Composite AI Market

The global Composite AI Market is valued at USD 0.96 Billion in 2023 and is projected to reach a value of USD 14.9 Billion by 2032 at a CAGR (Compound Annual Growth Rate) of 35.6% between 2024 and 2032. The global market is driven by the increasing demand for advanced data analytics, the need for enhanced decision-making capabilities, and the integration of multiple AI technologies like Machine Learning & Natural Language Processing.

Key Highlights

• In 2023, North America dominated the market, with 35.2% market share, driven by the strong government support for AI adoption, substantial investments in research and development, and the presence of leading technology companies and academic institutions
• The product design and development segment is anticipated to account for 26.3% of the market share during the forecast period due to the growing need for innovative AI-driven solutions that can enhance product lifecycle management, optimize design processes, and accelerate time-to-market
• Based on Vertical, the BFSI segment is projected to maintain its dominance in the global market, driven by growing adoption of advanced technologies like artificial intelligence, machine learning, and data analytics is transforming the BFSI sector
• The rise of generative AI, which includes models like GPT (Generative Pre-trained Transformer), is driving the market growth. Generative AIs ability to create new content, generate human-like text, and perform advanced data synthesis is being integrated with other AI technologies to enhance decision-making and automation processes

Application Overview

Based on Application, the global market is segmented into Product Design & Development, Quality Control, Predictive Maintenance, Security & Surveillance, Customer Service, and Other Applications (Fraud Detection & Prevention and Supply Chain Management). In 2023, The product design and development segment is expected to account for 26.3% of the market share during the forecast period.

Product design & development applications are crucial in driving the implementation of Composite AI solutions in the market. These applications offer tools & functionalities that foster innovation by generating new ideas and concepts. They empower businesses to explore novel product opportunities and pinpoint where Composite AI can deliver the most value. Leveraging Composite AI in product design & development provides significant advantages, including enhanced product development capabilities, cost reduction, and more efficient market entry for innovative products.

Customer service is a key application area for Composite AI, where AI-powered chatbots & virtual assistants provide round-the-clock support and handle routine inquiries. Fraud detection is another expanding field, with businesses employing AI algorithms to detect and prevent fraudulent transactions. In risk management, AI is utilized to evaluate and mitigate risks related to investments, loans, & other financial activities. Supply chain management also benefits from Composite AI, as companies use AI to optimize logistics, forecast demand, and manage inventory. Top companies in the Composite AI market are focused on integrating this technology. For example, Amazon uses Composite AI to tailor product recommendations, while Netflix leverages it to suggest movies and TV shows that align with customer preferences.

Regional Overview

North America dominated the global market with a revenue share of 35.2% in 2023. This is driven by strong government support for AI adoption across various sectors. Governments in the region actively promote AIs transformative potential by funding research & development, offering tax incentives, and establishing AI centers of excellence. The region boasts a robust R&D ecosystem, with world-class universities, research institutions, and companies collaborating to advance AI technologies. For example, in November 2023, the US Department of Commerces National Institute of Standards and Technology (NIST) invited contributions to a new initiative aimed at developing innovative methods for evaluating AI systems and enhancing the reliability of rapidly evolving technologies.

The Asia Pacific region is swiftly embracing AI in edge computing, with countries such as China, South Korea, & India at the forefront. The rising use of IoT devices and the need for real-time data processing in the region are propelling the demand for edge AI solutions. In China, edge AI is being utilized to manage traffic flow, optimize energy usage, and enhance public safety in urban areas.

Key Trends

1. Integration of Multi-Model AI Systems: Increasing use of diverse AI technologies, such as Machine Learning, Natural Language Processing, and knowledge graphs, to enhance decision-making and insights.
2. Rise of Generative AI: Growing adoption of generative AI techniques for creating new data, automating content generation, and improving model accuracy.
3. Enhanced Data Privacy and Security: Development of AI solutions with built-in privacy and security features to protect sensitive information and comply with regulatory requirements.
4. Expansion in Industry Applications: Broadening applications of Composite AI across sectors like finance, healthcare, and retail for tailored solutions and improved operational efficiency.
5. Advancements in AI Algorithms and Techniques: Continuous evolution of AI algorithms, leading to more powerful and sophisticated Composite AI systems capable of handling complex data tasks.
6. Increased Focus on Real-Time Analytics: Demand for real-time data processing and analytics to drive quick, informed decision-making and enhance business agility.
7. Growth of Cloud-Based AI Solutions: Rising preference for cloud-based Composite AI solutions due to their scalability, flexibility, and cost-effectiveness.

Market Dynamics

Enhancing Performance and Accuracy with Composite AI Solutions

AI applications are increasingly complex, necessitating the integration of multiple AI technologies and models to address sophisticated challenges. While machine learning (ML) effectively handles many classification and recognition tasks, it often falls short for problems requiring deeper understanding. Additionally, MLs demands for extensive training data and computational resources can be prohibitive. Composite AI solutions address these limitations by combining diverse AI algorithms and components, enhancing performance and accuracy. By leveraging the strengths of various AI models & techniques, Composite AI enables organizations to achieve more robust, precise results and improve decision-making and problem-solving capabilities.

Leveraging Composite AI in Edge Computing

The rise of Internet of Things (IoT) devices and the demand for real-time decision-making are accelerating the use of edge computing. By integrating Composite AI solutions with edge devices, data can be processed and analyzed locally, which minimizes latency and allows for quicker insights and responses. This integration opens up opportunities for deploying Composite AI in edge computing scenarios. Edge computing supports intelligent applications & 5G/6G IoT networks by offering benefits like reduced latency, rapid responses, context-aware services, mobility, and enhanced privacy. It extends the cloud by providing intermediate services closer to the network edge, thus improving service quality for applications sensitive to latency. The integration of emerging technologies such as IoT, wireless sensor networks (WSNs), cloud/edge computing, & 5G/6G communication networks across sectors like healthcare, agriculture, education, & transportation can enhance quality of life by creating intelligent systems that offer high-quality, innovative services.

Overcoming Barriers to Composite AI Adoption

Organizations may be hesitant to adopt Composite AI solutions due to a lack of trust in AI technology or insufficient understanding of its capabilities and limitations. Concerns about data privacy, security, & potential biases in AI models can also hinder implementation. Privacy issues primarily involve data breaches and unauthorized access to personal information. As data is collected and processed for insights, the risk of it falling into the wrong hands increases, leading to potential breaches. Advancements in AI technology may further exacerbate these risks, as generative AI could be misused to create fake profiles or unauthorized images. According to recent statistics, cybercrimes impact the security of 80% of businesses globally, with severe consequences if personal data is compromised.

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Competitive Landscape

The global market is a rapidly advancing sector, characterized by the emergence of several leading players who are shaping its future. Companies in the global market have also employed a range of growth strategies to enhance their market position. Such strategies include launching new products, upgrading existing ones, forming partnerships and agreements, expanding their business operations, and engaging in mergers & acquisitions.

For example, in May 2022, BlackSwan Technologies, a leading cloud enterprise software provider, has announced a strategic partnership with Refinitiv, a prominent provider of financial crime data and an LSEG business. This collaboration will drive next-generation customer risk assessment by integrating advanced compliance solutions with extensive financial crime data and cutting-edge AI technologies for KYC, transaction monitoring, and screening.

For example, in November 2022, Squirro has unveiled a strategic global partnership with the Semantic Web Company, a knowledge graph specialist, to launch an innovative Composite AI solution. This groundbreaking Composite AI solution uniquely integrates Machine Learning (ML), Natural Language Processing (NLP), and knowledge graph technology, offering enterprises a comprehensive tool for intelligent decision-making. It combines content from various sources with user intent & context to enhance decision-making, providing personalized results tailored to individual needs and delivering them precisely when required.

Recent Market Developments

SAS Unveils SAS Decision Builder on Microsoft Fabric

• In July 2024, SAS, a leader in data and AI, has introduced SAS Decision Builder in private preview on Microsoft Fabric. This cloud-based intelligent decisioning solution leverages SAS’s advanced decisioning capabilities to enhance customer decision-making by integrating various AI models, rules, and procedural logic into a unified workflow.

Pegasystems Launches Pega GenAI Knowledge Buddy

• In January 2024, Pegasystems Inc., a leading provider of enterprise AI decisioning and workflow automation platforms, has unveiled Pega GenAI Knowledge Buddy, an advanced generative AI assistant designed to provide precise answers by synthesizing information from dispersed knowledge bases.

Squirro and BioQuest Forge Strategic Partnership to Expand Generative AI Insights in the APAC Region

• In December 2023, Squirro and BioQuest have announced a strategic partnership to advance Generative AI-driven insights and data analytics projects throughout the APAC region. This alliance highlights Squirros dedication to expanding its presence in the APAC region and utilizing BioQuests expertise to strengthen its knowledge graph capabilities, consultancy services, and implementation efforts.

Oracle Introduces AI Vector Search in Oracle Database 23c

• In September 2023, Oracle has announced plans to incorporate semantic search capabilities with AI vectors into Oracle Database 23c. This new feature set, named AI Vector Search, introduces a vector data type, vector indexes, and vector search SQL operators. These enhancements will allow the Oracle Database to store the semantic content of documents, images, and other unstructured data as vectors, facilitating rapid similarity searches.

UiPath Enhances Enterprise Automation with New AI-Driven Features

• In June 2023, UiPath, a leading provider of enterprise automation software, has unveiled its latest AI-driven automation features. These innovations leverage Generative AI & Specialized AI to enhance customers' capabilities in discovering, automating, and managing large-scale automation solutions.

Pegasystems Releases Pega GenAI

• In May 2023, Pegasystems Inc., a leader in low-code platforms that help top enterprises to Build for Change, has announced Pega GenAI. This suite of 20 new generative AI-powered tools will be integrated into Pega Infinity ‘23, the latest iteration of Pega’s product suite designed for AI-driven decision-making and workflow automation.

Squirro Launches New Enterprise-Grade Generative AI Solution

• In March 2023, Squirro, a provider of Augmented Intelligence solutions, has introduced a new enterprise-grade Generative AI (GenAI) solution. This innovation delivers the advantages of GenAI to enterprises while addressing common challenges associated with enterprise GenAI. Squirro’s solution integrates Large Language Models (LLMs) with its own Composite AI technology, which combines various AI methods like Machine Learning and Knowledge Graphs to generate insights, and its Insight Engine technologies.

The global Composite AI market can be categorized as Offering, Technique, Application, Vertical, and Region.