Artificial intelligence (AI) is the ability to process information in a way similar to the thought process of humans in learning, decision making, and problem solving. AI in enterprises is rapidly moving beyond hype and is expected to become one of the most significant technological segments. Enterprises are now identifying the value associated with integrating AI into their business processes. AI can be beneficial to enterprises in a number of ways that changes the way in which organizations communicate & innovate their processes, engage with customers, and assess the sales process. The number of commercial deployments of AI technology is rising significantly around the globe. Throughout the last few years, early adopting businesses of all sizes across various verticals began to reap benefits. Some of the key industry sectors already utilizing artificial intelligence include government, retail, financial services, manufacturing, automotive, and advertising.
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Digital transformation to artificial intelligence helps enterprises in understanding extortion of data and utilization of data-driven intelligence. Extensive adoption of AI in enterprises is because majority of tasks which are delegated to AI are data-driven and therefore it can be easily measured or benchmarked. AI can take many different forms, from problem-solving applications and reasoning to social intelligence solutions and natural language generation. These techniques layered together form the AI solutions that are seeing early adoption in enterprises. Specifically, predictive analytics which uses machine learning, data mining, statistics and modeling to analyze current data and to make predictions is the most commonly used solution.
The rising demand for AI-based cognitive solutions and the requirement for analyzing complex data sets in data sensitive companies are on a robust growth trajectory. Significant improvement in machine learning algorithms is also responsible for large scale adoption of AI solutions in enterprises. Growing demand for enhancing business functions and emerging innovation across industries are creating growth opportunities for enterprise AI. However, lack of skilled labor and concerns about data sharing are estimated to hinder the growth of the market. Furthermore, the slow digitization rate affecting the adoption of enterprise AI solutions in the emerging economies is also expected to act as a restraint to the growth of the enterprise AI market.
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The global enterprise AI market can be segmented based on component, technology, application, organization size, and region. On the basis of component, the market can be segmented into software (cloud-based and on-premise) and services (managed and professional services). The cloud deployment type offers various benefits that include more scalability, reduced operational and maintenance costs, and fewer complexities. Enterprise AI vendors are focusing on the deployment of cloud-based solutions, owing to large scale adoption of the cloud-based deployment type. Based on technology, the global market can further be categorized into machine learning, deep learning, and Natural Language Processing (NLP). Furthermore, based on application, the market is categorized into security & risk management, process automation, analytics application, and marketing management. In terms of organization size, the market has been bifurcated into small and medium sized enterprises (SMEs), and large enterprises.