Re: Artificial Intelligence Market Pdf Free
Icaro Aveiga
Autonomous trucking reduces costs by allowing for increased asset utilisation as 24/7 runtimes are possible. Moreover, the whole business model of transport & logistics (T&L) might be disrupted by new market entrants such as truck manufacturers offering T&L and large online retailers vertically integrating their T&L.
This report presents a brief overview of top AI global hubs outside the United States. Each country includes an AI ecosystem overview, government incentives & policies, education & research institutions, leading events, and industry groups. The initial markets for this report were selected based on global rankings, the highest number of AI companies concentrated there, venture capital, and related research institutions.
The global artificial intelligence market size was valued at USD 136.55 billion in 2022 and is projected to expand at a compound annual growth rate (CAGR) of 37.3% from 2023 to 2030. The continuous research and innovation directed by tech giants are driving adoption of advanced technologies in industry verticals, such as automotive, healthcare, retail, finance, and manufacturing. For instance, in November 2020, Intel Corporation acquired Cnvrg.io, an Israeli company that develops and operates a platform for data scientists to build and run machine learning models, to boost its artificial intelligence business. Technology has always been an essential element for these industries, but artificial intelligence (AI) has brought technology to the center of organizations. For instance, from self-driving vehicles to crucial life-saving medical gear, AI is being infused virtually into every apparatus and program.
COVID-19 outbreak is expected to stimulate market growth of next-generation tech domains, including artificial intelligence, owing to mandated WFH (work-from-home) policy due to the pandemic. For instance, LogMeIn, Inc., a U.S.-based company that provides SaaS (Software-as-a-Service) and cloud-based customer engagement and remote connectivity & collaboration services, has experienced a significant increase in new sign-ups across its product portfolios amid the pandemic. Also, tech companies are expanding their product offerings and services to widen availability across the globe. For instance, in April 2020, Google LLC launched an AI-enabled chatbot called Rapid Response Virtual Agent for call centers. This chatbot is built to respond to issues customers might be experiencing due to coronavirus (COVID-19) outbreak over voice, chat, and other social channels.
The introduction of big data is projected to accelerate the expansion of the artificial intelligence market as a large volume of data needs to be stored, captured, and analyzed. End-users are increasingly concerned about the need to manage and improve the computational model of such data. This is encouraging companies to introduce artificial intelligence solutions at a faster pace. Several private and public organizations have gathered tasks or application-specific information comprising issues, such as medical informatics, fraud detection, national intelligence, marketing, and cybersecurity. Artificial Intelligence algorithms enable automated analysis of unsupervised and unorganized data by continuously improving each set of data.
Artificial intelligence is becoming increasingly important in big data because it enables the extraction of high-level and complex abstractions through a centralized learning process. The need for extracting and mining meaningful patterns from large amounts of data propels the growth of artificial intelligence in big data analytics. Furthermore, the technology aids in overcoming big data analytics challenges such as data analysis trustworthiness, raw data format variation, imbalanced input data, and highly distributed input sources. Another issue is a lack of efficient storage and information retrieval, as data is collected in large quantities and made available across multiple domains. These difficulties are overcome by using semantic indexing, which improves comprehension and knowledge discovery.
Software solutions led the market and accounted for more than 36.7% of the global revenue in 2022. This high percentage can be attributed to prudent advances in information storage capacity, high computing power, and parallel processing capabilities to deliver high-end services. Furthermore, the ability to extract data, provide real-time insight, and aid decision-making has positioned this segment to capture a significant portion of the market. Artificial intelligence software solutions include libraries for designing and deploying artificial intelligence applications, such as primitives, linear algebra, inference, sparse matrices, video analytics, and multiple hardware communication capabilities. The need for enterprises to understand and analyze visual content to gain meaningful insights is expected to spur the adoption of artificial intelligence software over the forecast period.
Companies adopt AI services to reduce their overall operational costs, yielding more profit. Artificial Intelligence as a Service, or AIaaS, is being used by companies to obtain a competitive advantage over cloud. Artificial intelligence services include installation, integration, maintenance, and support undertakings. The segment is projected to grow significantly over the forecast period. AI hardware includes chipsets such as GPU (Graphics Processing Unit), CPU, application-specific integrated circuits (ASIC), and field-programmable gate arrays (FPGAs). GPUs and CPUs currently dominate the artificial intelligence hardware market due to their high computing capabilities required for AI frameworks. For instance, in September 2020, Atomwise partnered with GC Pharma to offer AI-based services to the former and help develop more effective novel hemophilia therapies.
Machine learning and deep learning cover significant investments in AI. They include both AI platforms and cognitive applications, including tagging, clustering, categorization, hypothesis generation, alerting, filtering, navigation, and visualization, which facilitate the development of advisory, intelligent, and cognitively enabled solutions. Growing deployment of cloud-based computing platforms and on-premises hardware equipment for the safe and secure restoration of large volumes of data has paved a way for the expansion of the analytics platform. Rising investments in research and development by leading players will also play a crucial role in increasing the uptake of artificial intelligence technologies. During the forecast period, NLP segment is expected to gain momentum. NLP is becoming increasingly widely used in various businesses to understand client preferences, evolving trends, purchasing behavior, decision-making processes, and more, in a better manner.
The advertising & media segment led the market and accounted for more than 19.5% of the global revenue share in 2022. This high share is attributable to growing AI marketing applications with significant traction. For instance, in January 2022, Cadbury started an initiative to let small business owners create their AD for free using the face and voice of a celebrity, with the help of an AI tool. However, the healthcare sector is anticipated to gain a leading share by 2030. Healthcare segment has been segregated based on use cases such as robot-assisted surgery, dosage error reduction, virtual nursing assistants, clinical trial participant identifier, hospital workflow management, preliminary diagnosis, and automated image diagnosis. The BFSI segment includes financial analysis, risk assessment, and investment/portfolio management solicitations.
Artificial intelligence has witnessed a significant share in the BFSI sector due to high demand for risk & compliance applications along with regulatory and supervisory technologies (SupTech). By using AI-based insights in Suptech tools in financial markets, the authorities are increasingly examining FinTech-based apps used for regulatory, supervisory, and oversight purposes for any potential benefits. In a similar vein, regulated institutions are creating and implementing FinTech applications for reporting and regulatory and compliance obligations. Financial institutions are using AI applications for risk management and internal controls as well. The combination of AI technology with behavioral sciences enables large financial organizations to prevent wrongdoing, moving the emphasis from ex-post resolution to proactive prevention.
Other verticals for artificial intelligence systems include retail, law, automotive & transportation, agriculture, and others. Conversational AI platform is one of the most used applications in every vertical. For instance, in April 2020, Google LLC launched a Rapid Response Virtual Agent for call centers. This new chatbot is built to respond to issues customers might be experiencing due to coronavirus (COVID-19) outbreak over voice, chat, and other social channels. Retail segment is anticipated to witness a substantial rise owing to the increasing focus on providing an enhanced shopping experience. An increasing amount of digital data in text, sound, and images from different social media sources is driving the need for data mining and analytics. In the entertainment and advertising industry, AI has been creating a positive impact, and companies are using AI techniques to promote their products and connect to the customer base.
The regional market in Asia Pacific is anticipated to witness significant growth in artificial intelligence market. This growth owes to the significantly increasing investments in artificial intelligence. For instance, in April 2018, Baidu, Inc., a China-based tech giant, announced that it had entered into definitive agreements with investors concerning the divestiture of its financial services group (FSG), providing wealth management, consumer credit, and other business services. The investors are led by Carlyle Investment Management LLC and Tarrant Capital IP, LLC, with participation from ABC International and Taikanglife, among others. Also, a growing number of start-ups in the region are boosting the adoption of AI to improve operational efficiency and enable process automation.
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