AI for security solutions includes the integration of endpoint data and analytics to obtain threat intelligence, which helps to detect and expose an attack in a particular environment. With the growth in online transactions and a surge in NEFT, RTGS, along with the mobile transactions are surging the demand for security solutions. Thus, the banking sector has observed a significant increase in the adoption of artificial intelligence based security solutions which have helped to enhance banking services. The artificial intelligence in security market is projected to witness to rise in the next few years, the key significant factors which include growing requirement of technologies such as artificial intelligence, machine learning and deep learning to tackle the emerging threats and advanced insistent threats which remains undiscovered within the network which steal the data, rising number of security breaches and growing BYOD trends has further steered the growth of artificial intelligence in security market during the forecast period. Since digital threats and cybercrimes are increasing in number, security requires to be improved. Security now requires continuous supervision and adaption to the present market scenarios. With an increase in connected devices, enterprises and applications, the businesses are becoming more prone as they are linked to a mass of independent endpoints. AI in security offers an attracting proposition with its proactive threat reduction abilities which is required for continuous supervision and adjustment to the multifaceted security vulnerabilities faced by modern digitalized economy. Furthermore, with the rising use of advanced techniques for cybercrimes, there is an increasing requirement for artificial intelligence based methods to counter the threats from malicious software bots. AI can be used to fight against various cyber threats such as watering hole attack, spear phishing, ransomware, webshell, DDoS attacks and remote exploitation, by identifying and avoiding them from proliferating into the systems. AI based security systems can inspect even those threats which have not happened in the past unlike conventional based security systems. However, the dearth of artificial intelligence skilled professionals will limit the market growth.

In addition to this, the rising adoption of cloud-based solutions and services and government support and investment in research and development of artificial intelligence technology are few of the major contributing factors in the creation of lucrative opportunities for the artificial intelligence in security market players in the coming years.

The global Artificial Intelligence (AI) in Security Market is segregated on the basis of Security Type as Network Security, Application Security and Cloud Security. Based on Service the global Artificial Intelligence (AI) in Security Market is segmented in Professional Services and Managed Services. Based on Deployment the global Artificial Intelligence (AI) in Security Market is segmented in On-premise and Cloud. Based on End-user Industry the global Artificial Intelligence (AI) in Security Market is segmented in Government & Defense, Retail, BFSI, Manufacturing, Healthcare, Automotive & Transportation and Other End-user Industries.

The global Artificial Intelligence (AI) in Security Market report provides geographic analysis covering regions, such as Europe, North America, Asia Pacific, and Rest of The World. The Artificial Intelligence (AI) in Security Market for each region is further segmented for major countries including the U.S., Canada, Germany, the U.K., France, Italy, China, India, Japan, Brazil, South Africa, and others.

Competitive Analysis

Nvidia Corporation, Intel Corporation, Samsung Electronics, IBM Corporation, Google and others are among the major players in the global Artificial Intelligence (AI) in Security Market. The companies studied in terms of product strategy and various n several growth and expansion strategies to gain a competitive edge in the market. The major players not only follow value chain integration with business operations in multiple stages of the value chain.

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