Among recent major technologies in the United States, generative artificial intelligence (AI) had a much steeper leap in users in year * from year * than the other major technologies. Nearly ** times the amount of people had used generative AI within a year of its making, compared to * times the amount of tablet users and barely * times the amount of smartphone users. This leap has not remained steady, however, and tablets had more users in year * since its release than is expected of generative AI. U.S. citizens are skeptical Adults in the United States were somewhat concerned with the development and growth of generative AI in 2023. While most were somewhat concerned another third was mostly concerned, and relatively few individuals were excited. This is understandable with the rapid growth of new technology, as change and unknown factors always cause concern among the wider population. Investment in tech going strong In the U.S. investment in new technologies and generative AI were among the highest in enterprises. These topped investments in hiring, cost-cutting, and outsourcing. This high rate of investment in new technologies and AI is likely driven by the whole-of-enterprise effect that these trends might have on companies.

As of 2023, nearly ** percent of digital leaders globally stated that their companies adopted cloud technology either on small or large scale. Big data/ analytics were the second most popular adopted technology with around ** percent of respondents reporting the same. Artificial intelligence/ machine learning At the same time, ** percent of respondents were considering using Artificial intelligence (AI) / machine learning (ML) technology, while ** percent said that their companies were piloting the implementation AI/ML technology. What is cloud computing?   Cloud computing refers to the use of networks of remote servers accessed over the internet to store, manage, and process data. It offers customers access to a wide range of technologies while lowering costs and reducing the need for technical expertise. The cloud service market is divided into three primary service models encompassing infrastructure, platforms, and software. Customers are able to choose between private, public, or hybrid cloud deployment depending on their business needs and security concerns. SaaS: the most widely adopted cloud solutions     In line with increases in companies’ adoption of cloud computing technologies, the worldwide revenue generated from these technologies has increased rapidly in recent years. Software as a Service (SaaS) is the largest segment of the global cloud computing market with revenues forecast to be around *** billion U.S. dollars in 2023. Popular applications of SaaS include customer relationship management and enterprise resource planning software.

This statistic shows the responses to a survey regarding digital technology adoption among organizations in Canada, by technology platform, as of 2016. During the reported period, 74 percent of organizations surveyed reported utilizing cloud computing technologies.

By comparing data from 2022 and 2024, it appeared that technology adoption in farming grew on a global scale. This was especially true of North America and Latin America. The latter witnessed the fastest growth, as the share of farmers using or willing to adopt at least one new technology in 2024 increased by ** percent compared to 2022 (** percent of respondents in 2024 against ** percent in 2022). In Europe, on the other hand, data highlighted a negative trend (** percent of farmers in 2024 against ** percent in 2022).

A survey by SWZD revealed that in ** percent of businesses across the Asia-Pacific region planned to adopt IT automation technology within the next two years. The majority of surveyed companies in the regions would also likely to adopt other cloud and emerging technologies such as serverless computing, gigabit wi-fi networking, and ** technology.

Blockchain technology has the potential to improve supply chain transparency if further adopted in warehouse automation. In 2019, the technology adoption rate was only at eight percent, but it has the potential to rise to ** percent by 2030.

Technological innovation market diffusion data.Principal dataset sources.----The Cross-country Historical Adoption of Technology (CHAT) Dataset. No. w15319. National Bureau of Economic Research, 2009. [67]Discovered via Horace Dediu, Clayton Christensen Institute. [68]Note: Only U.S. data was extracted and used.----Comin, D.A., & Hobijn, B. (2004). Cross-country technology adoption: making the theories face the facts. Journal of Monetary Economics 51.1 (2004): 39-83. [69]Discovered via Ritchie, H., & Roser, M. (2017). Technology Diffusion & Adoption. [70]Note: Only U.S. data was extracted and used.----Cox, W. M., & Alm, R. (1997). Time Well Spent: The Declining Real Cost of Living in America. Annual Report Federal Reserve Bank of Dallas, pages 2-24 [71]Derived and built from American Association of Home Appliance Manufacturers; Cellular Telephone Industry Association; Electrical Merchandising, various issues; Information Please Almanac; Public Roads Administration; Television Bureau of Advertising; U.S. Bureau of the Census (Census of Housing; Current Population Reports; Historical Statistics of the United States, Colonial Times to 1970; Statistical Abstract of the United States); U.S. Department of Energy; U.S. Department of Transportation.

Introduction

Backup Statistics: As the world is transforming digitally, data is termed as the backbone of both personal and professional life. Backup is the crucial process of creating a copy of important files and information to protect against loss. This practice is essential because data can be lost due to accidental deletion, hardware failure, or cyberattacks. With growing threats like ransomware, hardware failure, and accidental deletion, having a reliable backup strategy is no longer optional; it’s essential.

This article includes current statistical analysis from different sources that will cover all the importance of data backup, the evolving landscape of backup solutions, and what individuals and organizations need to know to stay protected.

Copeland, Adam, and Shapiro, Adam Hale, (2016) "Price Setting and Rapid Technology Adoption: The Case of the PC Industry." Review of Economics and Statistics 98:3, 601-616.

ABSTRACT Managerial decisions on the adoption of innovative technologies by a firm are made under conditions of uncertainty and must account for network externalities that imply the benefit of a technology is received not only from its intrinsic payoff, but also from the size of the network of other adopters. The theoretical model presented in this study demonstrates that for firms evaluating information technology investment with network effects key determinants of the technology selection pattern are adoption reversibility and switching costs. If switching costs are sufficiently high to make technology adoption irreversible then safer established technologies have an advantage as choosing a riskier untested technology opens the firm to the risk of being stranded without a network of followers. With lower switching costs, the technology adoption decision is reversible which provides an advantage to riskier untested technologies. A discussion of empirical evidence on adoption patterns in information technology provides application for the theoretical model.

In 2020, hotel executives in the United States were surveyed on their adoption rates of contactless hotel technologies. The majority of respondents, 44 percent, stated that they were considering new digital messaging services to handle guest requests in the future.

About the Dataset

The Historical Adoption of TeCHnologies (HATCH) dataset provides yearly data of technology adoption levels at both the global and country levels. The dataset includes a heterogeneous set of technologies that differ in their size, use, and spatial diffusion. The following files are available.

Citation

The paper can be cited as: Nemet, G., Greene, J., Müller-Hansen, F. et al. Dataset on the adoption of historical technologies informs the scale-up of emerging carbon dioxide removal measures. Commun Earth Environ 4, 397 (2023). https://doi.org/10.1038/s43247-023-01056-1

Paper describing the data is available here: https://www.nature.com/articles/s43247-023-01056-1

File Descriptions

HATCH1.0.csv

Description: Dataset used in the analysis for "Dataset on the adoption of historical technologies informs the scale-up of emerging carbon dioxide removal measures," which includes a limited number of country-level datapoints.

HATCH_v1.5_Clean.csv

Description: Expanded dataset that includes country-level adoption of many technologies used in v1.0, with the addition of more global technology time series.

Tech_Growth_V1.5_variabledescriptions_Clean.yaml

Description: Description of each technology, including description, metric, and technology category.

HATCH_v1.5_DataSources.csv

Description: Lists the data sources and corresponding citations for each technology in the HATCH dataset.

Code for calculating growth rates available at: DOI: 10.5281/zenodo.8327347

Table of growth rate calculations for each technology available at: https://zenodo.org/records/10056128

Link to Scenario Explorer hosted by IIASA: https://cdr.apps.ece.iiasa.ac.at/story/hatch/

Abstract

Malawi Technology Adoption and Risk Initiative (MTARI) household baseline survey is a part of a larger impact evaluation study, being conducted by the World Bank and the University of Michigan researchers. The randomized field experiment was designed to examine whether provision of insurance against a major source of production risk induces farmers to take out loans to adopt a new crop technology. The study sample was composed of roughly 800 maize and groundnut farmers. Randomly selected half of the farmers in the sample were offered a credit to purchase high-yielding hybrid maize and groundnut seeds for planting in the November 2006 crop season. The other half of farmers were offered a similar credit package, but were also required to purchase (at actuarially fair rates) a weather insurance policy that partially or fully forgave the loan in the event of poor rainfall. In Malawi, the dominant source of production risk is the level of rainfall.

The household baseline survey was administered to all farmers in the sample in September and October 2006. The survey covered income, education, assets, income-generating activities (including detailed information on crop production and crop choice), measures of risk aversion, and knowledge about financial products such as credit and insurance.

Geographic coverage

Lilongwe North, Mchinji, Kasungu, and Nkhotakota regions in central Malawi.

Analysis unit

• individuals,
• households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The study sample was composed of roughly 800 maize and groundnut farmers in 32 localities in central Malawi. Researchers randomly selected 16 localities where farmers were offered credit to purchase high-yielding hybrid maize and groundnut seeds for planting in the November 2006 crop season. In the remaining 16 localities, farmers were offered a similar credit package, but were also required to purchase a weather insurance policy that partially or fully forgave the loan in the event of poor rainfall.

The farmers in the study were current National Smallholder Farmers Association of Malawi (NASFAM) members. NASFAM contacted clubs (composed of 10-20 farmers) in June and July 2006 and offered them the opportunity to be included in the study. The study sample consists of 159 clubs from four different regions of central Malawi: Lilongwe North, Mchinji, Kasungu, and Nkhotakota. In these clubs there were 787 farmers who agreed to be part of the study and were available to be surveyed in the following September.

Mode of data collection

Face-to-face [f2f]

What Is DREAM? DREAM, or Dynamic Research Evaluation for Management, is a menu-driven software package for evaluating the economic impacts of agricultural research and development (R and D). Users can simulate a range of market, technology adoption, research spillover, and trade policy scenarios based on a flexible, multi-market, partial equilibrium model. With DREAM you can define a range of technology investment, development, and adoption scenarios and save them in an integrated database. Scenarios are described using market, R and D, and adoption information for any number of separate "regions." Some factors, such as taxes, subsidies, growth rates, and price elasticities, can be specified as constant or as changing over the analysis period. Each region in which production takes place may have its own pattern of technology adoption. After specifying the initial conditions for each region, you can simulate the likely effects of technology development and adoption on prices; on quantities produced, consumed, and traded; and on the flow of economic benefits to producers, consumers, and government. DREAM handles simple to relatively complex evaluation problems using a standardized interface. A number of market assumptions are possible: small open economy, closed economy, vertically integrated farm and post-harvest sectors in a single economy, or multiple trading regions. The software also accommodates technology-driven shifts in supply or demand, and users may specify constant or variable shift effects over time in farmers fields. Importantly, DREAM's multiple region specification can simulate various technology "spillover" scenarios wherein a technology may be adopted in more than one region. Changes in the pattern of technology spillovers can significantly alter the size and distribution of R and D benefits. DREAM has been applied to the evaluation of individual projects in a national context as well as to entire commodity sectors at a subcontinental or continental scale. And while it was designed primarily to evaluate options for R and D that is yet to be undertaken (ex ante assessments), DREAM has also been successfully applied to analyzing the effect of past research (ex post assessments).

The dataset for this research project was meticulously constructed to investigate the adoption of ChatGPT among students in the United States. The primary objective was to gain insights into the technological barriers and resistances faced by students in integrating ChatGPT into their information systems. The dataset was designed to capture the diverse adoption patterns among students in various public and private schools and universities across the United States. By examining adoption rates, frequency of usage, and the contexts in which ChatGPT is employed, the research sought to provide a comprehensive understanding of how students are incorporating this technology into their information systems. Moreover, by including participants from diverse educational institutions, the research sought to ensure a comprehensive representation of the student population in the United States. This approach aimed to provide nuanced insights into how factors such as educational background, institution type, and technological familiarity influence ChatGPT adoption.

This statistic depicts the share of companies in the aviation, travel and tourism industry worldwide who are likely to adopt new technologies between 2018 and 2022, broken down by technology. During the survey, ** percent of respondents stated they are likely or very likely to adopt the 'internet of things'.

Beacon Technology Market Outlook

The global beacon technology market size is projected to grow from USD 2.5 billion in 2023 to USD 31.9 billion by 2032, reflecting an impressive CAGR of 33.2% over the forecast period. One of the most significant growth factors for this market is the increasing adoption of proximity marketing, a key component in the digital transformation strategies of many industries.

Several driving factors contribute to the robust growth of the beacon technology market. Firstly, the escalating demand for location-based services (LBS) and growing investments in smart city projects are major catalysts. Many urban centers are deploying beacon technology to enhance public services, traffic management, and urban planning, which is expected to significantly drive market expansion. Additionally, industries such as retail and healthcare are leveraging beacon technology to improve customer engagement and operational efficiency, respectively. This widespread adoption across sectors is further bolstering market growth.

Secondly, advancements in Bluetooth Low Energy (BLE) technology have made beacons more efficient and cost-effective, thereby increasing their adoption. BLE beacons offer extended battery life and broader range, making them suitable for various applications from indoor navigation to asset tracking. The reduced power consumption and the enhanced capabilities of BLE beacons have made them a preferred choice for businesses looking to implement proximity-based solutions. Coupled with the falling prices of beacon hardware, this technological evolution is a pivotal growth driver.

Moreover, the proliferation of smartphones and increasing internet penetration are acting as enablers for beacon technology. With the majority of the global population now using smartphones, the potential user base for beacon-enabled applications has significantly expanded. Businesses are increasingly utilizing mobile apps integrated with beacon technology to offer personalized experiences, real-time notifications, and interactive services. This trend is particularly noticeable in retail, where beacons are used for targeted advertisements, in-store navigation, and customer analytics.

From a regional perspective, North America currently dominates the beacon technology market due to high technology adoption rates and significant investments in IoT infrastructure. Europe follows closely, driven by robust developments in smart city initiatives and retail innovations. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period. Factors such as rapid urbanization, increasing disposable incomes, and growing emphasis on digitalization are contributing to the burgeoning demand for beacon technology in this region.

Component Analysis

The beacon technology market is segmented into three main components: hardware, software, and services. Each of these components plays a crucial role in the overall ecosystem of beacon technology, contributing to its functionality, deployment, and maintenance. The hardware segment includes the physical beacon devices, which are essential for emitting signals and interacting with user devices. This segment is witnessing significant advancements in terms of miniaturization, battery life, and signal range, making beacons more versatile and cost-effective.

The software segment comprises the platforms and applications that facilitate the interaction between beacons and user devices. This includes mobile apps, content management systems, and analytics platforms. Software solutions are critical for configuring beacons, managing campaigns, and analyzing user data. The increasing adoption of cloud-based solutions is driving growth in this segment, as it allows for scalable and flexible deployment of beacon services. Additionally, advancements in software development are enabling more sophisticated and personalized user experiences.

Services play a vital role in the deployment and management of beacon technology. This includes consulting, installation, maintenance, and support services. As the adoption of beacon technology grows, the demand for professional services is also increasing. Companies are seeking expertise in designing and implementing beacon-enabled solutions to maximize their ROI. Service providers are also focusing on offering end-to-end solutions, from initial consultation to ongoing support, to meet the diverse needs of their clients.

Furthermore, the integration of Artificial Intelligence (AI) and Machine Learning (ML

Snapshot img

Human Resource Technology Market Size 2025-2029

The human resource (HR) technology market size is forecast to increase by USD 18.31 billion, at a CAGR of 8.4% between 2024 and 2029.

The market is experiencing significant growth, driven by several key trends. One of the most notable trends is the increasing adoption of HR technology among Small and Medium-sized Enterprises (SMEs). This is due to the cost savings and efficiency gains that HR technology can provide. Another trend is the integration of artificial intelligence (AI) in HR solutions, which is enabling more accurate and data-driven hiring decisions. However, the market also faces challenges, including data security and privacy concerns. As companies adopt more advanced HR technologies, ensuring the security and confidentiality of employee data becomes a top priority. This report provides a comprehensive analysis of these trends and challenges, offering insights into the future growth prospects of the HR technology market.

What will be the Size of the human resource (HR) technology Market During the Forecast Period?

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The market is experiencing significant growth and transformation, driven by the increasing demand for digital solutions to enhance workplace culture, productivity, and employee engagement. AI chatbots and people analytics are leading tech trends, automating routine HR tasks and providing valuable insights for leadership in areas such as talent retention, employee development, and diversity and inclusion. Cloud-based HR software solutions enable remote team management, compliance, and outsourcing, while also facilitating process automation and ethics in areas like recruitment and employee onboarding.
Employee well-being and benefits are also key focus areas, with technology playing a crucial role in employee productivity, engagement strategies, and communication. Digital transformation is a top priority for organizations, with HR technology adoption becoming essential for effective workforce planning and branding. Employee reskilling and diversity and inclusion are also critical areas of focus, as companies seek to stay competitive and foster a culture of innovation and continuous improvement.

How is this human resource (HR) technology Industry segmented and which is the largest segment?

The human resource (HR) technology industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Application

  Payroll processing
  Applicant management
  Learning and development
  Talent management
  Others


End-user

  Large enterprises
  Small and medium enterprises (SMEs)
  Government organizations
  Non-profit organizations


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK
    France


  APAC

    China
    India
    Japan


  South America

    Brazil


  Middle East and Africa

By Application Insights

The payroll processing segment is estimated to witness significant growth during the forecast period.

The market encompasses a variety of solutions for managing payroll processing, workforce management, recruitment, and employee experience. Payroll processing solutions are essential, automating salary calculations, tax deductions, benefits management, and pay slip generation. Automated payroll systems streamline the process, reducing HR administrative burden and minimizing errors. Compliance features ensure adherence to local and global payroll regulations. Other HR technologies include cloud-based workforce management tools for scheduling, time tracking, and attendance monitoring, and recruitment platforms for streamlining the hiring process. Employee experience platforms focus on enhancing employee engagement and satisfaction. Payroll processing solutions remain a crucial application within the HR technology market, ensuring accurate and timely compensation for employees while maintaining regulatory compliance.

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The payroll processing segment was valued at USD 5.47 billion in 2019 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 42% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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The North American market is driven by the high adoption rate of advanced HR solutions among businesses of all sizes, with small businesses playing a pivotal role. in the United States, there were approximately 34 million small bus

AI-Powered Writing Assistant Software Market Outlook

The global market size for AI-powered writing assistant software was valued at approximately USD 1.2 billion in 2023 and is forecasted to reach USD 10.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 26.7%. This surge is driven by increasing digital transformation initiatives across industries, coupled with advancements in natural language processing (NLP) and machine learning (ML) technologies.

One of the primary growth factors for this market is the rising demand for automation in content creation and editing processes. Businesses and individuals are increasingly relying on AI-powered tools to streamline the creation of high-quality content, thus enhancing productivity and reducing operational costs. Additionally, the growing complexity of content management in industries such as marketing and customer support has fueled the adoption of these advanced tools. AI-powered writing assistants help in generating content that is not only grammatically correct but also tailored to specific audience needs, thereby improving engagement and effectiveness.

Another significant driver is the increasing penetration of cloud-based solutions. Cloud deployment offers several advantages, such as scalability, flexibility, and cost-effectiveness, which are particularly beneficial for small and medium enterprises (SMEs). The ability to access writing assistant tools from anywhere, combined with the ease of integration with other cloud-based applications, is accelerating the adoption rate. Furthermore, the frequent updates and improvements that cloud solutions offer without the need for manual intervention by the user make them highly attractive.

The integration of AI-powered writing assistants into various applications, such as email clients, word processors, and customer relationship management (CRM) systems, is also contributing to market growth. This seamless integration enhances user experience by providing real-time suggestions and corrections, thereby making communication more efficient and effective. Moreover, the growing application of AI in educational institutions for improving student writing skills and assisting educators in grading and feedback processes is noteworthy.

Regionally, North America holds a significant share of the AI-powered writing assistant software market, driven by high technology adoption rates and substantial investments in AI and ML technologies. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period due to increasing digital transformation efforts and growing awareness about the benefits of AI-powered solutions. The availability of a large, untapped market and the rapid pace of technology adoption are key factors contributing to this growth.

Component Analysis

The AI-powered writing assistant software market is segmented by components into software and services. The software segment comprises the core writing assistant tools that are responsible for generating, editing, and improving content. These tools leverage advanced NLP and ML algorithms to provide real-time suggestions on grammar, style, tone, and readability. The software segment dominates the market due to its direct application in various content creation and management processes. Organizations are increasingly investing in these tools to enhance their content quality and operational efficiency.

Within the software segment, there is a growing trend towards the development of specialized modules tailored to specific industry needs. For example, some tools are designed specifically for marketing content, offering features like SEO optimization and keyword suggestions. Others focus on technical writing, providing advanced grammar checks and consistency checks that align with industry standards. This trend towards specialization is driving further growth in the software segment.

The services segment includes consulting, implementation, and support services associated with AI-powered writing assistant software. These services are crucial for organizations that need assistance with the integration and customization of writing assistant tools into their existing workflows. Expert consulting services help organizations identify the most suitable tools for their needs, while implementation services ensure seamless deployment. Ongoing support services are essential for troubleshooting and ensuring the optimal performance of the software, thereby contributing to customer satisfaction and retention.

The global Legal Tech market is experiencing robust growth, driven by the increasing adoption of technology within law firms and legal departments. The market, estimated at $15 billion in 2025, is projected to grow at a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. Firstly, the rising volume of legal data necessitates efficient management solutions like e-discovery and legal analytics. Secondly, the demand for improved legal practice management tools, aimed at streamlining operational efficiency and reducing costs, is a significant driver. Thirdly, increasing awareness of the benefits of AI-powered legal technologies, such as contract analysis and automated document review, is further propelling market growth. Finally, the ongoing digital transformation within the legal sector is accelerating the adoption of these technologies across various segments. The North American market currently holds the largest share, followed by Europe, due to high technological adoption rates and established legal tech infrastructure in these regions. The market segmentation reveals a strong demand across all applications (government, commercial) and types (e-discovery, legal analytics, legal practice management). While e-discovery currently dominates, legal analytics and legal practice management are experiencing faster growth, indicating a shift towards more proactive and data-driven legal practices. Competitive landscape analysis indicates a mix of established players and emerging startups, leading to innovation and competitive pricing. However, challenges remain, including high implementation costs, data security concerns, and the need for ongoing training and support for legal professionals adopting new technologies. Overcoming these hurdles will be crucial for sustained market growth and wider adoption of Legal Tech solutions.