AI engineering is a process of designing and developing AI systems that can perform tasks that ordinarily require human intelligence, such as reasoning, natural communication, and problem-solving. The AI engineering market is driven by the increasing demand for AI-enabled products and services, advances in AI technology, and the need for efficient AI development tools. However, the high cost of AI development tools and the lack of skilled AI engineers have been expected to restrain the growth of this market. The global AI engineering market is segmented on the basis of component, application, end-use industry, and geography. Based on components, it is divided into software and hardware. By application, it includes predictive maintenance & quality control, supply chain management & logistics, product development & design optimization, human resource management & training optimization, customer relationship management & marketing optimization, and others.
Market Overview
The increasing demand for AI-enabled devices and applications, and the need for efficient data management are some of the major factors driving the growth of the AI engineering market. Moreover, the increasing adoption of cloud computing and big data analytics is providing a boost to market growth.
However, the lack of a skilled workforce is restraining market growth. In addition, the high initial investment required for implementing AI solutions is another factor hampering the market growth.
The global AI engineering market is segmented based on component, application, end-user, and geography. Based on components, the market includes software tools and platforms. The software tools segment is expected to grow at a rapid pace during the forecast period owing to the increasing demand for the development and deployment of AI-based applications.
Based on application, the market includes Predictive Maintenance, Predictive Quality Control & Visual Inspection, Process Automation & Optimization, Inventory Management & Tracking, and Others (including Customer Relationship Management (CRM), Security & Surveillance). Among these applications, predictive maintenance is expected to hold a significant share in terms of revenue in 2018 as it helps in reducing downtime and maintenance costs by detecting potential failures before they occur.
Segmentation Analysis:
The global Artificial Intelligence (AI) Engineering market is segmented based on use case. Public cloud is mainly used for transaction processing, system management, and data warehousing whereas private cloud is used for application development and deployment. Organizations are increasingly adopting private clouds to achieve cost advantages and improve agility.
Private clouds offer scalability, flexibility, and privacy compared to public clouds. They also allow organizations to manage their own resources more effectively. Private clouds are becoming an important part of the IT infrastructure for financial institutions because they can improve operational efficiency and reduce costs. The growth of the private cloud in the financial services market is driven by increased demand from businesses for faster innovation cycles, improved security, and ability to scale quickly.
Global Artificial Intelligence (AI) Engineering market Competitive Analysis:
Key players in the Global Artificial Intelligence (AI) Engineering market are Microsoft Corp, Intel Corp, Oracle Corporation, Alphabet Inc, IBM Corp, Nvidia Corp, Cisco Systems, Baidu Inc, Verint Systems, Salesforce.com Inc, Meta Platforms Inc, SAP SE, Dolbey Systems, People.ai, Netbase Solutions, Lexalytics, Siemens AG and among other players.
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