Recent developments include: December 2023: TELUS International, a digital customer experience innovator in AI and content moderation, launched Experts Engine, a fully managed, technology-driven, on-demand expert acquisition solution for generative AI models. It programmatically brings together human expertise and Gen AI tasks, such as data collection, data generation, annotation, and validation, to build high-quality training sets for the most challenging master models, including the Large Language Model (LLM)., September 2023: Cogito Tech, a player in data labeling for AI development, launched an appeal to AI vendors globally by introducing a “Nutrition Facts” style model for an AI training dataset known as DataSum. The company has been actively encouraging a more Ethical approach to AI, ML, and employment practices., June 2023: Sama, a provider of data annotation solutions that power AI models, launched Platform 2.0, a new computer vision platform designed to reduce the risk of ML algorithm failure in AI training models., May 2023: Appen Limited, a player in AI lifecycle data, announced a partnership with Reka AI, an emerging AI company making its way from stealth. This partnership aims to combine Appen's data services with Reka's proprietary multimodal language models., March 2022: Appen Limited invested in Mindtech, a synthetic data company focusing on the development of training data for AI computer vision models. This investment is part of Appen's strategy to invest capital in product-led businesses generating new and emerging sources of training data for supporting the AI lifecycle.. Key drivers for this market are: Rapid Adoption of AI Technologies for Training Datasets to Aid Market Growth. Potential restraints include: Lack of Skilled AI Professionals and Data Privacy Concerns to Hinder Market Expansion. Notable trends are: Rising Usage of Synthetic Data for Enhancing Authentication to Propel Market Growth.

In 2022, the global total corporate investment in artificial intelligence (AI) reached almost ** billion U.S. dollars, a slight decrease from the previous year. In 2018, the yearly investment in AI saw a slight downturn, but that was only temporary. Private investments account for a bulk of total AI corporate investment. AI investment has increased more than ******* since 2016, a staggering growth in any market. It is a testament to the importance of the development of AI around the world. What is Artificial Intelligence (AI)? Artificial intelligence, once the subject of people’s imaginations and the main plot of science fiction movies for decades, is no longer a piece of fiction, but rather commonplace in people’s daily lives whether they realize it or not. AI refers to the ability of a computer or machine to imitate the capacities of the human brain, which often learns from previous experiences to understand and respond to language, decisions, and problems. These AI capabilities, such as computer vision and conversational interfaces, have become embedded throughout various industries’ standard business processes. AI investment and startups The global AI market, valued at ***** billion U.S. dollars as of 2023, continues to grow driven by the influx of investments it receives. This is a rapidly growing market, looking to expand from billions to trillions of U.S. dollars in market size in the coming years. From 2020 to 2022, investment in startups globally, and in particular AI startups, increased by **** billion U.S. dollars, nearly double its previous investments, with much of it coming from private capital from U.S. companies. The most recent top-funded AI businesses are all machine learning and chatbot companies, focusing on human interface with machines.

During a 2022 survey conducted in the United States, it was found that 18 percent of respondents thought that artificial intelligence will lead to there being many fewer jobs. By contrast, 25 percent of respondents aged between 30 and 44 years stated that AI will create many more jobs.

Artificial intelligence

Artificial intelligence (AI) is the ability of a computer or machine to mimic the competencies of the human mind, learning from previous experiences to understand and respond to language, decisions, and problems. Particularly, a large amount of data is often used to train AI into developing algorithms and skills. The AI ecosystem consists of machine learning (ML), robotics, artificial neural networks, and natural language processing (NLP). Nowadays, tech and telecom, financial services, healthcare, and pharmaceutical industries are prominent for AI adoption in companies.

AI companies and startups

More and more companies and startups are engaging in the artificial intelligence market, which is forecast to grow rapidly in the coming years. Examples of big tech firms are IBM, Microsoft, Baidu, and Tencent, with the last owning the highest number of AI and ML patent families, amounting to over nine thousand. Moreover, driven by the excitement for this new technology and by the large investments in it, the number of startups involved in the industry around the world has grown in recent years. For instance, in the United States, the New York company UiPath was the top-funded AI startup.

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Cloud Artificial Intelligence (AI) Market Size 2024-2028

The cloud artificial intelligence (ai) market size is forecast to increase by USD 12.61 billion, at a CAGR of 24.1% between 2023 and 2028.

The market is experiencing significant growth, driven by the emergence of technologically advanced devices and the increasing adoption of 5G and mobile penetration. These advancements enable faster and more efficient data processing, leading to increased demand for cloud-based AI solutions. However, the market also faces challenges from open-source platforms, which offer free alternatives to proprietary AI offerings. Companies must navigate this competitive landscape by focusing on providing value-added services and maintaining a strong competitive edge through innovation and differentiation. To capitalize on market opportunities, organizations should explore applications in sectors such as healthcare, finance, and manufacturing, where AI can drive operational efficiency, enhance customer experiences, and generate new revenue streams. Effective strategic planning and a strong focus on data security will be crucial for businesses seeking to succeed in this dynamic and evolving market.

What will be the Size of the Cloud Artificial Intelligence (AI) Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2018-2022 and forecasts 2024-2028 - in the full report.
Request Free SampleThe market continues to evolve, driven by advancements in machine learning (ML), computer vision, and natural language processing. Bias mitigation and responsible AI are increasingly prioritized, with knowledge graphs and explainable AI (XAI) playing crucial roles in ensuring transparency and trust. Agile development and AI ethics are integral to creating ethical and unbiased AI systems. ML models are being applied across various sectors, from fraud detection and sales forecasting to speech recognition and image recognition. Data security and privacy remain paramount, with cloud computing and edge computing solutions offering secure alternatives. Deep learning (DL) and reinforcement learning are advancing rapidly, enabling more sophisticated AI applications. Semantic reasoning and predictive analytics are transforming decision making, while AI-powered chatbots and virtual assistants enhance customer service. Data labeling and model training are essential components of AI development, with API integration streamlining deployment and model training. Risk management and predictive analytics are critical for businesses seeking to mitigate potential threats and optimize operations. The ongoing unfolding of market activities reveals a dynamic landscape, with AI regulations and governance emerging as key considerations. Sentiment analysis and text analytics offer valuable insights into customer behavior and preferences. In the ever-evolving AI ecosystem, continuous innovation and adaptation are essential. The integration of various AI technologies and applications will shape the future of business and society.

How is this Cloud Artificial Intelligence (AI) Industry segmented?

The cloud artificial intelligence (ai) industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments. ComponentSoftwareServicesGeographyNorth AmericaUSEuropeGermanyUKAPACChinaJapanRest of World (ROW)

By Component Insights

The software segment is estimated to witness significant growth during the forecast period.Artificial Intelligence (AI) software development is a significant area of innovation in the business world, with applications ranging from automating operations to personalizing service delivery and generating insights. AI technologies, such as machine learning (ML), deep learning (DL), computer vision, speech recognition, and natural language processing, are transforming industries. Responsible AI practices, including bias mitigation and explainable AI (XAI), are crucial for building trust and ensuring fairness in AI systems. Agile development methodologies facilitate the integration of AI capabilities into existing software. Data security and privacy are paramount in AI implementations. Cloud computing and edge computing provide flexible solutions for storing and processing sensitive data. AI regulations, such as those related to data privacy and security, are shaping the market. AI ethics are also a critical consideration, with transparency and accountability essential for building trust in AI systems. AI is revolutionizing various industries, from healthcare to finance and marketing. In healthcare, AI is used for predictive analytics, sales forecasting, and fraud detection, improving patient outcomes and operational efficiency. In finance, AI is used for risk management, text analytics, and sent

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.

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Artificial Intelligence (AI) Infrastructure Market Size 2024-2028

The artificial intelligence (ai) infrastructure market size is forecast to increase by USD 22.07 billion at a CAGR of 20.6% between 2023 and 2028.

The market is experiencing significant growth, driven by the emerging application of machine learning (ML) in various industries. The increasing availability of cloud-based AI applications is also fueling market expansion. However, privacy concerns associated with AI deployment pose a challenge to market growth. As ML algorithms collect and process vast amounts of data, ensuring data security and privacy becomes crucial. Despite these challenges, the market is expected to continue its growth trajectory, driven by advancements in AI technologies and their increasing adoption across sectors. The implementation of robust data security measures and regulatory frameworks will be essential to address privacy concerns and foster market growth.

What will be the Size of the Artificial Intelligence (AI) Infrastructure Market During the Forecast Period?

Request Free SampleThe market encompasses the hardware and software solutions required to build, train, deploy, and scale AI models. Key market drivers include the increasing demand for machine learning workloads, data processing for various applications such as image recognition and natural language processing, and the need for computational power and networking capabilities to handle large data sets. The market is characterized by continuous improvement and competitive advantage through the use of GPUs and TPUs for AI algorithms, as well as cloud computing solutions offering high-bandwidth and scalability. Security is a critical consideration, with data handling and storage solutions implementing robust encryption and access control measures.AI infrastructure is utilized across diverse industries, including healthcare and finance, to drive innovation and precision medicine, and to enhance operational efficiency and productivity. Data processing frameworks play a pivotal role in facilitating the deployment and scaling of AI models, enabling organizations to maintain flexibility and adapt to evolving business needs.

How is this Artificial Intelligence (AI) Infrastructure Industry segmented and which is the largest segment?

The artificial intelligence (ai) infrastructure industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments. TypeProcessorStorageMemoryGeographyNorth AmericaUSEuropeGermanyUKAPACChinaJapanSouth AmericaMiddle East and Africa

By Type Insights

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

The market is experiencing significant growth due to the increasing adoption of AI and machine learning (ML) technologies across various industries. The market encompasses hardware, software, machine learning workloads, data processing, model training, deployment, scalability, flexibility, security, and computational power. Hardware solutions include GPUs and TPUs, while software solutions consist of data processing frameworks, image recognition, natural language processing, and AI algorithms. Industries such as healthcare, finance, and precision medicine are leveraging AI for decision-making, autonomous systems, and real-time data processing. AI infrastructure requires high computational demands, and cloud computing provides scalable storage solutions and cost-efficiency. Networking solutions offer high-bandwidth and low-latency for data transfer, ensuring data residency and data security.Data architecture includes databases, data warehouses, data lakes, in-memory databases, and caching mechanisms. Data preparation and resource utilization are crucial for model inference, data reconciliation, data classification, data visualization, and model validation. AI model production and data preprocessing are essential for continuous improvement and competitive advantage. AI accelerators, AI workflows, and data ingestion further enhance the capabilities of AI infrastructure. The market's growth is driven by the increasing need for cost-efficiency, integration, and modular systems.

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The Processor segment was valued at USD 3.76 billion in 2018 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 49% 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.

For more insights on the market share of various regions, Req

During a 2022 survey conducted in the United States, it was found that 26 percent of respondents thought that artificial intelligence will not make their lives either easier or harder. Moreover, 31 percent of respondents aged between 30 and 44 years stated that AI will make their lives much easier.

Artificial intelligence

Artificial intelligence (AI) is the ability of a computer or machine to mimic the competencies of the human mind, learning from previous experiences to understand and respond to language, decisions, and problems. Particularly, a large amount of data is often used to train AI into developing algorithms and skills. The AI ecosystem consists of machine learning (ML), robotics, artificial neural networks, and natural language processing (NLP). Nowadays, tech and telecom, financial services, healthcare, and pharmaceutical industries are prominent for AI adoption in companies.

AI companies and startups

More and more companies and startups are engaging in the artificial intelligence market, which is forecast to grow rapidly in the coming years. Examples of big tech firms are IBM, Microsoft, Baidu, and Tencent, with the last owning the highest number of AI and ML patent families, amounting to over nine thousand. Moreover, driven by the excitement for this new technology and by the large investments in it, the number of startups involved in the industry around the world has grown in recent years. For instance, in the United States, the New York company UiPath was the top-funded AI startup.

The Artificial Intelligence Software market is valued at USD 80.26 Billion in 2022 and will be USD 612.36 Billion by 2030 with a CAGR of 29.06% during the forecast period. Factors Affecting the Artificial Intelligence Software Market

Increasing demand for IoT solutions boosts Artificial Intelligence Software market growth:

Software that uses artificial intelligence is increasingly being used in industries from healthcare to defense, as it is one of the most effective ways to eliminate the need for human labor. To compete in the artificial intelligence software market, other well-known companies are also releasing new AI software at the same time. For instance, Amazon announced the release of a new artificial intelligence tool called “Create with Alexa '' in November 2022 to produce stories for children. This brand-new artificial intelligence program creates briefings that include animation, music, and pictures.

Increasing demand for AI in the healthcare sector

The health industry's application of artificial intelligence software improved the standard of living for workers. In the coming years, the market for artificial intelligence software will probably be driven by rising demand from the healthcare industry. Technology advancements also offer profitable chances for market expansion.

Restraint for Artificial Intelligence Software Market

The difficulty associated adoption of AI tools can hamper market growth:

The market's limiting factors include the absence of Al talent in emerging nations, difficulties with the all-at-once adoption of Al tools, and the black box effect. To combat these factors and end the "black box effect," businesses have improved their solutions with more moral and explicable Al models. The black box effect causes the Al algorithms to occasionally provide results that are difficult to verify. These algorithms' results could be biased in a subtle way that is hard to detect. Therefore, the results are not adequately explained. As a result, consumers frequently embrace Al tools without feeling secure or trusted

Impact of the COVID-19 Pandemic on the Artificial Intelligence Software Market:

The pandemic crisis altered the way businesses functioned and made them more complex. Businesses moved their business operations to the cloud to adapt pt this development., machine learning, and other cutting-edge technologies saw a spike in use as a result. One of the first industries to use this technology, which increased the precision and effectiveness of diagnoses, treatments, and predictions, was the healthcare industry. For instance, according to the study report from January 2022, researchers at Indiana University and the Regenstrief Institute discovered that machine learning (ML) models could aid in public health decision-making during the pandemic. What is Artificial Intelligence Software?

A mainframe program called artificial intelligence (Al) software imitates human behavior by gaining knowledge from various insights and data patterns. Artificial intelligence platforms, chatbots, deep learning software, and machine learning software are a few examples of different types of Al software. Additional features of Al software include voice and speech recognition, machine learning, and virtual assistants. To automate company procedures and organize data for better data insights, various sorts of enterprises utilize artificial intelligence software which is machine learning incorporated. In addition, the market for Al software is anticipated to increase exponentially in the future due to rising technological advancements.

According to Cognitive Market Research, the global AI in Education Market size is USD 3.2 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 40.6% from 2024 to 2031. Market Dynamics of AI in Education Market

Key Drivers for AI in Education Market

Increasing Number of Smartphone Users - The growing number of smartphone users is predicted to drive the expansion of artificial intelligence (Al) in the education business in the future. Smartphone users use a cellular phone that includes a computer and other functions not traditionally associated with phones, such as a web browser, an operating system, and the capacity to run software applications. Smartphone users benefit from personalized and flexible learning experiences that incorporate AI technology into educational applications and platforms. In addition, smartphones enable real-time interaction and engagement, allowing students to communicate seamlessly with Al-powered virtual assistants (tutors), and their widespread use broadens the reach and impact of Al in education, making high-quality and personalized learning more accessible to a larger population. According to the Ericsson Mobility Report 2022 from Ericsson, a Swedish networking and telecoms business, smartphone subscriptions were 6,420 million in 2022 and are expected to rise to 7,740 million by 2028. Increasing Adoption of Online Education

Key Restraints for AI in Education Market

Data Safety and Security Issues Lack of awareness Introduction of the AI in Education Market

AI-enabled products and services in the education sector serve a number of functions, such as material delivery, skill evaluation, student integration, and adaptive instructional platforms, to improve learning for both students and educators. Artificial intelligence (AI) technologies such as deep learning, machine learning, and natural language processing (NLP) are increasingly being incorporated into training and education software to improve performance and learning experiences. Artificial intelligence (AI) technologies are being integrated into current educational paradigms to improve educational systems for better information transmission and evaluation. The introduction of AI into the education industry has greatly helped educational institutions by lowering costs, increasing administrative effectiveness, and improving IT security on campuses by detecting risks sooner and taking immediate action. The demand for Artificial Intelligence (AI) in education is being driven by factors such as increased business and public sector investments in AI and EdTech, as well as increased edutainment penetration. Additionally, technological advancements are increasing global need for AI in education. However, privacy, ethical, and access constraints, as well as equity concerns, impede market growth to some extent.

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 rapid expansion is fueled by several key drivers. Firstly, the increasing availability of high-volume, high-velocity data from various sources, including wearable sensors, video analytics, and social media, provides rich fodder for AI algorithms. Secondly, advancements in AI technologies, particularly in machine learning and deep learning, enable more accurate predictions, personalized fan experiences, and optimized player performance analysis. Thirdly, the growing adoption of cloud-based solutions facilitates scalability, accessibility, and cost-effectiveness for sports organizations of all sizes. Finally, the competitive landscape is pushing teams and leagues to leverage AI for a decisive edge, driving further market expansion. The market segmentation reveals significant opportunities across applications. Player analysis, encompassing injury prediction, performance optimization, and talent scouting, represents a substantial portion of the market. Fan engagement, leveraging AI-powered personalization and interactive experiences, is another rapidly growing segment. Data interpretation and analysis tools are crucial for extracting valuable insights from the vast amounts of data generated in modern sports. While on-premises deployment continues to be relevant, cloud-based solutions are gaining significant traction due to their flexibility and scalability. Key players like SAS Institute, Opta Sports, Sportsradar, Catapult Group, IBM, SAP, and Salesforce (Tableau) are actively shaping the market through innovative solutions and strategic partnerships. Geographical growth will likely see strong performance in North America and Europe initially, followed by increasing adoption in the Asia-Pacific region as technological infrastructure and digital adoption mature. The continued refinement of AI algorithms, coupled with increasing investment in sports technology, positions the AI in sports market for sustained and substantial future growth. 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: Growing Demand for Real Time Data Analytics, Demand for Predictive Insights To Enhance Fan Engagement; Increasing Engagement of Fans in Sports. Notable trends are: Increasing Engagement of Fans in Sports is Expected to Drive the Market.

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AI Market In Media And Entertainment Industry Size 2024-2028

The ai market in media and entertainment industry size is forecast to increase by USD 30.73 billion, at a CAGR of 26.4% between 2023 and 2028.

The AI market in the media and entertainment industry is witnessing significant growth, driven by the increasing utilization of multimodal AI to enhance consumer experiences. This technology allows AI systems to process and analyze various forms of data, including text, images, and speech, enabling more personalized and engaging content. Another key trend is the adoption of blockchain technology to securely store and share data for AI model training. This ensures data privacy and security, addressing a major concern for media and entertainment companies.
However, the reliance on external sources of data for training AI models poses a challenge. Ensuring data accuracy, ownership, and ethical usage is crucial to mitigate potential risks and maintain consumer trust. Companies in this industry must navigate these dynamics to effectively capitalize on the opportunities presented by AI and provide innovative, personalized experiences for their audiences.

What will be the Size of the AI Market In Media And Entertainment Industry during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2018-2022 and forecasts 2024-2028 - in the full report.
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The AI market in media and entertainment continues to evolve, with dynamic applications across various sectors. In game development, AI training datasets enhance player experiences through realistic non-playable characters and intelligent enemy behavior. Recommendation engines personalize content for streaming services, while cybersecurity measures protect against potential threats. AI-powered video editing streamlines production workflows, enabling real-time rendering and automated dubbing. Deep learning algorithms enable sentiment analysis, allowing content distributors to tailor recommendations based on viewer preferences. Machine learning models optimize programmatic advertising, ensuring targeted delivery to specific audiences. Data analytics and licensing agreements facilitate revenue generation in animation studios, while bias detection ensures ethical AI usage.

Interactive advertising engages viewers through object detection and metadata tagging, enhancing user experience. Project management software streamlines workflows, from pre-production to post-production. Natural language processing and CGI rendering bring AI-powered content creation tools to life, while cloud rendering and monetization strategies enable scalability and profitability. AI ethics, explainable AI, and facial recognition are crucial considerations in this rapidly evolving landscape. Virtual production and AI-powered post-production workflows revolutionize television production, while social media platforms leverage AI for content moderation and personalized content delivery. Big data processing and model interpretability enable more efficient and effective AI implementation. In the ever-changing media and entertainment industry, AI continues to unfold new patterns and applications, driving innovation and growth.

How is this AI In Media And Entertainment Industry Industry segmented?

The ai in media and entertainment industry industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Technology

  Machine learning
  Computer vision
  Speech recognition


End-user

  Media companies
  Gaming industry
  Advertising agencies
  Film production houses


Offering

  Software
  Services


Application

  Media
  Entertainment


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  Middle East and Africa

    Egypt
    KSA
    Oman
    UAE


  APAC

    China
    India
    Japan


  South America

    Argentina
    Brazil


  Rest of World (ROW)

By Technology Insights

The machine learning segment is estimated to witness significant growth during the forecast period.

The media and entertainment industry has been significantly transformed by the integration of artificial intelligence (AI) technologies. Machine learning (ML), in particular, has been instrumental in enhancing video data management and analytics. For instance, Wasabi Technologies' latest object storage solutions employ AI and ML capabilities for automated tagging and metadata indexing of video content. These advancements enable seamless storage of video content in S3-compatible object storage systems, improving content accessibility and searchability. AI is also revolutionizing game development with the use of deep learning algorithms for creating more

As of December 2022, Baidu was the largest owner of active machine learning and artificial intelligence (AI) patent families worldwide, with ****** active patent families owned. In 2022, the company had claimed the leading position from Tencent now ranked second with ****** active patent families owned. IBM ranked fifth with just under ***** active patent families. The statistic is based on data provided by PatentSight.

The global Big Data Analytics in Defense market is experiencing robust growth, projected to maintain a Compound Annual Growth Rate (CAGR) exceeding 13% from 2025 to 2033. This expansion is fueled by several key factors. The increasing reliance on advanced technologies for enhanced situational awareness and improved decision-making within military operations is a primary driver. The need to analyze vast quantities of data from diverse sources, including sensor networks, satellite imagery, and social media, is pushing the adoption of sophisticated big data analytics solutions. Furthermore, the growing demand for predictive intelligence and improved cybersecurity within defense organizations is further accelerating market growth. Technological advancements in artificial intelligence (AI), machine learning (ML), and cloud computing are continuously enhancing the capabilities of big data analytics platforms, making them more efficient and effective. Segmentation reveals a strong demand across all platforms (Army, Navy, Air Force), with hardware, software, and services all contributing significantly to the overall market value. While the market faces some restraints, such as data security concerns and the high cost of implementation, these are being mitigated by ongoing innovation and government investment in defense modernization initiatives. The North American market currently holds a substantial share, driven by significant defense spending and the presence of major technology players. However, the Asia-Pacific region is poised for rapid expansion due to increasing military modernization efforts in countries like China and India. The competitive landscape is dominated by established defense contractors and technology giants, indicating a robust ecosystem fostering further innovation and market penetration. The market's trajectory suggests continued high growth over the forecast period, driven by the increasing strategic importance of big data analytics in national security and defense operations. The market's future is characterized by a strong focus on developing AI-powered analytics solutions for real-time threat detection, predictive maintenance of defense equipment, and optimized resource allocation. Furthermore, the integration of big data analytics with other emerging technologies, such as the Internet of Things (IoT) and blockchain, will further expand its capabilities and applications. The increasing emphasis on cybersecurity and data privacy is likely to drive demand for robust and secure data analytics solutions. Collaborative partnerships between defense organizations and technology providers are crucial for developing and deploying effective big data analytics solutions. Government initiatives to encourage innovation and investment in the defense technology sector will play a significant role in shaping the market's future trajectory. The continued growth in defense budgets globally will further support the market's expansion, making it a highly attractive investment opportunity for both established players and emerging technology companies. Recent developments include: September 2022: The United States Air Force signed a contract worth USD 1.25 million with ZeroEyto procure an AI gun detection solution for the service's unmanned aerial vehicles (UAVs) at the Dover Air Force Base, Delaware. ZeroEyes' technology will enable drones to detect handheld weapons for base protection., July 2022: The Indian Ministry of Defense launched 75 newly developed artificial intelligence (AI) products and technologies during the first-ever 'AI in Defense symposium and exhibition in New Delhi. These include autonomous systems, AI platform automation, command, control, communication, computer (C4), blockchain-based automation, intelligence, surveillance & reconnaissance (ISR), intelligent monitoring systems, cyber security, and others.. Notable trends are: Software Segment Will Showcase Remarkable Growth During the Forecast Period.

The European AI in defense market, valued at approximately €1.5 billion in 2025, is projected to experience robust growth, driven by escalating geopolitical tensions and the increasing need for advanced military capabilities. A Compound Annual Growth Rate (CAGR) of 8% from 2025 to 2033 indicates a significant expansion, reaching an estimated market size of over €3 billion by 2033. Key drivers include the adoption of AI-powered systems for enhanced situational awareness, improved decision-making, and autonomous weapon systems. The market is segmented across hardware, software, and platforms (land, air, and naval), with applications spanning cybersecurity, battlefield healthcare, and warfare platform optimization. Leading companies like BAE Systems, Lockheed Martin, and Thales are heavily investing in R&D, fostering innovation and competition. The UK, Germany, and France are expected to be the largest national markets within Europe, due to their robust defense budgets and advanced technological infrastructure. However, challenges remain, including data privacy concerns, ethical implications of autonomous weapons, and the need for robust cybersecurity measures to protect AI systems from adversarial attacks. The substantial growth is fueled by several trends. Governments across Europe are prioritizing the modernization of their defense forces, incorporating AI technologies to gain a competitive advantage. The increasing availability of large datasets suitable for AI training, coupled with advancements in deep learning and machine learning algorithms, are further accelerating market expansion. Furthermore, the rising demand for AI-powered solutions for predictive maintenance, logistics optimization, and intelligence gathering is significantly impacting market growth. Despite these positive factors, restraints include the high cost of AI development and implementation, along with concerns about potential job displacement due to automation in the defense sector. Nevertheless, the long-term outlook for the European AI in defense market remains overwhelmingly positive, with significant opportunities for growth and innovation. Recent developments include: Jul 2022: The Defense Ministry of France announced that it had authorized the go-ahead for the final phase of new artificial intelligence and big data processing capability, which is being developed by the company Athea, a joint venture between Thales and Atos. The main aim of such a project will be to provide France with secure and sovereign artificial intelligence and big data platforms that can analyze massive data generated by military equipment as well as other sensors., May 2022: Palantir Technologies Inc., a data analytics company, announced that it successfully won a USD 12.5 million contract with the Defense Ministry of the United Kingdom. Plantir Technologies Inc., under the contract, will be providing support for its Foundry platform, which will enable the users to cut down on their costs by work automation and reduction in the time required to process the data.. Notable trends are: Increasing Investments In Artificial Intelligence Will Drive The Market During The Forecast Period.

The AI-as-a-Service (AIaaS) market is experiencing explosive growth, projected to reach $15.09 billion in 2025 and exhibiting a remarkable Compound Annual Growth Rate (CAGR) of 36.78%. This rapid expansion is driven by several key factors. Firstly, the increasing accessibility and affordability of AI technologies through cloud-based platforms are lowering the barrier to entry for businesses of all sizes. Secondly, the growing demand for data-driven insights and automation across diverse industries, including BFSI (Banking, Financial Services, and Insurance), retail, healthcare, and manufacturing, is fueling the adoption of AIaaS solutions. Furthermore, the continuous advancements in AI algorithms and machine learning capabilities are enhancing the efficiency and effectiveness of AIaaS offerings, leading to greater business value. Finally, the rise of hybrid cloud deployments provides flexibility and scalability, making AIaaS a compelling option for organizations with varying IT infrastructure needs. Looking ahead, the AIaaS market is expected to maintain its robust growth trajectory throughout the forecast period (2025-2033). The continued development of specialized AIaaS solutions catering to specific industry needs will further drive market expansion. Large enterprises will remain a significant segment, driven by their need for sophisticated AI capabilities to optimize operations and gain a competitive edge. However, the growth of AIaaS adoption among small and medium-sized enterprises (SMEs) will also contribute significantly to overall market growth, as these businesses increasingly recognize the potential of AI to improve productivity and efficiency. While challenges remain, such as data security and privacy concerns, the overall market outlook for AIaaS remains exceptionally positive, promising substantial growth and transformation across various sectors. This report provides a comprehensive analysis of the AI as a Service (AIaaS) market, projecting substantial growth from $XXX million in 2025 to $XXX million by 2033. The study covers the historical period (2019-2024), base year (2025), and forecast period (2025-2033), offering invaluable insights for businesses navigating this rapidly evolving landscape. This detailed market analysis incorporates crucial data points and industry trends, making it an essential resource for investors, entrepreneurs, and market strategists. Recent developments include: September 2022: The AI4HealthyCities Health Equity Network was established by the Novartis Foundation, Microsoft AI for Health, and the New York University (NYU) School of Global Public Health as a joint endeavor to employ data analytics and artificial intelligence (AI) to address heart health inequities., June 2022: Wipro and the media giant Eros Investments established a strategic relationship to scale a global machine learning and artificial intelligence-based content localization solution. For international media companies and over-the-top (OTT) streaming platforms, the technology will automate the labor-intensive process of subtitling and dubbing with accuracy close to that of a human.. Key drivers for this market are: Increasing Demand for Predictive and Analytics Solutions, Rising Demand for Enhancing Consumer Experience. Potential restraints include: Increasing Security and Privacy Concerns Among Enterprises. Notable trends are: Increasing Demand for Predictive and Analytics Solutions is Expected to Drive Market Growth.

The U.S. Data Collection And Labeling Market size was valued at USD 855.0 million in 2023 and is projected to reach USD 3964.16 million by 2032, exhibiting a CAGR of 24.5 % during the forecasts period. The US Data Collection and Labeling Market implies the process of gathering and labeling data for the creation of machine learning, artificial intelligence, as well as other data-related applications. The market helps various sectors including retail health care, automotive, and finance through supplying labeled data which is critical in training and improving models used in AI and overall decision-making. Some of the primary applications are related to image and speech recognition, self-driving cars and many others related to Predictive analysis. New directions promote the development of a greater degree of automatization of processes, the use of highly specialized annotation tools, and the need for further development of specialized data labeling services. The market is also experiencing incorporation of artificial intelligence for the automation of several data labeling tasks. Recent developments include: In July 2022, IBM announced the acquisition of Databand.ai to augment its software portfolio across AI, data and automation. For the record, Databand.ai was IBM's fifth acquisition in 2022, signifying the latter’s commitment to hybrid cloud and AI skills and capabilities. , In June 2022, Oracle completed the acquisition of Cerner as the Austin-based company gears up to ramp up its cloud business in the hospital and health system landscape. .

The AI Chipsets market is experiencing explosive growth, projected to reach a substantial size by 2033, driven by a remarkable Compound Annual Growth Rate (CAGR) of 39%. This surge is fueled by several key factors. The increasing adoption of artificial intelligence across diverse sectors, including consumer electronics (driven by the rise of smart devices and personalized AI assistants), automotive (with the proliferation of autonomous driving technologies and advanced driver-assistance systems), healthcare (fueled by medical image analysis and personalized medicine), and automation and robotics (powering industrial automation and smart factories), is a primary driver. Furthermore, advancements in deep learning algorithms and the need for enhanced processing power to handle complex AI workloads are pushing the demand for specialized AI chipsets. Competition among major players like NVIDIA, AMD, Intel, and others is intensifying, fostering innovation and driving down costs, making AI technology more accessible across various applications. However, despite the phenomenal growth, the market faces certain challenges. The high cost of development and manufacturing of advanced AI chipsets can act as a restraint, particularly for smaller companies or those operating in developing economies. Furthermore, the market is characterized by a relatively high barrier to entry, owing to the specialized expertise and significant capital investment required. Nevertheless, ongoing technological advancements, coupled with decreasing production costs, are anticipated to mitigate these challenges, paving the way for even greater market expansion in the forecast period. The segmentation by component (CPU, GPU, NNP, etc.) and application reveals that the GPU segment currently dominates, though the NNP segment is expected to witness the fastest growth due to its specialized architecture optimized for AI workloads. The Asia-Pacific region is poised to become a key market due to its burgeoning tech sector and growing adoption of AI technologies. Recent developments include: May 2022 - Intel introduced two new deep-learning processors for instruction and inference: Habana Gaudi2 and Habana GrecoTM. These innovative processors fill a market void by offering clients high-efficiency, high-performance, deep learning computing options for simultaneous training applications and inference installations in the data center and also reducing the AI obstacle to the entrance to businesses of all sizes., February 2022 - Celestial AI, an AI accelerator company with a proprietary hardware and software platform for machine learning chipsets, announced a USD 56 million Series A investment. The new capital will be used for product development and strategic supplier engagements, including Broadcom., January 2022 - Nvidia and AMD announced that the U.S. government has put in place new restrictions to cut China and Russia off from high-end AI chips., March 2021 - Intel collaborated with the Central Board of Secondary Education (CBSE), aiming to introduce the 'AI For All' initiative to create a basic understanding of artificial intelligence across various industry verticals in India.. Key drivers for this market are: Increase in Demand for Autonomous Driving Technology, Growth in Edge Analytics for IoT Application. Potential restraints include: Increase in Demand for Autonomous Driving Technology, Growth in Edge Analytics for IoT Application. Notable trends are: Consumer Electronics Is Expected to Witness Significant Growth.

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Artificial Intelligence In Marketing Size 2024-2028

The artificial intelligence in marketing size is forecast to increase by USD 41.02 billion, at a CAGR of 30.9% between 2023 and 2028.

The Artificial Intelligence (AI) market in marketing is experiencing significant growth, driven by the increasing adoption of cloud-based applications and services. This shift towards cloud solutions enables businesses to leverage AI technologies more efficiently and cost-effectively, enhancing their marketing capabilities. Furthermore, the ongoing digitalization and expanding internet penetration are fueling the demand for AI solutions in marketing, as companies seek to engage with customers more effectively in the digital space. However, the market's growth is not without challenges. The lack of skilled professionals poses a significant obstacle to wider AI adoption in marketing.
As AI applications become more complex, the need for specialized expertise in areas such as machine learning, data analytics, and programming grows. Companies must invest in upskilling their workforce or partner with external experts to overcome this challenge and fully capitalize on the opportunities presented by AI in marketing.

What will be the Size of the Artificial Intelligence In Marketing during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2018-2022 and forecasts 2024-2028 - in the full report.
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Artificial intelligence (AI) continues to reshape marketing landscapes, with dynamic market activities unfolding across various sectors. Machine learning models optimize digital marketing strategies, enabling predictive analytics for marketing ROI and customer engagement. Brands build stronger connections through AI-powered personalization and sentiment analysis. Data privacy regulations necessitate transparency and accountability, influencing marketing technology stacks and Data Security measures. A/B testing and conversion rate optimization are enhanced through AI-driven insights, while marketing automation workflows streamline customer relationship management. Marketing analytics software and dashboards provide data-driven insights, enabling marketing budget allocation and multi-channel marketing strategies. Behavioral targeting and customer journey mapping are refined through AI, enhancing marketing attribution models and email marketing automation.

Virtual assistants and chatbots facilitate seamless customer experiences, while marketing automation platforms optimize search engine optimization, pay-per-click advertising, and social media advertising. Natural language processing and AI marketing consultants aid content marketing strategies, ensuring algorithmic bias and ethical AI considerations remain at the forefront. Marketing dynamics remain in a constant state of evolution, with AI-driven innovations continuing to transform the industry. Data Governance, marketing attribution models, and programmatic advertising are among the many areas where AI is making an impact. The ongoing integration of AI into marketing technologies and strategies ensures a continuously adaptive and effective marketing landscape.

How is this Artificial Intelligence Ining Industry segmented?

The artificial intelligence ining industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Deployment

  On-premises
  Cloud


Application

  Social Media Advertising
  Search Engine Marketing/ Search Advertising
  Virtual Assistant
  Content Curation
  Sales & Marketing Automation
  Analytics Platform
  Others


Technology

  Machine Learning
  Natural Language Processing
  Computer Vision
  Others


Geography

  North America

    US
    Canada


  Europe

    Germany
    UK


  APAC

    China
    Japan
    Australia
    India


  South America

    Brazil
    Argentina


  Middle East and Africa

    UAE


  Rest of World (ROW)

By Deployment Insights

The on-premises segment is estimated to witness significant growth during the forecast period.

Artificial Intelligence (AI) is revolutionizing marketing, with machine learning models at its core. Brands are building stronger connections with consumers through AI-driven personalization and predictive analytics. A/B testing and marketing analytics software enable data-driven insights, while conversion rate optimization and marketing automation workflows streamline campaigns. Data privacy regulations ensure transparency and accountability, shaping marketing strategies. Behavioral targeting and sentiment analysis provide deeper customer understanding, enhancing customer engagement. Predictive analytics and marketing ROI are key performance indicators, driving marketing budget allocation. C

The data discovery market is experiencing robust growth, fueled by the increasing volume and complexity of data generated across various industries. The market, currently valued in the billions (a precise figure cannot be provided without the missing "XX" market size value, but a reasonable estimate based on similar market reports and a 21% CAGR would place it in the several billion-dollar range in 2025), is projected to maintain a Compound Annual Growth Rate (CAGR) of 21% from 2025 to 2033. This expansion is driven by several key factors. Firstly, the digital transformation initiatives across enterprises are leading to a surge in data generation, creating a critical need for efficient data exploration and analysis tools. Secondly, the rise of big data analytics and the growing demand for data-driven decision-making across sectors, including BFSI, telecom, retail, and manufacturing, are significantly bolstering market demand. Furthermore, advancements in artificial intelligence (AI) and machine learning (ML) are enhancing the capabilities of data discovery platforms, making them more user-friendly and effective in extracting valuable insights. The market is segmented by component (software and services), enterprise size (SMEs and large enterprises), and industry vertical, with BFSI, telecommunications, and retail showing strong adoption. However, despite the impressive growth trajectory, certain restraints exist. The high initial investment costs associated with implementing data discovery solutions can pose a challenge for smaller organizations. Additionally, the complexity of data integration and the need for skilled professionals to manage and interpret the results can hinder wider adoption. Nonetheless, the ongoing technological advancements and the increasing awareness of the strategic value of data are expected to mitigate these limitations, driving further market penetration. The competitive landscape includes both established players like SAS Institute and Salesforce (via Tableau), and emerging innovative companies, signifying a dynamic and evolving market with ample opportunities for growth and innovation. The geographical distribution of the market is likely to be skewed towards mature markets like North America and Europe initially, with Asia Pacific exhibiting strong growth potential in the coming years. Recent developments include: August 2022: CoreLogic, a major global provider of analytics-driven and property data solutions, expanded its partnership with Google Cloud to assist in the introduction of its novel CoreLogic Discovery Platform. Discovery Platform, which is fully built on Google Cloud's safe and sustainable technology, offers a complete asset analytics platform and cloud-based data interchange for enterprises in a variety of industries., June 2022: Select Star established an official collaboration with dbt Labs. Dbt has been one of Select Star's most significant integrations, with over 15,000 models and 225,000 columns linked up to date. Select Star is intended to facilitate the data discovery required by companies in order to harness the potential of their data and generate effective outcomes. As a result, Select Star and Dbt Labs have a shared goal, to empower analytics engineers to convert information better and keep appropriate documentation so that business users and data analysts can trust their data., June 2022: TD SYNNEX's SNX Tech Data established a collaboration with Instructure INST, a Learning Management Systems ("LMS") company, to utilize advanced learning capabilities in India. TD SYNNEX earned a substantial advantage with this deal, in addition to developing its data, Internet of Things, and analytics products. By enabling end-to-end business analytics powered by self-service data discovery, corporate reporting, mobile apps, and embedded analytics, TD SYNNEX's partners were able to offer complete business analytics propelled by data-driven business culture.. Key drivers for this market are: Increasing Number of Multi-Structured Data Sources, Growing Importance for Data-Driven Decision-Making. Potential restraints include: Data Security and Privacy Concerns. Notable trends are: The Banking, Financial Services, and Insurance Sector Holds a Dominant Position.

Applied AI in Agriculture Market Analysis The global applied AI in agriculture market is anticipated to grow exponentially in the coming years, with a market size of over USD 19942.01 million in 2025 and a CAGR of XX% during the forecast period 2025-2033. This growth is primarily driven by the increasing need for efficient farming practices, growing adoption of precision farming techniques, and rising government initiatives to promote smart agriculture. Key trends shaping the market include the integration of AI with IoT devices, the development of advanced algorithms for data analysis, and the increasing use of drones and sensors for data collection. Market Dynamics and Segmentation The applied AI in agriculture market is segmented based on technology, offering, application, company, and region. Major technology segments include machine learning, computer vision, and predictive analytics. The software and AI-as-a-Service segments dominate the offerings market. Drone analytics and precision farming are the prominent applications of AI in agriculture. Key market players include Microsoft, IBM, Google, Amazon.com, Inc., Deere & Company, TechTarget, Vision Robotics Corporation, DroneDeploy, PrecisionHawk, and AGCO Corporation. Regionally, North America and Europe are expected to hold the largest market shares, while Asia Pacific is projected to grow at the highest CAGR during the forecast period. The market is also influenced by factors such as the limited availability of skilled workforce, data privacy and security concerns, and the high cost of implementation. Recent developments include: May 2022, The Alliance for a Green Revolution in Africa (AGRA) and Microsoft have expanded their partnership to advance digital agricultural transformation in Africa. The partnership, which was formalized through a Memorandum of Understanding (MoU) signed on the sidelines of the World Economic Forum in Davos in 2022, builds on previous work between AGRA and Microsoft that focused on supporting AGRA's digital transformation efforts to improve food security in Africa., December 2022 Amazon Web Services (AWS), a subsidiary of Amazon.com, Inc., announced eight new capabilities for Amazon SageMaker, its fully managed machine learning (ML) service. Amazon SageMaker allows developers, data scientists, and business analysts to build, train, and deploy ML models quickly and easily., September 2022 DroneDeploy and Corteva Agriscience announced a partnership to help farmers make better management decisions year-round. Corteva operates one of the world's largest agricultural drone fleets, and DroneDeploy is a leading provider of drone software. Together, the two companies will offer farmers a suite of tools that can be used to monitor crops, identify problems, and optimize yields.. Key drivers for this market are: . The growing adoption of cloud computing, . The increasing adoption of precision agriculture; . Driver impact analysis. Potential restraints include: . High Cost of artificial intelligence precision farming, . Restraint impact analysis. Notable trends are: Growing number of wholesalers are adopting cloud-native software is expected to drive market growth..