List of supplementary figures

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.

This statistic shows the impact of automation and artificial intelligence on the number of IT and business processing outsourcing (BPO) services workers around the world, in terms of skill level, from 2016 to 2022. By 2022, the number of highly skilled IT/BPO service workers is projected to increase by **** million, whereas the number of low-skilled service workers is forecast to decrease by **** million, due to the application of automation and AI.

Introduction

According to Market.us's analysis, The Global DeepFake AI Market is projected to grow significantly over the next decade, with its market size expected to reach USD 18,989.4 million by 2033, up from USD 550 million in 2023. This represents an impressive compound annual growth rate (CAGR) of 42.5% between 2024 and 2033.

In 2023, North America emerged as the dominant region, holding a substantial 38.5% market share, which amounted to approximately USD 211.7 million in revenue. This strong position can be attributed to advanced AI research infrastructure, high adoption rates of new technologies, and growing demand for DeepFake AI solutions across industries such as entertainment, advertising, and cybersecurity.

DeepFake AI technology involves the use of artificial intelligence to create or manipulate video and audio content with a high degree of realism. This technology primarily leverages machine learning algorithms to superimpose existing images and videos onto source images or videos using a technique known as generative adversarial networks (GANs). The potential applications of DeepFake AI are vast, ranging from entertainment and media to more sensitive uses like personalizing digital interactions and creating realistic simulations for training purposes.

The market for DeepFake AI is expanding as the technology becomes more accessible and its potential applications across various industries are recognized. As of 2023, the market has seen considerable growth, driven by industries such as media, entertainment, and cybersecurity, where there is a demand for more sophisticated and realistic simulation technologies. Companies are investing in developing safeguards against the misuse of DeepFake technologies, which is also fostering growth in the cybersecurity sector.

The rapid advancement in AI and machine learning technologies, particularly in the area of generative adversarial networks (GANs), is a significant driver of the DeepFake AI market. Innovations in neural network architectures and the increasing computational power available make it possible to create more realistic and convincing deepfakes. These technological improvements enhance the potential uses of DeepFake AI, expanding its application across various sectors including entertainment, advertising, and education.

As the technology progresses, new opportunities arise within verticals that could benefit from hyper-realistic simulations. For instance, in the film industry, DeepFake technology can be used to rejuvenate older actors or to continue the legacy of deceased ones. Additionally, in training and education, realistic scenarios can be simulated without the need for physical presence, reducing costs and improving learning outcomes. The growing interest in personalized content also presents significant opportunities for this market.

The global reach of DeepFake technology is expanding as awareness of its capabilities increases. Emerging markets are beginning to explore the potential applications of DeepFakes, leading to a broader market expansion. Furthermore, as the technology finds legitimate uses, such as in customer service avatars and virtual assistants, the market continues to grow. The integration of DeepFake technology into mobile applications and social media platforms is further democratizing access, thereby expanding the market significantly.

The market for artificial intelligence grew beyond *** billion U.S. dollars in 2025, a considerable jump of nearly ** billion compared to 2023. This staggering growth is expected to continue, with the market racing past the trillion U.S. dollar mark in 2031. AI demands data Data management remains the most difficult task of AI-related infrastructure. This challenge takes many forms for AI companies. Some require more specific data, while others have difficulty maintaining and organizing the data their enterprise already possesses. Large international bodies like the EU, the US, and China all have limitations on how much data can be stored outside their borders. Together, these bodies pose significant challenges to data-hungry AI companies. AI could boost productivity growth Both in productivity and labor changes, the U.S. is likely to be heavily impacted by the adoption of AI. This impact need not be purely negative. Labor rotation, if handled correctly, can swiftly move workers to more productive and value-added industries rather than simple manual labor ones. In turn, these industry shifts will lead to a more productive economy. Indeed, AI could boost U.S. labor productivity growth over a 10-year period. This, of course, depends on various factors, such as how powerful the next generation of AI is, the difficulty of tasks it will be able to perform, and the number of workers displaced.

The Artificial Intelligence (AI) Model Service market is experiencing explosive growth, driven by the increasing adoption of AI across various industries. While precise market size figures for 2025 are unavailable, considering the rapid advancements and investments in AI, a reasonable estimate places the market value at $50 billion. This substantial figure reflects the high demand for pre-trained and customizable AI models, eliminating the need for companies to develop these complex systems from scratch. Key drivers include the decreasing cost of cloud computing, the rising availability of large datasets for training, and the growing need for automation and improved efficiency across sectors like healthcare, finance, and manufacturing. The market is segmented by application (e.g., image recognition, natural language processing, predictive analytics) and model type (e.g., generative, discriminative). Leading players like OpenAI, Google, Amazon Web Services, and Microsoft are heavily investing in research and development, leading to continuous innovation and improvements in model accuracy and performance. Trends such as the increasing use of edge AI and the growing adoption of AI in small and medium-sized enterprises (SMEs) further contribute to the market's expansion. However, challenges remain, including concerns about data privacy, ethical implications of AI, and the need for skilled professionals to manage and deploy these sophisticated models effectively. Despite these restraints, the overall market outlook is overwhelmingly positive, with a projected Compound Annual Growth Rate (CAGR) suggesting a substantial increase in market value over the forecast period (2025-2033). The competitive landscape is dynamic, with established tech giants competing with innovative startups. The geographic distribution of the market shows strong growth in North America and Asia Pacific, driven by the presence of major technology hubs and early adoption of AI solutions. Europe and other regions are also experiencing significant growth, albeit at a potentially slightly slower pace. The forecast period (2025-2033) anticipates continued market expansion, fueled by technological breakthroughs, increased investment, and wider industry adoption. The market's evolution will be significantly shaped by ongoing research into explainable AI, improved model security, and the development of more efficient training techniques. Companies will likely focus on developing specialized AI models tailored to specific industry needs, offering customized solutions to further accelerate market growth. The ongoing development of more accessible and user-friendly AI tools is expected to widen the adoption across different segments, leading to continuous expansion throughout the forecast period.

As of 2019, 57 percent of Swedes reported to be concerned about artificial intelligence (AI) misusing their personal data. The corresponding figures for Norwegians and Finns were 47 percent and 58 percent. Another main concern regarding handling personal data was interpreting the data wrong.

The data consists the figures required in the paper Matrix multiplication using Neuromorphic computing

The Artificial Intelligence (AI) Tools market is experiencing robust growth, driven by increasing adoption across diverse sectors. While precise market size figures are unavailable, considering the involvement of major tech players like IBM, Google, and Microsoft, and the rapid advancements in AI capabilities, a reasonable estimate for the 2025 market size could be around $150 billion. This substantial market is projected to exhibit a Compound Annual Growth Rate (CAGR) of approximately 25% from 2025 to 2033, indicating a significant expansion in the coming years. This growth is propelled by several key factors. The rising availability of large datasets, advancements in machine learning algorithms, and the decreasing cost of computing power are democratizing AI adoption. Industries such as healthcare (with players like GE Healthcare and Siemens Healthineers), agriculture (with companies like The Climate Corporation and Agribotix), and finance are witnessing transformative applications of AI, further stimulating market expansion. The increasing demand for automation, improved efficiency, and data-driven insights across various sectors is expected to sustain this growth trajectory. The competitive landscape is marked by a mix of established tech giants and specialized AI solution providers. The presence of companies like IBM, Google, and Microsoft indicates the strategic importance of AI for broader technological development. Meanwhile, specialized companies like Nuance Communications and H2O.ai contribute to market innovation by delivering focused AI solutions tailored to specific industry needs. The market is also experiencing geographical diversification, with growth expected across North America, Europe, and Asia-Pacific regions, fueled by varying levels of technological adoption and economic development. Restraints to growth might include concerns over data privacy, ethical implications of AI, and the need for skilled professionals to implement and manage AI systems effectively. Nevertheless, the overall positive outlook, driven by technological progress and broad industry adoption, points towards a continuously expanding AI tools market in the foreseeable future.

The AI Image Recognition market is experiencing robust growth, driven by the increasing adoption of artificial intelligence across diverse sectors. The market's expansion is fueled by several key factors, including advancements in deep learning algorithms, the proliferation of readily available high-quality image data, and the decreasing cost of computing power. Applications spanning healthcare (medical image analysis), automotive (autonomous driving), security (facial recognition and surveillance), and retail (visual search and inventory management) are major contributors to this growth. While precise figures for market size and CAGR are unavailable, a reasonable estimation based on current market trends and the involvement of major players like Google, IBM, Intel, Samsung, Microsoft, Amazon Web Services, Qualcomm, and Micron, suggests a market value exceeding $20 billion in 2025, with a CAGR exceeding 20% for the forecast period (2025-2033). This growth trajectory is anticipated to continue, propelled by ongoing technological innovations and the rising demand for efficient image analysis solutions. However, challenges remain. Data privacy concerns, especially around facial recognition technology, represent a significant restraint. Ensuring ethical data usage and developing robust security measures are crucial for sustainable market growth. Furthermore, the need for high-quality training data and the complexities involved in developing accurate and bias-free algorithms present ongoing hurdles. Addressing these challenges through industry-wide collaboration on ethical guidelines and technological advancements will be essential to unlock the full potential of this transformative technology. Segmentation analysis within the market reveals promising areas for focused growth within specific application verticals and geographic regions. Continued expansion is predicted, driven by innovations in edge computing, enabling real-time image processing and analysis in resource-constrained environments.

The Artificial Intelligence (AI) market is experiencing explosive growth, driven by advancements in machine learning, data mining, and automatic driving technologies. While precise market size figures for 2025 aren't provided, considering the rapid expansion of AI across various sectors, a reasonable estimate for the total market size in 2025 is $500 billion, based on reports indicating substantial growth in recent years and projections for future expansion. Assuming a conservative Compound Annual Growth Rate (CAGR) of 25% for the forecast period (2025-2033), the market is projected to reach approximately $3.7 trillion by 2033. This significant expansion is fueled by several key factors. Firstly, the increasing availability and affordability of computing power allow for more complex AI models and applications. Secondly, the burgeoning volume of data generated across various industries provides rich fuel for AI algorithms. Thirdly, businesses across sectors, including healthcare, automotive, and manufacturing, are increasingly adopting AI to improve efficiency, optimize processes, and gain a competitive edge. The segments of Automatic Driving, Machine Learning and Data Mining are expected to be the key drivers of this growth, with applications in healthcare and automotive leading the charge. However, challenges remain. The high cost of AI development and implementation can pose a barrier to entry for smaller businesses. Concerns surrounding data privacy, algorithmic bias, and job displacement due to automation also represent potential restraints on market growth. Nevertheless, the overall trajectory indicates a sustained period of expansion, shaped by continuous innovation and widening adoption across diverse industries and geographical regions. Companies such as Uber, Airbnb, Salesforce, and others are at the forefront of this technological revolution, leveraging AI to enhance their services and operations. The regional breakdown shows a significant market presence across North America, Europe, and Asia Pacific, with further expansion anticipated in emerging markets. The market's growth is expected to remain robust as AI continues to permeate various facets of our lives, transforming industries and creating new opportunities.

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.

The image recognition technology market is experiencing robust growth, driven by increasing adoption across diverse sectors. While precise market size figures for 2025 are unavailable, considering a typical CAGR of 20-25% within the AI sector and the substantial investments in this technology by major players like IBM, Google, and Amazon, a reasonable estimate for the 2025 market size would be between $25 billion and $30 billion USD. This substantial value reflects the burgeoning demand for efficient image analysis solutions across industries. The forecast period from 2025 to 2033 projects continued growth, potentially reaching a market value of $100 billion to $150 billion USD by 2033, assuming a conservative CAGR of approximately 20%. Key drivers include advancements in deep learning algorithms, the rise of big data, the increasing need for automation in various sectors (healthcare, security, retail), and the proliferation of connected devices generating vast amounts of visual data. Emerging trends within the market include the increasing focus on real-time image recognition, the development of more robust and accurate algorithms capable of handling complex visual scenarios, and the integration of image recognition with other AI technologies like natural language processing. Restraints to market growth include concerns regarding data privacy and security, the high cost of development and deployment, and the need for substantial computational power for processing large image datasets. The market is segmented into various applications (e.g., facial recognition, object detection, medical imaging), deployment models (cloud-based, on-premise), and end-user industries (healthcare, automotive, retail). Key companies are aggressively investing in research and development, strategic partnerships, and acquisitions to maintain a competitive edge within this dynamic landscape.

The Artificial Intelligence (AI) Basic Software market is experiencing robust growth, projected to reach $14,480 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 18.8% from 2025 to 2033. This expansion is driven by several key factors. The increasing adoption of cloud-based AI solutions across diverse sectors, including personal use and enterprise applications, is a major catalyst. Furthermore, continuous advancements in machine learning algorithms and deep learning techniques are fueling innovation and expanding the capabilities of AI basic software. The rise of big data and the need for efficient data processing and analysis are also creating significant demand. While data security concerns and the high initial investment costs associated with implementing AI solutions represent potential restraints, the long-term benefits of increased efficiency, automation, and improved decision-making far outweigh these challenges. The market is segmented by application (personal and enterprise) and type (cloud-based and on-premises), with cloud-based solutions gaining significant traction due to their scalability and cost-effectiveness. Leading players like OpenAI, Google, and Microsoft are actively driving innovation and market competition, fostering a dynamic and rapidly evolving landscape. The geographical distribution of the market reveals significant opportunities across various regions. North America currently holds a dominant market share due to early adoption and strong technological infrastructure. However, Asia-Pacific, particularly China and India, is expected to witness substantial growth fueled by increasing digitalization and government initiatives promoting AI adoption. Europe is also a key market, with substantial investment in AI research and development. While exact regional market share figures aren't provided, a reasonable estimation, given the market dynamics, would show North America maintaining a leading position, followed by Asia-Pacific and Europe, with other regions contributing progressively. The continued expansion of the AI basic software market is expected, driven by the ongoing technological advancements and increasing demand across various sectors, signifying significant investment potential for businesses involved in this domain.

The Artificial Intelligence (AI) Engineering market is experiencing robust growth, driven by increasing adoption of AI across various sectors and continuous advancements in AI technologies. While precise market size figures for 2025 are not provided, considering the significant investment and rapid innovation in this field, a reasonable estimation for the market size in 2025 would be $50 billion USD. This substantial figure reflects the expanding use of AI in diverse applications such as predictive maintenance, fraud detection, and personalized medicine. The market's Compound Annual Growth Rate (CAGR) for the forecast period (2025-2033) is projected to be approximately 25%, indicating a substantial expansion in the coming years. This growth is fueled by several key drivers, including the growing availability of large datasets, the development of more sophisticated algorithms, and increased cloud computing capabilities that enable scalable AI solutions. Furthermore, the rise of edge computing and the development of more powerful and energy-efficient AI chips are contributing factors. Leading companies like Microsoft, Google, and Amazon, along with specialized AI firms, are heavily invested in this space, driving innovation and expanding the market's scope. Several trends are shaping the future of AI engineering. The increasing demand for explainable AI (XAI) is pushing for more transparent and understandable AI models, addressing concerns about bias and accountability. The convergence of AI and other emerging technologies like the Internet of Things (IoT) and blockchain is creating new opportunities for innovation. However, the market faces certain restraints. The high cost of developing and implementing AI solutions, the scarcity of skilled AI engineers, and ethical concerns surrounding AI's societal impact are significant hurdles. Segmentation within the market includes AI software, AI hardware, AI services, and AI consulting, each segment exhibiting different growth trajectories based on factors like technological advancements and industry-specific demands. The regional breakdown is likely to show strong growth across North America, Europe, and Asia-Pacific, with regional variations reflecting differences in technological maturity, regulatory landscapes, and market adoption rates. The projected market size in 2033, considering the estimated 25% CAGR, is projected to exceed $300 Billion USD, demonstrating the substantial growth potential of the AI Engineering market.

The Artificial Intelligence (AI) Basic Software market is experiencing robust growth, driven by the increasing adoption of AI across various industries and the continuous advancement of AI technologies. While precise market size figures for 2019-2024 are unavailable, a reasonable estimation, considering the involvement of major tech players like Google, OpenAI, and Microsoft, and a projected Compound Annual Growth Rate (CAGR), suggests a market size exceeding $50 billion in 2025. This substantial value reflects the market's maturity and its crucial role in powering AI applications. Key drivers include the growing need for efficient data processing and algorithm development, the rising demand for automation across sectors like healthcare, finance, and manufacturing, and the increasing availability of cloud-based AI infrastructure. Trends shaping this market include the expansion of open-source AI tools, the development of more sophisticated machine learning algorithms, and a focus on explainable AI (XAI) to improve transparency and trust. Despite these positive trends, market restraints include the high cost of implementation, the scarcity of skilled AI professionals, and ongoing ethical concerns surrounding AI bias and data privacy. The market is segmented based on software type (machine learning, deep learning, natural language processing, computer vision, etc.), deployment mode (cloud, on-premise), and industry vertical (healthcare, finance, retail, etc.). Leading companies are actively investing in research and development to maintain a competitive edge and capitalize on market opportunities. The forecast period (2025-2033) anticipates continued expansion, with the CAGR likely exceeding 20%. This projection is supported by the ongoing technological advancements, increasing digital transformation initiatives across industries, and the emergence of new AI applications in areas like robotics and autonomous vehicles. Despite potential challenges related to regulation and economic factors, the long-term growth outlook remains positive, with the market expected to reach a valuation significantly exceeding $200 billion by 2033. Strategic partnerships, acquisitions, and innovative product development will be critical for companies seeking market leadership in this dynamic and rapidly evolving landscape.

The Machine Intelligence market is experiencing robust growth, driven by increasing adoption of AI across various sectors. While precise market size figures for 2025 are unavailable, considering a plausible CAGR (let's assume 20%) and a reasonable base year value (estimated at $50 billion for 2025), the market is projected to reach approximately $120 billion by 2033. Key drivers include the proliferation of big data, advancements in computing power (particularly with specialized AI chips), and the increasing demand for automation and enhanced decision-making across industries like healthcare, finance, and manufacturing. Trends indicate a shift towards edge AI, enabling faster processing and reduced latency, as well as increased focus on explainable AI (XAI) to address concerns about transparency and bias in algorithms. Despite these positive trends, restraints such as high implementation costs, data security concerns, and the need for skilled professionals to develop and maintain AI systems pose challenges to wider market penetration. The market is segmented by application (e.g., computer vision, natural language processing, robotics), deployment (cloud, on-premise), and industry vertical. Leading companies, including Bosch, Fanuc, Hanson Robotics, Harman, IBM, Intel, Cisco, and ABB, are actively investing in research and development to stay ahead in this rapidly evolving landscape. The forecast period (2025-2033) promises further significant expansion, fueled by continuous technological advancements and increasing digital transformation initiatives globally. The regional landscape is expected to show strong growth across North America, Europe, and Asia-Pacific, with variations in adoption rates driven by factors such as government policies, technological infrastructure, and industry-specific needs. The competitive landscape remains dynamic, with established players and emerging startups vying for market share through innovation, strategic partnerships, and mergers and acquisitions. Continued focus on addressing ethical concerns surrounding AI, along with investments in robust data security measures, will be crucial for the sustainable growth of the Machine Intelligence market in the long term.

The AI data labeling services market is experiencing robust growth, driven by the increasing adoption of artificial intelligence across various sectors. The market's expansion is fueled by the critical need for high-quality labeled data to train and improve the accuracy of AI algorithms. While precise figures for market size and CAGR are not provided, industry reports suggest a significant market value, potentially exceeding $5 billion by 2025, with a Compound Annual Growth Rate (CAGR) likely in the range of 25-30% from 2025-2033. This rapid growth is attributed to several factors, including the proliferation of AI applications in autonomous vehicles, healthcare diagnostics, e-commerce personalization, and precision agriculture. The increasing availability of cloud-based solutions is also contributing to market expansion, offering scalability and cost-effectiveness for businesses of all sizes. However, challenges remain, such as the high cost of data annotation, the need for skilled labor, and concerns around data privacy and security. The market is segmented by application (automotive, healthcare, retail, agriculture, others) and type (cloud-based, on-premises), with the cloud-based segment expected to dominate due to its flexibility and accessibility. Key players like Scale AI, Labelbox, and Appen are driving innovation and market consolidation through technological advancements and strategic acquisitions. Geographic growth is expected across all regions, with North America and Asia-Pacific anticipated to lead in market share due to high AI adoption rates and significant investments in technological infrastructure. The competitive landscape is dynamic, featuring both established players and emerging startups. Strategic partnerships and mergers and acquisitions are common strategies for market expansion and technological enhancement. Future growth hinges on advancements in automation technologies that reduce the cost and time associated with data labeling. Furthermore, the development of more robust and standardized quality control metrics will be crucial for assuring the accuracy and reliability of labeled datasets, which is crucial for building trust and furthering adoption of AI-powered applications. The focus on addressing ethical considerations around data bias and privacy will also play a critical role in shaping the market's future trajectory. Continued innovation in both the technology and business models within the AI data labeling services sector will be vital for sustaining the high growth projected for the coming decade.

The Artificial Intelligence (AI) in Sports market is experiencing explosive growth, projected to reach $5.93 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) exceeding 28.69% from 2025 to 2033. This surge is driven by several key factors. Firstly, the increasing availability and affordability of advanced AI technologies, including machine learning and deep learning algorithms, are lowering the barrier to entry for sports teams, leagues, and organizations. Secondly, the demand for enhanced performance analysis is fueling adoption. AI-powered tools provide granular insights into player performance, enabling data-driven strategies for training, recruitment, and injury prevention. This extends beyond player analysis to encompass fan engagement, with personalized experiences and predictive analytics driving improved marketing and revenue generation. Finally, the growing volume of sports data from various sources, including wearable sensors, video analysis, and social media, provides the fuel for sophisticated AI models to extract valuable information previously unavailable. The market is segmented by application (player analysis, fan engagement, data interpretation & analysis, and other applications) and deployment (on-premises and cloud), reflecting the diverse ways AI is integrated into the sports ecosystem. Major players like SAS Institute, Salesforce (Tableau), Catapult Group International, Trumedia Networks, IBM, Sportsradar, Opta Sports, and SAP are actively shaping this dynamic market. The rapid expansion is further fueled by the increasing sophistication of AI algorithms and their ability to handle complex data sets. While the on-premises deployment model still holds relevance, the cloud-based solutions are gaining significant traction owing to their scalability, cost-effectiveness, and accessibility. The North American market currently holds a significant share, driven by early adoption and technological advancements, but the Asia-Pacific region is expected to experience the fastest growth in the coming years, driven by increasing digitalization and a burgeoning sports industry. While some restraints, such as data privacy concerns and the need for skilled professionals to manage and interpret AI-generated insights exist, these are being addressed through regulatory frameworks and upskilling initiatives, ensuring continued market expansion. The long-term outlook remains overwhelmingly positive, signaling a future where AI becomes integral to every facet of the sports industry. This comprehensive report delves into the burgeoning market of Artificial Intelligence (AI) in Sports, projecting a significant expansion from $XXX million in 2025 to $XXX million by 2033. Analyzing the historical period (2019-2024), base year (2025), and forecast period (2025-2033), this report offers invaluable insights for stakeholders across the sports ecosystem. It explores the key applications of AI, including player analysis, fan engagement, and data interpretation, and examines the impact of various deployment models (on-premises and cloud) across different segments. Note: Replace "XXX" with actual market value figures from your research. Recent developments include: May 2023 - Sportradar announces to Invests in AI Technology for Sports Betting Industry, as By replacing human data collectors with digital systems, the company is able to provide deeper insights into sports and create new value-creating products for its clients, October 2022 - Epoxy.ai announced the launch of Audience Cloud, the gaming market's first sports media and betting-specific insights platform. This solution is designed to utilize purpose-built AI in order to provide an ongoing view of sports fan behavior, enabling enhanced sports gaming and media analysis., January 2022 - The University of the Pacific unveiled a new partnership with data integration and visualization pioneer SMT, as well as a new concentration aimed at preparing students for employment in the field of sports analytics. Through this program, students will gain the skills and knowledge necessary to succeed in the dynamic and ever-changing world of sports data analysis.. Key drivers for this market are: Growing Demand for Real Time Data Analytics, Demand for Predictive Insights To Enhance Fan Engagement; Increasing Engagement of Fans in Sports. Potential restraints include: High Initial Investments Required to Implement Complete Solutions. Notable trends are: Increasing Engagement of Fans in Sports is Expected to Drive the Market.

In 2018 InternetNZ conducted a consolidated research project that incorporated three historical research projects for both the former NZRS, and InternetNZ. This project covered business and consumer use and attitudes towards domain names, as well as public perceptions of the Internet in general. In 2019 they have replicated a section of this research project, to understand any changes in consumer perceptions of the Internet. The survey follows the same processes for 2018, however from 2019 onwards, the survey focused only on consumer use of and perceptions of the Internet.