Global Artificial Intelligence in Applications Market Size, Share & Trends Analysis, By Application (Healthcare, Finance, manufacturing, Retail), By Technology (Machine Learning (ML), Natural Language Processing (NLP), Computer Vision, Context-Aware Computing), By Deployment (On-premise, Cloud Based, Hybrid), By Region (North America, Europe, APAC, and Others), and Segment Forecasts, 2023 – 2030
  • Published Date: Nov, 2023
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  • Pages: 200
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  • Report Summary
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  • Methodology
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The AI in Application Market, often referred to as the AI Application Market, encompasses the diverse landscape of applications and solutions that leverage artificial intelligence (AI) technologies to enhance and optimize various processes across multiple industries. This market includes software, platforms, and services that utilize AI algorithms, machine learning, natural language processing, computer vision, and other AI techniques to automate tasks, analyze data, make predictions, and improve decision-making. AI applications span across sectors such as healthcare, finance, manufacturing, e-commerce, transportation, education, and more, providing benefits like increased efficiency, cost savings, enhanced user experiences, and data-driven insights. The market continually evolves as AI technologies advance, offering innovative solutions to address a wide range of challenges and opportunities in our increasingly AI-driven world.

Some of the benefits of designing a Artificial Intelligence in Applications Market include:

  • Automation: Through AI, repetitive and labor-intensive tasks can be streamlined, leading to heightened operational efficiency and significant cost reductions.
  • Elevated Productivity: AI-driven tools and applications serve as a force multiplier for human capabilities, resulting in increased productivity and more informed decision-making.
  • Data Insight: AI empowers rapid data analysis, unveiling intricate patterns and furnishing actionable insights for businesses and organizations.
  • Tailored Experiences: AI personalizes user interactions by delivering individualized recommendations and content, bolstering customer satisfaction and engagement.
  • Enhanced Customer Support: AI-driven chatbots and virtual assistants provide an elevated level of customer service, offering round-the-clock assistance and efficiently addressing inquiries.
  • Proactive Decision-Making: With predictive analytics, AI anticipates trends and future events, equipping organizations to make anticipatory decisions and mitigate risks effectively.

Global Artificial Intelligence in Applications Market was valued at US $ 287 Billion in 2022 and is expected to reach US $2016.84 Billion by 2030 growing at a CAGR of 27.6% during the forecast period 2023 – 2030.

COVID -19 Impact

The COVID-19 pandemic has left an indelible mark on the AI application market, ushering in both immediate adaptations and long-term transformations. The accelerated digital transformation triggered by the pandemic prompted a surge in AI applications that facilitate remote work, automate processes, and support digital engagement. In healthcare, AI played a pivotal role in diagnosis, patient monitoring, and drug discovery, particularly in the context of the burgeoning telemedicine services. Supply chain management also witnessed increased AI adoption for demand prediction, inventory optimization, and logistics enhancements. As remote work became the norm, AI-powered collaboration tools saw widespread adoption, improving teamwork, document management, and knowledge sharing. The pandemic underscored the importance of data analysis and predictive modeling, as AI was employed to track the virus's spread, monitor interventions, and analyze clinical data. Retail and e-commerce sectors turned to AI for demand forecasting, inventory management, and customer engagement, while the entertainment industry relied on AI for content recommendations and moderation.

With the shift to online activities, AI's role in cybersecurity became more pronounced, detecting threats and anomalies in network traffic and safeguarding data. Education leveraged AI for remote learning solutions and personalized learning platforms. Despite the challenges, the pandemic fueled innovation and investment in AI technologies, as businesses recognized their potential to address pandemic-related challenges and enhance resilience. However, the pandemic also brought challenges and ethical considerations to the forefront, particularly in terms of privacy, data security, and the responsible use of AI in healthcare and public health decisions. AI also played a role in vaccine development, accelerating the process through data analysis and candidate identification. The pandemic underscored AI's adaptability and resilience. Many of the AI applications that emerged during the crisis are poised to shape post-pandemic industries, as organizations recognize the value of AI-driven solutions in ensuring continuity, efficiency, and innovation in an evolving landscape.

Factors Driving the Market

Drivers

Rising Demand for Automation

The surging demand for automation is a powerful catalyst propelling the growth of AI in the application market. Automation, driven by AI technologies, offers an array of advantages, from heightened efficiency and productivity to cost savings and reduced human error. As businesses and organizations seek to streamline their operations and respond to the ever-increasing need for scalability and 24/7 availability, AI-powered automation becomes an indispensable asset.

AI automation not only enhances productivity but also leads to consistent and standardized processes, ensuring accuracy and quality across various tasks. Its potential to revolutionize the customer experience through rapid responses, personalized recommendations, and data-driven decision-making positions it as a key driver of customer satisfaction and loyalty. Additionally, the scalability and adaptability of AI-driven automation enable businesses to swiftly respond to market changes and evolving customer preferences, fostering innovation and a competitive edge. This demand for automation transcends industry boundaries, impacting sectors such as manufacturing, healthcare, finance, logistics, and more. AI automation is intricately linked to emerging technologies like the Internet of Things (IoT), bolstering automation capabilities and connectivity. Furthermore, it contributes to security enhancements by monitoring and responding to cybersecurity threats and fraud prevention. Sustainable practices, operational resilience, and the optimization of resources are additional benefits, aligning with broader environmental and business goals. In conclusion, the escalating demand for automation underlines the pivotal role of AI in reshaping industries and revolutionizing how businesses operate. As automation becomes an essential tool for efficiency, customer satisfaction, and competitiveness, AI applications are experiencing rapid growth and transformation across diverse sectors.

Advancements in AI Technologies

The continuous advancements in AI technologies serve as a driving force behind the expansion of the AI application market. These ongoing developments lead to enhanced performance, lower costs, and increased scalability, making AI solutions more appealing and accessible to a wide range of industries and organizations. Moreover, the evolution of AI technology fosters the creation of new use cases and applications, unlocking innovative possibilities that were once considered out of reach. Interoperability and customization benefit from these advancements, enabling the seamless integration of AI into existing workflows and systems while tailoring AI solutions to specific needs. The ongoing progress also supports the emergence of ethical and responsible AI, essential for building trust and ensuring regulatory compliance. Edge AI, robustness, and security enhancements, as well as the growing focus on cross-industry innovation, further accentuate the transformative potential of AI technologies. As AI research and development continue to thrive, they attract talent, investments, and collaborative efforts across various sectors. This ever-evolving landscape solidifies AI's role as a transformative and indispensable technology, ushering in a new era of innovation and application across industries, from healthcare and finance to manufacturing and beyond.

Challenges

Data Privacy and Security Concerns

Data privacy and security concerns exert a profound influence on the AI market. The surge in data protection regulations has compelled AI developers and businesses to comply with strict rules, encompassing data consent, encryption, and access control. Compliance measures have become imperative, and companies must invest in technology and processes that ensure the safeguarding of personal information. Trust and user confidence, integral to the widespread adoption of AI, hinge on robust data security and privacy practices. However, these concerns also pose challenges, as they can limit the types and amounts of data AI systems can access and employ. Stricter regulations have led to increased scrutiny from regulators and authorities, making transparent data practices a necessity. Data breaches involving AI can result in legal and financial liabilities, adversely affecting brand reputation and causing financial losses. Ethical considerations are inextricably linked to data privacy and security in AI, as ensuring the privacy of individuals is an ethical imperative. Furthermore, data privacy and security often intersect with the critical issues of bias and fairness in AI. Protecting data privacy must be harmonized with the imperative to ensure AI systems are fair and unbiased. These concerns also have financial implications, as they can impact innovation by constraining access to data sources and requiring costly security measures. For smaller AI startups, in particular, data privacy and security requirements can pose significant entry barriers.

In this complex landscape, the global nature of AI operations encounters challenges due to divergent data privacy laws in various regions, affecting data flow and market access. Moreover, cyber threats targeting AI systems themselves necessitate heightened investment in security measures. Addressing these challenges while balancing innovation and safeguarding data privacy is critical for the continued growth and responsible development of AI technologies.

Trends

AI for Drug Discovery and Medical Diagnosis

AI for Drug Discovery and Medical Diagnosis offers a multitude of opportunities with transformative potential in the healthcare sector and beyond. By harnessing the power of artificial intelligence, drug discovery processes can be greatly accelerated, leading to the development of new pharmaceuticals in a more efficient and cost-effective manner. Personalized medicine, made possible through AI, enables tailored treatment plans that enhance patient outcomes and minimize adverse effects. Additionally, AI-driven diagnostics enable early disease detection, reducing healthcare costs and improving patient care quality. Resource optimization in healthcare, thanks to AI, streamlines operations and resource allocation, contributing to cost savings and improved patient experiences. The growth of telemedicine and remote patient monitoring, facilitated by AI, expands healthcare access and patient care options. Furthermore, AI empowers the identification of existing drugs that can be repurposed for new medical conditions, thereby saving valuable time and resources.

Through targeted therapy and the reduction of unnecessary medical tests and procedures, AI helps mitigate healthcare expenses while ensuring more effective treatments. AI also plays a vital role in supporting public health initiatives, from analyzing disease outbreaks to improving vaccination and treatment strategies. The vast data generated by AI applications fosters further research and insights, contributing to a deeper understanding of diseases and potential cures. Global collaboration in healthcare, enabled by AI, enhances the exchange of knowledge and expertise among healthcare professionals and researchers. In addition to improving healthcare outcomes, AI adoption creates employment opportunities in AI-related fields and encourages the development of essential skills. AI for Drug Discovery and Medical Diagnosis is revolutionizing healthcare, unlocking new horizons for economic growth, medical advancements, and ultimately, improved health outcomes for individuals and communities.

AI for Fraud Detection and Risk Management

AI plays a pivotal role in Fraud Detection and Risk Management across various industries, offering a multifaceted approach to identifying and mitigating fraudulent activities while effectively managing risks. Through its capabilities, AI excels in anomaly detection by recognizing unusual or suspicious patterns, providing real-time monitoring of transactions and activities, and adapting to evolving fraud tactics. The technology excels in pattern recognition, behavioral analysis, and natural language processing, enabling organizations to uncover and respond to fraudulent behavior, even in the face of sophisticated techniques.

Moreover, AI's scalability and predictive analytics empower organizations to handle large volumes of data and forecast future trends, proactively addressing vulnerabilities and potential risks. It also enhances customer authentication, secures lending processes, and aids in regulatory compliance. By automating fraud detection, AI reduces the need for manual reviews, resulting in cost savings. Its adaptive learning capabilities ensure resilience against evolving threats, while its capacity for data integration provides a comprehensive view of risks. Furthermore, AI helps balance the need for robust fraud prevention with a seamless customer experience by minimizing false positives. In the event of a security breach or fraud incident, AI contributes to incident response efforts by identifying the extent of damage and guiding effective containment and resolution strategies. Overall, AI's data-processing power, pattern recognition, and adaptability make it an invaluable asset for safeguarding against fraudulent activities and effectively managing risks, ensuring the security of organizations and individuals alike.

Market Segmentation

By Application

By Application, the global Artificial Intelligence in Applications Market is divided into Healthcare, Finance, Manufacturing, Retails.

Healthcare is leading with 46.94% market share globally and expected o be the fastest growing application with 30.67 % CAGR in AI in Application Market. The healthcare sector benefits from the vast availability of data, encompassing electronic health records, medical images, patient histories, and clinical notes, which AI effectively analyzes to enhance diagnostics, treatment plans, and patient care. AI's prowess in diagnosing diseases and conditions with exceptional accuracy, coupled with its ability to personalize treatment plans based on individual genetic and health data, offers the promise of earlier and more precise healthcare interventions. In drug discovery, AI expedites the identification of potential candidates, reducing research and development timelines. Remote monitoring and predictive analytics improve healthcare providers' ability to identify health issues proactively, and AI streamlines hospital operations and supports telemedicine platforms, extending accessible healthcare services. Regulatory support, increased investment, and collaborations between technology companies and healthcare providers have further accelerated AI's impact on the healthcare sector. Moreover, the COVID-19 pandemic underscored the critical role of AI in public health, from contact tracing and vaccine development to epidemiological modeling, emphasizing the vital and evolving role of AI in healthcare.

By Technology

By Technology, the global Artificial Intelligence in Applications Market is divided into Machine Learning (ML), Natural Language Processing (NLP), Computer Vision, Context-Aware Computing.

Computer Vision claims the forefront in the AI in Application Market due to its extensive application across various industries, including healthcare, automotive, retail, and manufacturing. It stands out as one of the most mature AI technologies, boasting a track record of successful commercial implementations.

On the other hand, Natural Language Processing (NLP) takes the lead as the fastest-growing technology with 25.3% CAGR in the AI in Application Market. This momentum is fueled by a rising demand for AI-driven language solutions, encompassing applications like chatbots, voice assistants, and machine translation. Beyond these language-centric applications, NLP is driving innovation in diverse sectors such as healthcare, education, and customer service. Its versatility and adaptability contribute significantly to its rapid growth in the AI landscape.

By Deployment

By Deployment, the global Artificial Intelligence in Applications Market is divided into On-premises, Cloud based, Hybrid.

Cloud deployment has emerged as the leading and fastest-growing model with 23.45% CAGR in the AI in Applications market, driven by a combination of scalability, cost-efficiency, and flexibility. Cloud platforms provide businesses with the ability to easily scale AI applications based on demand, optimizing resource utilization without significant upfront investments. The pay-as-you-go model ensures cost-effectiveness, eliminating the need for large capital expenditures. Cloud services offer pre-configured environments and a variety of AI-related tools, reducing deployment time and enabling organizations to leverage cutting-edge technologies. Global accessibility, seamless collaboration, and integration with other cloud-based services further contribute to the appeal of cloud deployment. Additionally, the robust security measures, handling of maintenance, updates, and advanced data storage solutions provided by leading cloud providers address key concerns associated with AI applications. In essence, the cloud's agility, accessibility, and comprehensive service offerings position it as the pivotal force propelling the growth and dominance of AI in the Applications market.

By Region

By region, the global Artificial Intelligence in Applications Market is divided into North America, Europe, APAC and Others. Others is further divided into Middle East, Africa and South America.

North America is leading with 40.34% market share globally due to its strong foundation in technological innovation and investment. Silicon Valley and tech hubs across the continent have fueled substantial investments in AI research and development, fostering a mature ecosystem of startups, research institutions, and enterprises that actively collaborate to drive AI advancements. Furthermore, North America's well-established market adoption of AI across various sectors positions it as a frontrunner. Additionally, the region benefits from a rich talent pool drawn from top universities and research institutions worldwide.

Conversely, the Asia-Pacific region has garnered recognition as the fastest-growing market with 26.4% CAGR, propelled by its sheer population size, burgeoning middle class, and rapid economic growth. Several APAC countries, including China and India, have experienced substantial economic expansion, spurring demand for AI applications to enhance efficiency and meet consumer needs. Government support and initiatives across the region further stimulate AI development, while emerging startups and tech companies contribute to a vibrant AI ecosystem. The APAC region's adaptive approach tailors AI solutions to address local challenges, making it a dynamic force in the global AI landscape.

Competitive Landscape

The global Artificial Intelligence in Applications Market is consolidated with the presence of few major players contributing to the market revenue. This dominance of these major players is driven by their technological expertise, extensive resources, and established brand recognition. These companies typically offered comprehensive and diversified solutions to end use application.

  • Google

Google AI, a subsidiary of Alphabet Inc., is a global leader in artificial intelligence research, development, and application. Founded in 2017, Google AI is at the forefront of AI innovation, contributing to advancements that impact a wide range of industries and technologies.

  • Amazon

Amazon.com, Inc., commonly known as Amazon, is one of the world's largest and most influential technology and e-commerce companies. Founded in 1994 by Jeff Bezos, Amazon has transformed the way people shop, access digital content, and utilize cloud computing.

  • Microsoft

Microsoft Corporation, commonly referred to as Microsoft, is one of the world's leading technology companies. Founded in 1975 by Bill Gates and Paul Allen, Microsoft has played a pivotal role in shaping the modern computing landscape.

  • IBM
  • INVIDIA
  • Apple
  • Meta
  • Salesforce
  • Adobe
  • SAP
  • Oracle
  • Tencent
  • Baidu
  • Alibaba
  • com
  • Huawei
  • Sense Time
  • Uipath
  • Palantir
  • ai

Recent Developments

  • In June 2023, a groundbreaking collaboration was unveiled as Google AI and Johnson & Johnson joined forces to pioneer the realm of AI-enhanced healthcare solutions. This strategic partnership will harness the power of artificial intelligence to create innovative algorithms and applications aimed at elevating patient care, propelling the frontiers of medical research, and revolutionizing the development of cutting-edge pharmaceuticals and therapies.
  • In May 2023, a landmark collaboration was unveiled, as Microsoft AI and Roche forged a partnership aimed at advancing the field of AI-driven drug discovery tools. This strategic alliance will leverage the potential of artificial intelligence to create novel algorithms designed for the identification and development of innovative pharmaceuticals and therapeutic solutions.
  • In February 2023, IBM unveiled a groundbreaking offering in the financial sector with the introduction of IBM Watson Assistant for Financial Services. This innovative cloud-based AI solution is designed to empower financial institutions by enhancing customer service, mitigating fraud, and ensuring regulatory compliance
  • In April 2023, Amazon made a significant announcement by introducing Amazon SageMaker Canvas for Financial Services. This cutting-edge no-code AI development tool empowers financial institutions to effortlessly craft and deploy AI models, all without the need for manual code creation.
  • In March 2023, a transformative collaboration was revealed as Google AI and Walmart joined forces to pioneer AI-driven retail solutions. This strategic partnership is set to propel the development of innovative AI algorithms aimed at enhancing customer experiences, streamlining inventory management, and tailoring personalized product recommendations.
  • In April 2023, a groundbreaking partnership was unveiled as Microsoft AI and Kroger teamed up to advance the world of AI-driven retail solutions. This strategic collaboration will focus on the creation of innovative AI algorithms designed to enhance customer experiences, streamline inventory management, and deliver personalized product recommendations.
  • In March 2023, NVIDIA introduced a game-changing solution with the release of NVIDIA AI Enterprise for Manufacturing, a comprehensive suite of AI software meticulously fine-tuned for utilization on NVIDIA's GPUs. This software holds the potential to enhance manufacturing operations, minimize downtime, and refine quality control processes.

Artificial Intelligence in Applications Market Scope

Report Components Details
Base Year

2022

Forecast Period

2023 – 2030

Quantitative Units

Revenue in US $ 

Drivers
  • Rising Demand for Automation
  • Data Proliferation and Analytics Needs
  • Advancements in AI Technologies
  • Decreasing Cost of AI Implementation
Challenges
  • Data Privacy and Security Concerns
  • Lack of AI Expertise
  • Algorithmic Bias and Explainability Issues
  • Limited Adoption in Traditional Industries
Trends
  • AI for Personalized Customer Experiences
  • AI for Predictive Maintenance and Asset Management
  • AI for Fraud Detection and Risk Management
  • AI for Drug Discovery and Medical Diagnosis
Segments Covered

Application (Finance, Healthcare, Manufacturing, Retail), By Technology (Machine Learning (ML), Natural Language Processing (NLP), Computer Vision, Context-Aware Computing), By Deployment (On-premise, Cloud Based, Hybrid

Countries Covered

U.S. and Canada in North America, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, Rest of Europe in Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the APAC, Others include Saudi Arabia, U.A.E, South Africa, Egypt, Israel, Rest of Middle East and Africa (MEA), Brazil, Argentina, Mexico, and Rest of South America as part of South America

Market Players Covered

Google, Amazon, Microsoft, IBM, NVIDIA, Apple, Meta, Salesforce, Adobe, SAP, Oracle, Tencent, Baidu, Alibaba, JD.com, Huawei, Sense Time, Uipath, Palantir, C3.ai

Table of Contents

1 INTRODUCTION OF GLOBAL ARTIFICIAL INTELLIGENCE IN APPLICATIONS MARKET

1.1 Overview of the Market

1.2 Scope of Report

1.3 Assumptions

 

2 EXECUTIVE SUMMARY

 

3 RESEARCH METHODOLOGY

3.1 Data Mining

3.2 Validation

3.3 Primary Interviews

3.4 List of Data Sources

 

4 GLOBAL ARTIFICIAL INTELLIGENCE IN APPLICATIONS MARKET OUTLOOK

4.1 Overview

4.2 Market Dynamics

4.2.1 Drivers

4.2.2 Restraints

4.2.3 Opportunities

4.3 Porters Five Force Model

4.3.1. Bargaining Power of Suppliers

4.3.2. Threat of New Entrants

4.3.3. Threat of Substitutes

4.3.4. Competitive Rivalry

4.3.5. Bargaining Power among Buyers

4.4 Value Chain Analysis

 

5 GLOBAL ARTIFICIAL INTELLIGENCE IN APPLICATIONS MARKET, BY APPLICATION

5.1 Overview

5.2 Healthcare

5.3 Finance

5.4 Manufacturing

5.5 Retail

6 GLOBAL ARTIFICIAL INTELLIGENCE IN APPLICATIONS MARKET, BY TECHNOLOGY

6.1 Overview

6.2 Machine Learning (ML)

6.3 Natural Language Processing (NLP)

6.4 Computer Vision

6.5 Context-Aware Computing

7 GLOBAL ARTIFICIAL INTELLIGENCE IN APPLICATIONS MARKET, BY DEPLOYMENT

7.1 Overview

7.2 On-Premises

7.3 Cloud-Based

7.4 Hybrid

8 GLOBAL ARTIFICIAL INTELLIGENCE IN APPLICATIONS MARKET, By REGION

8.1 North America

8.1.1 U.S.

8.1.2 Canada

8.2 Europe

8.2.1 Germany

8.2.3 U.K.

8.2.4 France

8.2.5 Rest of Europe

8.3 Asia Pacific

8.3.1 China

8.3.2 Japan

8.3.3 India

8.3.4 South Korea

8.3.5 Singapore

8.3.6 Malaysia

8.3.7 Australia

8.3.8 Thailand

8.3.9 Indonesia

8.3.10 Philippines

8.3.11 Rest of Asia Pacific

8.4 Others

8.4.1 Saudi Arabia

8.4.2 U.A.E.

8.4.3 South Africa

8.4.4 Egypt

8.4.5 Israel

8.4.6 Rest of Middle East and Africa (MEA)

8.4.7 Brazil

8.4.8 Argentina

8.4.9 Mexico

8.4.10 Rest of South America

9 COMPANY PROFILES

9.1 Google

9.1.1. Company Overview

9.1.2. Key Executives

9.1.3. Operating Business Segments

9.1.4. Product Portfolio

9.1.5. Financial Performance (As per availability)

9.1.6 Key News

 

9.2 Microsoft

9.2.1. Company Overview

9.2.2. Key Executives

9.2.3. Operating Business Segments

9.2.4. Product Portfolio

9.2.5. Financial Performance (As per availability)

9.2.6. Key News

 

9.3 Amazon

9.3.1. Company Overview

9.3.2. Key Executives

9.3.3. Operating Business Segments

9.3.4. Product Portfolio

9.3.5. Financial Performance (As per availability)

9.3.6. Key News

 

9.4  IBM

9.4.1. Company Overview

9.4.2. Key Executives

9.4.3. Operating Business Segments

9.4.4. Product Portfolio

9.4.5. Financial Performance (As per availability)

9.4.6. Key News

 

9.5 NVIDIA

9.5.1. Company Overview

9.5.2. Key Executives

9.5.3. Operating Business Segments

9.5.4. Product Portfolio

9.5.5. Financial Performance (As per availability)

9.5.6. Key News

 

9.6 Apple

9.6.1. Company Overview

9.6.2. Key Executives

9.6.3. Operating Business Segments

9.6.4. Product Portfolio

9.6.5. Financial Performance (As per availability)

9.6.6. Key News

 

9.7 Meta

9.7.1. Company Overview

9.7.2. Key Executives

9.7.3. Operating Business Segments

9.7.4. Product Portfolio

9.7.5. Financial Performance (As per availability)

9.7.6. Key News

 

9.8 Salesforce

9.8.1. Company Overview

9.8.2. Key Executives

9.8.3. Operating Business Segments

9.8.4. Product Portfolio

9.8.5. Financial Performance (As per availability)

9.8.6. Key News

 

9.9 Adobe

9.9.1. Company Overview

9.9.2. Key Executives

9.9.3. Operating Business Segments

9.9.4. Product Portfolio

9.9.5. Financial Performance (As per availability)

9.9.6. Key News

 

9.10 SAP

9.10.1. Company Overview

9.10.2. Key Executives

9.10.3. Operating Business Segments

9.10.4. Product Portfolio

9.10.5. Financial Performance (As per availability)

9.10.6. Key News

 

9.11 Oracle

9.11.1. Company Overview

9.11.2. Key Executives

9.11.3. Operating Business Segments

9.11.4. Product Portfolio

9.11.5. Financial Performance (As per availability)

9.11.6. Key News

 

9.12 Tencent

9.12.1. Company Overview

9.12.2. Key Executives

9.12.3. Operating Business Segments

9.12.4. Product Portfolio

9.12.5. Financial Performance (As per availability)

9.12.6. Key News

 

9.13 Baidu

9.13.1. Company Overview

9.13.2. Key Executives

9.13.3. Operating Business Segments

9.13.4. Product Portfolio

9.13.5. Financial Performance (As per availability)

9.13.6. Key News

 

9.14  Alibaba

9.14.1. Company Overview

9.14.2. Key Executives

9.14.3. Operating Business Segments

9.14.4. Product Portfolio

9.14.5. Financial Performance (As per availability)

9.14.6. Key News

 

9.15 JD.com

9.15.1. Company Overview

9.15.2. Key Executives

9.15.3. Operating Business Segments

9.15.4. Product Portfolio

9.15.5. Financial Performance (As per availability)

9.15.6. Key News

 

9.16 Huawei

9.16.1. Company Overview

9.16.2. Key Executives

9.16.3. Operating Business Segments

9.16.4. Product Portfolio

9.16.5. Financial Performance (As per availability)

9.16.6. Key News

 

9.17 Sense Time

9.17.1. Company Overview

9.17.2. Key Executives

9.17.3. Operating Business Segments

9.17.4. Product Portfolio

9.17.5. Financial Performance (As per availability)

9.17.6. Key News

 

9.18 Uipath

9.18.1. Company Overview

9.18.2. Key Executives

9.18.3. Operating Business Segments

9.18.4. Product Portfolio

9.18.5. Financial Performance (As per availability)

9.18.6. Key News

 

9.19 Palantir

9.19.1. Company Overview

9.19.2. Key Executives

9.19.3. Operating Business Segments

9.19.4. Product Portfolio

9.19.5. Financial Performance (As per availability)

9.19.6. Key News

 

9.20 C3.ai

9.20.1. Company Overview

9.20.2. Key Executives

9.20.3. Operating Business Segments

9.20.4. Product Portfolio

9.20.5. Financial Performance (As per availability)

 

9.20.6. Key News

Global Artificial Intelligence in Applications Market Segmentation

Artificial Intelligence in Applications by Technology: Market Size & Forecast 2023-2030

  • Machine Learning (ML)
  • Natural Language Processing (NLP)
  • Computer Vision
  • Context-Aware Computing

Artificial Intelligence in Applications by Deployment: Market Size & Forecast 2023-2030

  • On-Premise
  • Cloud-Based
  • Hybrid

Artificial Intelligence in Applications by Application: Market Size & Forecast 2023-2030

  • Finance
  • Healthcare
  • Manufacturing
  • Retail

Artificial Intelligence in Applications by Geography: Market Size & Forecast 2023-2030

  • North America (USA, Canada, Mexico)
  • Europe (Germany, UK, France, Russia, Italy, Rest of Europe)
  • Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Rest of Asia-Pacific)
  • South America (Brazil, Argentina, Columbia, Rest of South America)
  • Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria, South Africa, Rest of MEA)

Major Players:

  • Google
  • Amazon
  • Microsoft
  • IBM
  • INVIDIA
  • Apple
  • Meta
  • Salesforce
  • Adobe
  • SAP
  • Oracle
  • Tencent
  • Baidu
  • Alibaba
  • com
  • Huawei
  • Sense Time
  • Uipath
  • Palantir
  • ai

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