizations across sectors such as BFSI, healthcare, and retail are increasingly leveraging data intelligence solutions to enhance operational efficiency, personalize customer experiences, and drive strategic initiatives. The integration of AI and machine learning with data intelligence platforms has further fueled market growth by providing predictive insights and automation capabilities.



    Another significant growth factor is the proliferation of cloud-based solutions, which offer scalability, cost-efficiency, and ease of deployment. Cloud-based data intelligence platforms allow organizations to handle large volumes of data and perform complex analytics without the need for extensive on-premises infrastructure. The shift towards cloud computing is also driven by the growing need for remote working capabilities and digital transformation initiatives, further propelling market expansion.



    Moreover, regulatory compliance and the emphasis on data protection laws such as GDPR in Europe and CCPA in the United States have compelled organizations to adopt robust data intelligence solutions. These platforms help ensure that data management practices align with regulatory requirements, thereby mitigating risks and enhancing data security. The rising awareness of the importance of data integrity and privacy is expected to drive the adoption of data intelligence platforms across various sectors.



    The emergence of AI-Driven Analytics Platform is revolutionizing the way organizations approach data intelligence. These platforms leverage artificial intelligence to automate complex data processes, providing businesses with real-time insights and predictive analytics. By integrating AI capabilities, companies can enhance their decision-making processes, optimize operations, and gain a competitive edge in the market. The ability to analyze vast amounts of data quickly and accurately allows organizations to identify trends, detect anomalies, and make informed decisions that drive business growth. As AI technology continues to evolve, the potential for AI-Driven Analytics Platforms to transform industries and unlock new opportunities is immense.



    Regionally, North America dominates the data intelligence platform market, owing to the presence of leading technology providers and high adoption rates of advanced analytics solutions. The Asia Pacific region is also witnessing significant growth due to the rapid digitalization of enterprises and increased investments in data infrastructure. Europe, on the other hand, is experiencing steady growth driven by stringent data protection regulations and the increasing adoption of cloud-based solutions.



    Component Analysis



    The data intelligence platform market by component is bifurcated into software and services. The software segment holds a major share in the market, driven by the increased demand for advanced analytics, business intelligence tools, and data management solutions. Software components include various types of analytics platforms, data integration tools, and AI-driven data intelligence solutions. Organizations are investing heavily in these software solutions to gain real-time insights, enhance decision-making processes, and improve overall operational efficiency.



    Within the software segment, AI and machine learning-based applications have seen significant traction. These applications enable predictive analytics, automate routine data processing tasks, and provide deeper insights into business trends and customer behaviors. The integration of AI has revolutionized data intelligence platforms by making them more intuitive, efficient, and capable of handling large datasets with ease. This trend is expected to continue, with more companies adopting AI-enabled software solutions to stay competitive.



    On the other hand, the services segme

  17. c

    AI and Analytics Systems Market size will grow at a CAGR of 38.20% from 2023...

    • cognitivemarketresearch.com
    pdf,excel,csv,ppt
    Updated Apr 23, 2024
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    Cognitive Market Research (2024). AI and Analytics Systems Market size will grow at a CAGR of 38.20% from 2023 to 2030! [Dataset]. https://www.cognitivemarketresearch.com/ai-and-analytics-systems-market-report
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Apr 23, 2024
    Dataset authored and provided by
    Cognitive Market Research
    License

    https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy

    Time period covered
    2021 - 2033
    Area covered
    Global
    Description

    According to Cognitive Market Research, The global Ai and Analytics Systems market size is USD XX million in 2023 and will expand at a compound annual growth rate (CAGR) of 38.20% from 2023 to 2030.

    The demand for AI and Analytics Systems is rising due to the rising demand for data-driven decision-making and advancements in artificial Intelligence technologies.
    Demand for Business Analytics remains higher in the AI and Analytics Systems market.
    The Large Enterprises category held the highest AI and Analytics Systems market revenue share in 2023.
    North American Ai and Analytics Systems will continue to lead, whereas the Asia-Pacific Ai and Analytics Systems market will experience the most substantial growth until 2030.
    

    Growing Demand for Data-driven Decision-making to Provide Viable Market Output

    The increasing recognition of the value of data-driven decision-making acts as a significant driver for the AI and Analytics Systems market. Organizations across industries are leveraging advanced analytics and AI technologies to extract actionable insights from large datasets. This demand is fuelled by the need to gain a competitive edge, enhance operational efficiency, and respond swiftly to market dynamics. AI-driven analytics systems enable businesses to uncover patterns, trends, and correlations in data, empowering decision-makers with valuable information to formulate strategies and make informed choices.

    In July 2022, NBFC-giant HDFC on Tuesday announced its partnership with the leading customer relationship management (CRM) platform, Salesforce, to support its growth priorities. HDFC stated that Mulesoft's innovative API-led integration approach and low code integration capabilities would help the company innovate quickly around connecting systems and help create new experiences.

    (Source:www.livemint.com/companies/news/hdfc-partners-with-salesforce-to-support-growth-11657024820434.html)

    Rise of Predictive and Prescriptive Analytics to Propel Market Growth

    The surge in demand for predictive and prescriptive analytics is a key driver propelling the AI and Analytics Systems market forward. Businesses are increasingly adopting AI-powered analytics tools to move beyond descriptive analytics and delve into predictive and prescriptive capabilities. Predictive analytics helps forecast future trends and outcomes, aiding in proactive decision-making. On the other hand, prescriptive analytics recommends actions to optimize results based on predictive insights. As organizations seek more sophisticated ways to leverage data, the integration of AI into analytics systems becomes crucial for deriving actionable foresight and strategic recommendations.

    Market Restraints of the AI and Analytics Systems

    Data Security Concerns to Restrict Market Growth
    

    one prominent driver is the growing concern over data security. As organizations increasingly rely on advanced analytics and artificial intelligence to derive insights from massive datasets, the need to secure sensitive information becomes paramount. Instances of high-profile data breaches and cyber threats have raised apprehensions among businesses and consumers alike. This heightened awareness of data security risks acts as a driver, prompting investments in AI and analytics solutions that offer robust encryption, authentication, and other security measures. This demand for secure systems aims to mitigate the potential risks associated with handling vast amounts of sensitive data.

    Demand for AI anlaytics systems is rising due to the increasing demand for the autonomous AI programs

    Impact of COVID–19 on the AI and Analytics Systems Market

    The COVID-19 pandemic has had a profound impact on the AI and Analytics Systems market. While initially, there was a slowdown in some sectors due to economic uncertainties, the pandemic ultimately accelerated the adoption of AI and analytics solutions across various industries. Organizations recognized the critical need for advanced data analytics and AI-driven insights to navigate the unprecedented challenges posed by the pandemic. This led to increased investment in AI and analytics systems to enhance business resilience, optimize operations, and gain real-time insights into rapidly changing market conditions. The demand for solutions facilitating remote work, predictive analytics for supply chain management, and AI-powered healthcare applications surged. As businesses adapted t...

  18. Success.ai | LinkedIn Full Dataset | Enrichment API – 700M Public Profiles &...

    • datarade.ai
    Updated Jan 1, 2022
    + more versions
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    Success.ai (2022). Success.ai | LinkedIn Full Dataset | Enrichment API – 700M Public Profiles & 70M Companies – Best Price and Quality Guarantee [Dataset]. https://datarade.ai/data-products/success-ai-linkedin-full-dataset-enrichment-api-700m-pu-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Jan 1, 2022
    Dataset provided by
    Area covered
    Guatemala, Tunisia, Jordan, Saint Barthélemy, Svalbard and Jan Mayen, United Republic of, Greenland, Nicaragua, Equatorial Guinea, Qatar
    Description

    Success.ai’s LinkedIn Data Solutions offer unparalleled access to a vast dataset of 700 million public LinkedIn profiles and 70 million LinkedIn company records, making it one of the most comprehensive and reliable LinkedIn datasets available on the market today. Our employee data and LinkedIn data are ideal for businesses looking to streamline recruitment efforts, build highly targeted lead lists, or develop personalized B2B marketing campaigns.

    Whether you’re looking for recruiting data, conducting investment research, or seeking to enrich your CRM systems with accurate and up-to-date LinkedIn profile data, Success.ai provides everything you need with pinpoint precision. By tapping into LinkedIn company data, you’ll have access to over 40 critical data points per profile, including education, professional history, and skills.

    Key Benefits of Success.ai’s LinkedIn Data: Our LinkedIn data solution offers more than just a dataset. With GDPR-compliant data, AI-enhanced accuracy, and a price match guarantee, Success.ai ensures you receive the highest-quality data at the best price in the market. Our datasets are delivered in Parquet format for easy integration into your systems, and with millions of profiles updated daily, you can trust that you’re always working with fresh, relevant data.

    API Integration: Our datasets are easily accessible via API, allowing for seamless integration into your existing systems. This ensures that you can automate data retrieval and update processes, maintaining the flow of fresh, accurate information directly into your applications.

    Global Reach and Industry Coverage: Our LinkedIn data covers professionals across all industries and sectors, providing you with detailed insights into businesses around the world. Our geographic coverage spans 259M profiles in the United States, 22M in the United Kingdom, 27M in India, and thousands of profiles in regions such as Europe, Latin America, and Asia Pacific. With LinkedIn company data, you can access profiles of top companies from the United States (6M+), United Kingdom (2M+), and beyond, helping you scale your outreach globally.

    Why Choose Success.ai’s LinkedIn Data: Success.ai stands out for its tailored approach and white-glove service, making it easy for businesses to receive exactly the data they need without managing complex data platforms. Our dedicated Success Managers will curate and deliver your dataset based on your specific requirements, so you can focus on what matters most—reaching the right audience. Whether you’re sourcing employee data, LinkedIn profile data, or recruiting data, our service ensures a seamless experience with 99% data accuracy.

    • Best Price Guarantee: We offer unbeatable pricing on LinkedIn data, and we’ll match any competitor.
    • Global Scale: Access 700 million LinkedIn profiles and 70 million company records globally.
    • AI-Verified Accuracy: Enjoy 99% data accuracy through our advanced AI and manual validation processes.
    • Real-Time Data: Profiles are updated daily, ensuring you always have the most relevant insights.
    • Tailored Solutions: Get custom-curated LinkedIn data delivered directly, without managing platforms.
    • Ethically Sourced Data: Compliant with global privacy laws, ensuring responsible data usage.
    • Comprehensive Profiles: Over 40 data points per profile, including job titles, skills, and company details.
    • Wide Industry Coverage: Covering sectors from tech to finance across regions like the US, UK, Europe, and Asia.

    Key Use Cases:

    • Sales Prospecting and Lead Generation: Build targeted lead lists using LinkedIn company data and professional profiles, helping sales teams engage decision-makers at high-value accounts.
    • Recruitment and Talent Sourcing: Use LinkedIn profile data to identify and reach top candidates globally. Our employee data includes work history, skills, and education, providing all the details you need for successful recruitment.
    • Account-Based Marketing (ABM): Use our LinkedIn company data to tailor marketing campaigns to key accounts, making your outreach efforts more personalized and effective.
    • Investment Research & Due Diligence: Identify companies with strong growth potential using LinkedIn company data. Access key data points such as funding history, employee count, and company trends to fuel investment decisions.
    • Competitor Analysis: Stay ahead of your competition by tracking hiring trends, employee movement, and company growth through LinkedIn data. Use these insights to adjust your market strategy and improve your competitive positioning.
    • CRM Data Enrichment: Enhance your CRM systems with real-time updates from Success.ai’s LinkedIn data, ensuring that your sales and marketing teams are always working with accurate and up-to-date information.
    • Comprehensive Data Points for LinkedIn Profiles: Our LinkedIn profile data includes over 40 key data points for every individual and company, ensuring a complete understandin...
  19. B

    Big Data Technology Market Report

    • marketresearchforecast.com
    doc, pdf, ppt
    Updated Dec 14, 2024
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    Market Research Forecast (2024). Big Data Technology Market Report [Dataset]. https://www.marketresearchforecast.com/reports/big-data-technology-market-1717
    Explore at:
    doc, ppt, pdfAvailable download formats
    Dataset updated
    Dec 14, 2024
    Dataset authored and provided by
    Market Research Forecast
    License

    https://www.marketresearchforecast.com/privacy-policyhttps://www.marketresearchforecast.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The Big Data Technology Market size was valued at USD 349.40 USD Billion in 2023 and is projected to reach USD 918.16 USD Billion by 2032, exhibiting a CAGR of 14.8 % during the forecast period. Big data is larger, more complex data sets, especially from new data sources. These data sets are so voluminous that traditional data processing software just can’t manage them. But these massive volumes of data can be used to address business problems that wouldn’t have been able to tackle before. Big data technology is defined as software-utility. This technology is primarily designed to analyze, process and extract information from a large data set and a huge set of extremely complex structures. This is very difficult for traditional data processing software to deal with. Among the larger concepts of rage in technology, big data technologies are widely associated with many other technologies such as deep learning, machine learning, artificial intelligence (AI), and Internet of Things (IoT) that are massively augmented. In combination with these technologies, big data technologies are focused on analyzing and handling large amounts of real-time data and batch-related data. Recent developments include: February 2024: - SQream, a GPU data analytics platform, partnered with Dataiku, an AI and machine learning platform, to deliver a comprehensive solution for efficiently generating big data analytics and business insights by handling complex data., October 2023: - MultiversX (ELGD), a blockchain infrastructure firm, formed a partnership with Google Cloud to enhance Web3’s presence by integrating big data analytics and artificial intelligence tools. The collaboration aims to offer new possibilities for developers and startups., May 2023: - Vpon Big Data Group partnered with VIOOH, a digital out-of-home advertising (DOOH) supply-side platform, to display the unique advertising content generated by Vpon’s AI visual content generator "InVnity" with VIOOH's digital outdoor advertising inventories. This partnership pioneers the future of outdoor advertising by using AI and big data solutions., May 2023: - Salesforce launched the next generation of Tableau for users to automate data analysis and generate actionable insights., March 2023: - SAP SE, a German multinational software company, entered a partnership with AI companies, including Databricks, Collibra NV, and DataRobot, Inc., to introduce the next generation of data management portfolio., November 2022: - Thai Oil and Retail Corporation PTT Oil and Retail Business Public Company implemented the Cloudera Data Platform to deliver insights and enhance customer engagement. The implementation offered a unified and personalized experience across 1,900 gas stations and 3,000 retail branches., November 2022: - IBM launched new software for enterprises to break down data and analytics silos that helped users make data-driven decisions. The software helps to streamline how users access and discover analytics and planning tools from multiple vendors in a single dashboard view., September 2022: - ActionIQ, a global leader in CX solutions, and Teradata, a leading software company, entered a strategic partnership and integrated AIQ’s new HybridCompute Technology with Teradata VantageCloud analytics and data platform.. Key drivers for this market are: Increasing Adoption of AI, ML, and Data Analytics to Boost Market Growth . Potential restraints include: Rising Concerns on Information Security and Privacy to Hinder Market Growth. Notable trends are: Rising Adoption of Big Data and Business Analytics among End-use Industries.

  20. d

    Coresignal | Private Company Data | Company Data | AI-Enriched Datasets |...

    • datarade.ai
    .json, .csv
    Updated Aug 13, 2023
    + more versions
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    Coresignal (2023). Coresignal | Private Company Data | Company Data | AI-Enriched Datasets | Global / 35M+ Records / Updated Weekly [Dataset]. https://datarade.ai/data-products/coresignal-private-company-data-company-data-ai-enriche-coresignal
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Aug 13, 2023
    Dataset authored and provided by
    Coresignal
    Area covered
    Grenada, Jamaica, Kyrgyzstan, Argentina, Benin, Senegal, Togo, Pitcairn, Kiribati, Bhutan
    Description

    This Private Company Data dataset is a refined version of our company datasets, consisting of 35M+ data records.

    It’s an excellent data solution for companies with limited data engineering capabilities and those who want to reduce their time to value. You get filtered, cleaned, unified, and standardized B2B private company data. This data is also enriched by leveraging a carefully instructed large language model (LLM).

    AI-powered data enrichment offers more accurate information in key data fields, such as company descriptions. It also produces over 20 additional data points that are very valuable to B2B businesses. Enhancing and highlighting the most important information in web data contributes to quicker time to value, making data processing much faster and easier.

    For your convenience, you can choose from multiple data formats (Parquet, JSON, JSONL, or CSV) and select suitable delivery frequency (quarterly, monthly, or weekly).

    Coresignal is a leading private company data provider in the web data sphere with an extensive focus on firmographic data and public employee profiles. More than 3B data records in different categories enable companies to build data-driven products and generate actionable insights. Coresignal is exceptional in terms of data freshness, with 890M+ records updated monthly for unprecedented accuracy and relevance.

Share
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Close
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Statista (2025). Most used AI technologies among retail businesses in the United States 2024 [Dataset]. https://www.statista.com/statistics/1384355/most-used-ai-technologies-among-retail-businesses-united-states/
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Most used AI technologies among retail businesses in the United States 2024

Explore at:
Dataset updated
Jun 25, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Dec 2023 - Feb 2024
Area covered
United States
Description

In the United States, most retail companies are likely to use artificial intelligence (AI) for marketing purposes. Nearly ** percent of professionals from retail companies answering a survey in 2024 stated that their enterprises will be using AI to handle marketing automation. Chatbots and virtual shopping assistants follow in the ranking, with **** percent of answers.

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