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市場調查報告書
商品編碼
1560933
2024-2032 年按類型、產品、技術、系統、最終用途產業和地區分類的人工智慧市場報告Artificial Intelligence Market Report by Type, Offering, Technology, System, End-Use Industry, and Region 2024-2032 |
2023年全球人工智慧IMARC Group規模達926億美元。基於雲端的解決方案的日益普及、自動駕駛汽車 (AV) 銷售的不斷成長以及慢性病的日益流行是推動市場發展的一些關鍵因素。
人工智慧(AI)是指機器,特別是電腦系統對人類智慧過程的模擬。它涉及創建演算法和系統,使機器能夠執行通常需要人類認知功能的任務,例如學習、推理、解決問題和決策。人工智慧涵蓋廣泛的技術,包括機器學習、自然語言處理和電腦視覺。機器學習是人工智慧的一個子集,涉及演算法的開發,使電腦能夠根據資料進行學習並做出預測或決策,而無需明確編程。自然語言處理使機器能夠理解和解釋人類語言,促進人與電腦之間的溝通。此外,電腦視覺使機器能夠解釋和分析來自世界的視覺訊息,類似於人類感知和理解圖像的方式。
資料生成的指數級成長和高效能運算資源的可用性使人工智慧系統能夠處理和分析海量資料集,促進了先進人工智慧演算法和模型的發展。此外,人工智慧驅動的自動化有潛力簡化從製造到物流等各個領域的營運並提高效率。企業正在利用人工智慧來最佳化流程、降低成本並提高整體生產力。除此之外,人工智慧驅動的演算法使企業能夠為客戶提供個人化體驗,從而提高參與度和滿意度。推薦系統、聊天機器人和虛擬助理使用人工智慧來了解客戶偏好並提供量身定做的解決方案。除此之外,人工智慧還透過幫助診斷、藥物發現和治療開發來徹底改變醫療保健。醫學影像分析、預測分析和基因組學研究正受益於人工智慧驅動的見解。與此相適應,智慧型裝置和物聯網 (IoT) 正在將人工智慧整合到語音識別、臉部辨識和預測性維護中,促進人工智慧在消費性電子產品中的發展。此外,人工智慧正在透過演算法交易、詐欺偵測和風險評估重塑金融業。機器學習演算法分析市場趨勢並預測投資機會。此外,機器學習技術特別是深度學習的突破增強了人工智慧系統在影像辨識、自然語言理解和預測分析等任務中的能力,從而在各行業中得到更廣泛的應用。
數據擴散和處理能力
數位時代產生了前所未有的大量訊息,從客戶行為資料到物聯網設備的感測器資料。這些豐富的資料是訓練人工智慧演算法和模型的基礎。此外,高效能運算資源(包括 GPU 和專用人工智慧硬體)的可用性使研究人員和開發人員能夠以驚人的速度處理和分析這些龐大的資料集。資料可用性和處理能力之間的協同作用釋放了開發複雜人工智慧系統的潛力,該系統能夠識別模式、做出預測並得出以前無法獲得的見解。
機器學習的進步
受神經網路啟發的深度學習演算法在影像辨識、自然語言理解和語音合成等任務中展現了卓越的表現。這些演算法擅長從原始資料中自動學習分層特徵,使它們能夠以極高的準確性執行複雜的任務。遷移學習是深度學習中的一種技術,允許針對一項任務預先訓練的模型針對另一項任務進行微調,從而減少對大量標記資料的需求。這些進步降低了人工智慧開發的進入門檻,擴大了其在各個領域的適用性,推動人工智慧解決方案融入日常技術和流程。
自動化和效率
由人工智慧技術支援的自動化,例如機器人流程自動化 (RPA) 和自主系統,正在消除先前消耗寶貴人力資源的重複性和平凡的任務。這種轉變使人類工作者能夠專注於需要創造力、批判性思維和解決問題的更高價值的任務。製造、物流和客戶服務等行業正在部署人工智慧驅動的機器人和系統來處理從庫存管理到客戶互動等各種任務。其結果不僅提高了生產力,而且提高了準確性和一致性。企業正在認知到人工智慧改變其營運的潛力,從而導致廣泛採用自動化解決方案,增強人類能力並推動業務成長。
The global artificial intelligence market size reached US$ 92.6 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 737.1 Billion by 2032, exhibiting a growth rate (CAGR) of 24.9% during 2024-2032. The increasing adoption of cloud-based solutions, rising sales of autonomous vehicles (AVs), and the growing prevalence of chronic diseases represent some of the key factors driving the market.
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, particularly computer systems. It involves the creation of algorithms and systems that enable machines to perform tasks that typically require human cognitive functions, such as learning, reasoning, problem-solving, and decision-making. AI encompasses a wide range of technologies, including machine learning, natural language processing, and computer vision. Machine learning, a subset of AI, involves the development of algorithms that allow computers to learn from and make predictions or decisions based on data without explicit programming. Natural language processing enables machines to understand and interpret human language, facilitating communication between humans and computers. Additionally, computer vision empowers machines to interpret and analyze visual information from the world, similar to the way humans perceive and understand images.
The exponential increase in data generation and the availability of high-performance computing resources have enabled AI systems to process and analyze massive datasets, fostering the development of advanced AI algorithms and models. Additionally, AI-driven automation has the potential to streamline operations and enhance efficiency in various sectors, from manufacturing to logistics. Businesses are leveraging AI to optimize processes, reduce costs, and improve overall productivity. Other than this, AI-powered algorithms enable businesses to offer personalized experiences to customers, enhancing engagement and satisfaction. Recommendation systems, chatbots, and virtual assistants use AI to understand customer preferences and deliver tailored solutions. Besides this, AI is revolutionizing healthcare by aiding in diagnostics, drug discovery, and treatment development. Medical imaging analysis, predictive analytics, and genomics research are benefiting from AI-driven insights. In line with this, smart devices and the Internet of Things (IoT) are integrating AI for voice recognition, facial recognition, and predictive maintenance, contributing to the growth of AI in consumer electronics. Furthermore, AI is reshaping the financial industry with algorithmic trading, fraud detection, and risk assessment. Machine learning algorithms analyze market trends and predict investment opportunities. Moreover, breakthroughs in machine learning techniques, particularly deep learning, have enhanced the capabilities of AI systems in tasks such as image recognition, natural language understanding, and predictive analytics, leading to broader applications across industries.
Data Proliferation and Processing Power
The digital age has generated an unprecedented amount of information, ranging from customer behavior data to sensor data from IoT devices. This wealth of data serves as the foundation for training AI algorithms and models. Moreover, the availability of high-performance computing resources, including GPUs and specialized AI hardware, has empowered researchers and developers to process and analyze these vast datasets at remarkable speeds. This synergy between data availability and processing power has unlocked the potential to develop sophisticated AI systems capable of recognizing patterns, making predictions, and deriving insights that were previously inaccessible.
Advancements in Machine Learning
Deep learning algorithms, inspired by neural networks, have shown exceptional performance in tasks such as image recognition, natural language understanding, and speech synthesis. These algorithms excel at automatically learning hierarchical features from raw data, enabling them to perform complex tasks with remarkable accuracy. Transfer learning, a technique within deep learning, allows models pre-trained on one task to be fine-tuned for another, reducing the need for extensive labeled data. Such advancements have lowered the barriers to entry for AI development and expanded its applicability in various domains, driving the integration of AI solutions into everyday technologies and processes.
Automation and Efficiency
Automation powered by AI technologies, such as robotic process automation (RPA) and autonomous systems, is eliminating repetitive and mundane tasks that previously consumed valuable human resources. This shift allows human workers to focus on higher-value tasks that require creativity, critical thinking, and problem-solving. Industries like manufacturing, logistics, and customer service are deploying AI-powered robots and systems to handle tasks ranging from inventory management to customer interactions. The result is not only increased productivity but also improved accuracy and consistency. Businesses are recognizing the potential of AI to transform their operations, leading to the widespread adoption of automation solutions that augment human capabilities and drive business growth.
IMARC Group provides an analysis of the key trends in each segment of the global artificial intelligence market report, along with forecasts at the global, regional and country levels from 2024-2032. Our report has categorized the market based on type, offering, technology, system and end-use industry.
Narrow/weak artificial intelligence dominates the market
The report has provided a detailed breakup and analysis of the market based on the type. This includes narrow/weak artificial intelligence and general/strong artificial intelligence. According to the report, narrow/weak artificial intelligence represented the largest segment.
Unlike general or strong AI, which aims to replicate human-like cognitive abilities across a wide range of tasks, narrow AI is designed to excel in specific, well-defined tasks. This focused approach allows for more efficient development and deployment. Narrow AI technologies, such as machine learning and natural language processing, have demonstrated remarkable proficiency in tasks like image recognition, language translation, virtual assistants, and recommendation systems. This effectiveness has led to rapid adoption in sectors like healthcare, finance, e-commerce, and manufacturing, where the immediate benefits of automation, efficiency, and data-driven insights are highly valued. Additionally, the development of narrow AI systems often requires less complex algorithms and data, making it more accessible for businesses to implement and integrate into their existing workflows.
Software holds the largest share in the market
A detailed breakup and analysis of the market based on the offering has also been provided in the report. This includes hardware, software, and services. According to the report, software accounted for the largest market share.
In the industry of artificial intelligence (AI), software plays a pivotal role as it serves as the foundation for developing, deploying, and managing AI applications. The accessibility of AI software frameworks, libraries, and tools has lowered the entry barriers for businesses, researchers, and developers to experiment with and integrate AI capabilities into their operations. Software offerings encompass a wide array of AI applications, from machine learning platforms to natural language processing APIs. This flexibility allows organizations to tailor AI solutions to their specific needs, whether it's optimizing supply chains, personalizing customer experiences, or automating decision-making processes. Furthermore, the cloud-based nature of many AI software solutions enables seamless scalability and updates, ensuring that businesses can stay abreast of the latest advancements without significant infrastructure investments.
Machine learning is the most widely used technology
The report has provided a detailed breakup and analysis of the market based on technology. This includes machine learning, natural language processing, context-aware computing, computer vision, and others. According to the report, machine learning represented the largest segment.
AI software serves as the intellectual core, housing algorithms, models, and data processing mechanisms that empower machines to simulate human cognitive functions. This software-driven approach offers unparalleled flexibility, enabling developers and businesses to tailor AI solutions to a diverse range of applications across industries. The accessibility of AI software tools and platforms has democratized AI development, allowing organizations to integrate AI functionalities into existing workflows and applications without extensive hardware investments. This accessibility, coupled with the rapid advancements in AI algorithms and techniques, ensures that software remains at the forefront of AI innovation. Moreover, the cloud-based deployment of AI software solutions facilitates scalability and updates, ensuring that businesses can stay current with the evolving AI landscape.
Intelligence systems hold the largest share in the market
A detailed breakup and analysis of the market based on the system has also been provided in the report. This includes intelligence systems, decision support processing, hybrid systems, and fuzzy systems. According to the report, intelligence systems accounted for the largest market share.
Intelligence systems encompass a wide array of applications, ranging from virtual assistants and chatbots to advanced recommendation engines and predictive analytics platforms. These systems leverage AI algorithms to process vast amounts of data, derive meaningful insights, and facilitate informed decision-making. The appeal of intelligence systems lies in their ability to enhance efficiency, accuracy, and customer engagement across various sectors. Virtual assistants streamline customer interactions, while recommendation engines personalize user experiences, both of which contribute to improved satisfaction and retention. Furthermore, intelligence systems enable predictive analytics, enabling businesses to anticipate trends and optimize strategies.
Manufacturing represents the largest segment
The report has provided a detailed breakup and analysis of the market based on end-use industry. This includes healthcare, manufacturing, automotive, agriculture, retail, security, human resources, marketing, financial services, transportation and logistics, and others. According to the report, manufacturing represented the largest segment.
AI technologies are revolutionizing manufacturing by enhancing operational efficiency, quality control, and product innovation. AI-driven automation optimizes production processes, leading to reduced downtime, higher productivity, and improved resource utilization. Manufacturing involves intricate tasks such as predictive maintenance, where AI algorithms analyze equipment data to predict maintenance needs, preventing costly breakdowns. Quality control benefits from AI-powered visual inspection systems that detect defects with exceptional accuracy. Additionally, AI-driven analytics aid in demand forecasting and supply chain optimization, ensuring efficient inventory management and minimizing production bottlenecks.
North America exhibits a clear dominance in the market
The report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America was the largest market for artificial intelligence.
North America possesses a dense concentration of tech giants, research institutions, and startups, facilitating knowledge exchange and collaboration. Silicon Valley, in particular, serves as a global hub for AI research and development. The availability of venture capital funding in North America accelerates AI-driven entrepreneurship and disruptive solutions. Additionally, a skilled workforce proficient in AI technologies contributes to the region's competitive advantage. Major industries, including technology, healthcare, finance, and manufacturing, heavily invest in AI to gain a competitive edge, driving the market's growth. Moreover, North American governments promote AI research through funding and supportive policies. Collaboration between academia and industry propels AI advancements, while a receptive consumer base encourages AI adoption in products and services.
Major technology companies like Google, Microsoft, and IBM invest significantly in AI research and development, contributing to breakthroughs in algorithms, natural language processing, and machine learning frameworks. Additionally, tech leaders such as Facebook, OpenAI, and NVIDIA contribute to open-source AI projects, democratizing access to AI tools and accelerating development by fostering collaboration among developers. Other than this, organizations such as Apple, Amazon, and Intel acquire AI startups to harness their expertise and innovative solutions. Partnerships with research institutions and other industry players foster knowledge exchange and technology sharing. Besides this, financial institutions like JPMorgan Chase utilize AI for risk assessment, fraud detection, and trading algorithms, enhancing accuracy and decision-making.