Adaptive AI Market Size, Share, Opportunities, And Trends By Component (Platform, Services), By Deployment (Cloud, On-Premise), By Application (Machine Learning, Natural Language Processing (Nlp), Predictive Analysis, Personalization, Adaptive Testing, Others), By End-User (Healthcare, Finance, Education, Manufacturing, Environmental Sustainability, Others), And By Geography - Forecasts From 2023 To 2028
- Published : Aug 2023
- Report Code : KSI061615868
- Pages : 142
Adaptive AI Market is expected to grow with a considerable share during the forecast period
The adaptive AI market is a cutting-edge section of the artificial intelligence (AI) market in which AI systems can adapt to and learn from new data and experiences. Unlike standard AI models, which require regular human interaction for updates and upgrades, adaptive AI systems may self-improve over time. Because of their versatility, these systems can handle complicated and dynamic activities, making them suitable for use in a variety of industries such as banking, healthcare, cybersecurity, and customer support. The adaptive AI market is seeing considerable development as organizations seek intelligent and agile AI solutions, driving innovation and redefining how AI technologies are deployed across sectors.
Growing Demand for Autonomous and Self-Learning Systems
The rising efficiency and flexibility of autonomous and self-learning systems are increasing the adaptive AI market size. According to a 2021 IDC survey, organizations that used autonomous technology saw a 40% decrease in operating expenses and a 30% improvement in productivity. Autonomous AI systems make processes more efficient and scalable, decreasing the need for ongoing human monitoring and decision-making. These technologies provide seamless decision-making and performance enhancements, increasing competitiveness across industries ranging from manufacturing to healthcare. Further, as data-driven technologies advance, demand for autonomous and self-learning systems is projected to rise even higher.
Expansion of AI Applications across Various Industries
The use of AI applications across numerous sectors has increased. AI technology is gradually being incorporated into a wide range of industries, including healthcare, finance, manufacturing, retail, and transportation. For instance, AI-driven fraud detection has shown a 40% boost in accuracy in the banking industry as per Forbes. AI-powered chatbots have reduced customer complaints by 60% in the retail business (IBM). AI is revolutionizing processes, increasing efficiency, and driving economic development in a variety of industries throughout the world, from manufacturing to customer service.
Integration of AI with the Internet of Things (IoT) and Big Data Analytics
The integration of AI with IoT and big data analytics is moving the adaptive AI market forward. Organizations may acquire huge volumes of real-time data from multiple sources by combining AI's strong analytical skills with IoT's linked network of devices and sensors. AI, IoT, and big data collaboration enable real-time data analysis, allowing smart decision-making and predictive capabilities. This integration has a positive impact on industries such as healthcare, where AI-powered IoT devices can remotely monitor patients, resulting in a 30% reduction in hospital readmissions as per Frost & Sullivan. The combination of these cutting-edge technology opens new avenues for innovation and change across many industries.
North America is projected to dominate the Adaptive AI Market.
North America is expected to dominate the adaptive AI market. The market’s expansion is due to the presence of large technology businesses and AI research institutes, considerable investments in AI development, a favourable legislative environment, and widespread AI use across industries. Furthermore, North America is a hub for a high number of AI-focused startups and organizations, resulting in the rapid progress and commercialization of adaptive AI solutions. The robust ecosystem and favourable market circumstances in the area make it a main centre for driving innovations and growth in the adaptive AI market.
Focus on Improving Customer Experience and Engagement
The importance of increasing customer experience and engagement is motivated by the fact that it has a substantial influence on company performance. Further, according to a Salesforce survey, 84% of customers feel that the experience a company gives is just as important as its products and services. Businesses are investing in adaptive AI technologies to analyse consumer data, personalize interactions, and provide timely assistance. A great customer experience increases loyalty and advocacy, which leads to higher customer retention and revenue growth, making it an important driver in the adoption of adaptive AI technology.
- In June 2023, Moody's Corporation and Microsoft Corporation launched a new strategic alliance to bring next-generation data, analytics, research, collaboration, and risk solutions to financial services and global knowledge workers. Based on a combination of Moody's robust data and analytical capabilities and the power and scale of Microsoft Azure OpenAI Service, the partnership creates innovative offerings that enhance insights into corporate intelligence and risk assessment, powered by Microsoft AI and anchored by Moody's proprietary data, analytics, and research.
- In July 2023, SAS India, the market leader in business analytics software and services, launched a two-year full-time Master of Business Administration (MBA) in Analytics programme with Sir Padampat Singhania University (SPSU). The primary goal of this program is to build abilities in data-driven decision-making, financial planning, quantitative analysis, policy development, interpersonal interactions, and an awareness of the expanding global economy in order to train future business leaders.
- In June 2023, Salesforce and Deloitte Digital established a partnership to equip organizations worldwide with the accelerators and strategies required to adopt trustworthy AI for CRM. Deloitte Digital will help organizations deploy and expand AI Cloud by using its AI services, industry experience, and in-depth understanding of data protection requirements. Salesforce and Deloitte Digital will collaborate to help clients leverage the potential of AI for CRM to offer personalized customer experiences, boost corporate efficiency, and protect their data.
- SAS Visual Data Mining and Machine Learning: Using a visual interface, this software enables data scientists and analysts to develop and deploy machine learning models. It features adaptive AI algorithms that can adapt to changing data patterns automatically, ensuring models remain accurate and relevant over time.
- Oracle Adaptive Intelligent Apps: This AI-powered application suite assists firms in automating and optimizing activities such as customer care, supply chain management, and marketing. Machine learning is used in the apps to adapt to changing patterns and user behavior, allowing them to provide more personalized and efficient experiences.
- Amazon SageMaker: Developers and data scientists may use this fully managed service to construct, train, and deploy machine learning models at scale. SageMaker's Adaptive AI features automate model tweaking and selection, allowing users to optimise their machine-learning workflows more easily.
- IBM Cloud Pak for Data: This AI-powered data and analytics platform gives organizations the tools they need to efficiently manage and analyses data. Adaptive AI is used in the platform to automate data preparation, analyses trends, and obtain insights, allowing organizations to make data-driven choices.
- By Component
- By Deployment
- By Application
- Machine Learning
- Natural Language Processing (Nlp)
- Predictive Analysis
- Adaptive Testing
- By Industry
- Environmental Sustainability
- By Geography
- North America
- South America
- United Kingdom
- Middle East and Africa
- Saudi Arabia
- Asia Pacific
- South Korea
- North America
1.1. Market Overview
1.2. Market Definition
1.3. Scope of the Study
1.4. Market Segmentation
1.7. Base, and Forecast Years Timeline
2. RESEARCH METHODOLOGY
2.1. Research Data
3. EXECUTIVE SUMMARY
3.1. Research Highlights
4. MARKET DYNAMICS
4.1. Market Drivers
4.2. Market Restraints
4.3. Porter’s Five Force Analysis
4.3.1. Bargaining Power of Suppliers
4.3.2. Bargaining Power of Buyers
4.3.3. Threat of New Entrants
4.3.4. Threat of Substitutes
4.3.5. Competitive Rivalry in the Industry
4.4. Industry Value Chain Analysis
5. ADAPTIVE AI MARKET, BY COMPONENT
6. ADAPTIVE AI MARKET, BY DEPLOYMENT
7. ADAPTIVE AI MARKET, BY APPLICATION
7.2. Machine Learning
7.3. Natural Language Processing (NLP)
7.4. Predictive Analysis
7.6. Adaptive Testing
8. ADAPTIVE AI MARKET, BY INDUSTRY
8.6. Environmental Sustainability
9. ADAPTIVE AI MARKET, BY GEOGRAPHY
9.2. North America
9.3. South America
9.4.3. United Kingdom
9.5. Middle East And Africa
9.5.1. Saudi Arabia
9.6. Asia Pacific
9.6.4. South Korea
10. COMPETITIVE ENVIRONMENT AND ANALYSIS
10.1. Major Players and Strategy Analysis
10.2. Emerging Players and Market Lucrativeness
10.3. Mergers, Acquisitions, Agreements, and Collaborations
10.4. Vendor Competitiveness Matrix
11. COMPANY PROFILES
11.2. Suffescom Solutions
11.6. Tech Mahindra
11.7. Cygnus Software
11.8. Ness Digital Engineering
Ness Digital Engineering
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