Adaptive AI Market - Forecasts from 2024 to 2029

The Adaptive AI market is expected to grow at a CAGR of 44.71% reaching a market size of US$12,534.54 million in 2029 from US$943.05 million in 2022.

Reinforcement learning, transfer learning, and neural architecture search are a few approaches used in adaptive AI. Some examples of adaptive AI applications include self-driving cars that adjust to varying road conditions, healthcare systems that update diagnoses with fresh information, and targeted advertising campaigns influenced by consumer behaviour.

Adaptive AI produces quicker, better results by learning behavioural patterns from previous human and machine experience as well as from runtime situations. According to the AI index report published in 2023, corporate investment in AI is based on various activities including Merger/Acquisition, Minority Stake, Private Investment, and Public Offering. The total investment for the year 2019 was 95.63 billion dollars, which surged to 276.14 billion dollars in the year 2021. This investment growth is anticipated to be fueled by the growing adoption of adaptive AI.

Increase in demand for artificial intelligence

Artificial intelligence has proven to be a powerful instrument that can drastically change businesses across many industries. However, traditional machine learning models have found it challenging to adapt to the dynamic nature of our rapidly changing environment, which has limited their capacity to handle the volume of data generated by the Internet of Things (IoT) and autonomous cars. Adaptive AI is a significant advancement in artificial intelligence because it is capable of continuous learning. Adaptive AI models can instantly change and adapt when new data becomes available. Businesses can effectively address the challenges posed by our constantly changing data landscape thanks to adaptive AI's dynamic nature.

The market is also expanding as a result of the rising demand for AI systems with greater intelligence. Adaptive AI combines reinforcement learning with agent-based modelling to drive business growth. This unique blend enables real-time response to external changes even in production settings. As an example, consider the U.S. Army's adaptive AI system, which adapts learning processes to meet a range of needs. It acts as a personalized tutor, assesses strengths, optimizes teaching strategies, and measures progress effectively.

High demand from financial institutions

Throughout the forecast period, the financial industries' widespread use of adaptive AI is driving market growth. Financial institutions are constantly at risk from fraudulent activity. The capacity of adaptive AI to analyze massive amounts of data, identify trends, and identify anomalies in real time enables proactive fraud detection and prevention. Furthermore, adaptive AI systems may offer highly customized banking experiences through the analysis of consumer data. Through customized product recommendations and individualized financial advice, adaptive AI raises client satisfaction and engagement.

Rising use in the healthcare industry

One of the most groundbreaking innovations in the rapidly evolving field of healthcare is the introduction of adaptive AI. Artificial intelligence (AI) technology is integrated into healthcare procedures to improve diagnosis and treatment processes. Over time, AI continuously learns, changes, and improves. Using sophisticated algorithms and machine learning techniques, adaptive AI refines its predictions and recommendations by analyzing and learning from vast amounts of medical data. These systems' dynamic nature may allow them to continuously enhance their functionality, resulting in more accurate and customized healthcare outcomes. The sections that follow include in-depth talks of Adaptive AI's uses in healthcare as well as an examination of how this technology is changing modern medicine.

Rising technological development

Deep learning and reinforcement learning are two recent advances in machine learning algorithms that help these systems operate more effectively and efficiently. These algorithms provide AI models the ability to learn from intricate data patterns, adjust to a variety of settings, and produce more accurate predictions. The expansion of natural language processing techniques in applications involving human-machine interaction is facilitated by advancements in this field. Additionally, these systems have an abundance of training data due to the availability of large and diverse datasets. As a result, these systems can learn from a variety of examples, enhancing their capacity for pattern recognition, prediction, and context adaptation. These systems can adjust their models to fit particular scenarios thanks to the availability of domain-specific data. With all of the data being produced by the digital ecosystem, the market is primed for more expansion and innovation.

Growing popularity of adaptive games

Modern PCs and game consoles are now widely accessible to stream games directly to end devices, liberating them from the constraints of running on local hardware. These technological advancements form the foundation of adaptive AI. This makes it possible for games to use the cloud's computer capacity to allow more advanced AI behaviour, especially when it comes to gaming visuals. Furthermore, as per the World Economic Forum, the global video game revenue increased from 2022 to 2023. The revenue for social/casual games which is growing the fastest was 167 billion dollars in the year 2022, which increased to 185.8 billion in the year 2023. Similarly, the revenue for PC games in the year 2022 was 35.2 billion dollars which surged to 36.9 billion dollars in 2023 owing to the growing adoption of adaptive AI.

North America is witnessing exponential growth during the forecast period

The use of adaptive AI over traditional AI is increasing in multiple end-user industries in the US, as adaptive AI can revise its codes according to the changes in real-time situations. Various companies are launching new and innovative products in the market to use adaptive AI to make the maximum out of it. For instance, in July 2023, Workday, a California-based company launched Workday Adaptive Planning. The company is a leader in enterprise cloud applications for human resources and finance. The technology Elastic Hypercube Technology (EHT) Is patented by the company, as it will help the company to address the growing demand for complex business scenarios, expand planning, and change business needs. Therefore, such product launches in the market are anticipated to propel the adaptive AI market in the forecasted period.

Market key launches

• In January 2024, to provide SMBs and large enterprises with Generative AI capabilities, Adaptive Computing Enterprises, Inc. announced the launch of its adaptive. ai-as-a-service offering. This product is an end-to-end platform for developing AI and ML applications. It comes with robust web-browser management software, more than 120 HPC and AI/ML application packages and tools, and streamlined GPU infrastructure deployment for a monthly fee that is all-inclusive and significantly less expensive than other generative AI delivery options on the market.
• In January 2024, Squirrel Ai, a Chinese education technology company, recently unveiled what it called the world's first adaptive learning large model spanning major subjects. Now, the company plans to bring its AI-enabled products to international users by year's end. "By the end of this year, Squirrel AI is anticipated to provide new goods and services to customers worldwide. In order to support educational equity, we will also provide the Squirrel Ai system at no cost to 20% of children from the world's lowest-income families, according to Li Haoyang, chairman of Squirrel Ai.

Segmentation:

By Component

• Platform
• Services

By Deployment

• Cloud
• On-Premises

By Application

• Machine Learning
• Natural Language Processing (NLP)
• Predictive Analysis
• Personalization
• Adaptive Testing
• Others

By Industry

• Healthcare
• Finance
• Education
• Manufacturing
• Environmental Sustainability
• Others

By Geography

• North America
• United States
• Canada
• Mexico
• South America
• Brazil
• Argentina
• Others
• Europe
• Germany
• United Kingdom
• France
• Spain
• Others
• Middle East and Africa
• Saudi Arabia
• UAE
• Israel
• Others
• Asia Pacific
• China
• Japan
• India
• South Korea
• Indonesia
• Taiwan
• Others