Explainable AI Market Rising Trends, Technology Research and Precise Outlook 2021-2030

The Global Explainable AI (XAI) Market size is estimated to be USD 3.55 billion in 2019 and is predicted to reach USD 21.78 billion by 2030 with a CAGR of 20.1% from 2020-2030.

Explainable AI is a method/technique in the space of artificial intelligence, where the solution can be analyzed and understood by humans. It is different than the traditional machine learning techniques, where developers are often fail to understand why the system has arrived at a specific decision. Explainable AI is gaining traction from industries such as healthcare, retail, media & entertainment, and aerospace & defense. For instance, the use of explainable AI or XAI in the retail industry is imperative for predicting upcoming trends in fashion along with reason, and that would allow the retailers to stock and display the latest merchandise in their store. In addition, the concept of recommendation engines in the e-commerce industry is an example of explainable AI, where the system recommends products to the customer based on his/her search history. Further, recommendation engines also suggest accessories/additional products along with the product being selected for purchase. This is done with the help of explainable AI, where the system suggests products that are useful to the customer.

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Competitive Landscape

The global explainable AI market is marked by intense competition by the major players operating in this space. Tactical mergers & acquisitions, joint ventures & partnerships, technological innovations are some of the key strategies taken up by the major players in order to ensure long term sustenance in this industry. DataRobot, Factmata, DarwinAI, IBM Corporation, Google LLC, Microsoft Corporation, and Ditto.ai among others are some of the key players operating in this space.

In May 2020, DawrinAI announced a strategic collaboration with Lockheed Martin in order to improve the latter’s customer understanding of AI solutions

Market Dynamics and Trends

Explainable AI offers significant benefits such as higher customer retention rate, and better inventory management. Understanding the weakness of a model is a major way to maximize its performance. Better understanding of the models and reason for their failure makes it easier to improve them. Using explainable AI is a powerful way to detect flaws in the system and remove biases in the data, resulting in increased trust among the users. Explainable AI helps in verifying predictions in order to fine tune models, and gain newer insights to solve the problem at hand.

Fraud detection is a major application area of explainable AI. Explainable AI is useful to predict fraudulent attacks and determine which attack has a higher degree of threat. Cyber-attacks have become smarter over the years. For instance, in April 2019, approximately 540 million Facebook profiles were leaked, and were published on Amazon’s cloud computing service by third-party app developers. This is an example where explainable AI can be used to understand why and how this incident happened, in order to protect user information in the future. Moreover, on 3rd July 2020, National Highways Authority of India (NHAI) was struck with a cyber-attack resulting in the loss of a huge amount of data stored in its server. This attack was a result of a weak cyber infrastructure. Such increasing number of attacks all over the world are creating demand for explainable AI in areas such as fraud detection among others. The growing demand for explainable AI has attracted major investments in recent time. For instance, in 2019, Fiddler Labs managed to bag a funding of USD 10.2 Mn by Lightspeed Ventures and Lux Capital. This funding has helped the company to take its total funding to reach USD 13.2 Mn since 2018.

However, greater deployment costs for explainable AI is a major factor barring the growth of the market. High capital investment is a major reason why most companies find it difficult to implement such technologies in their systems.

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Market Segmentations and Scope of the Study:

The global market for explainable AI is segmented on the basis of offering into solutions and services. Based on deployment, the market for explainable AI is segmented into cloud and on-premise. Based on technology, the explainable AI market is segmented into machine learning, natural language processing, contextual awareness and others. Based by application, the explainable AI market is segmented into fraud detection, drug discovery, predictive maintenance, social media advertising, identity and access management, recommendation engines and supply chain management among others. Further, based on end-use industry, the explainable AI market is segmented into telecom, healthcare, BFSI, public sector, retail, logistics, aerospace & defense, and media & entertainment among others. Moreover, based on region, the explainable AI market is segmented into North America, Europe, Asia Pacific, and Rest of the World.

Geographical Analysis

North America and Europe led the global market for explainable AI and is expected to retain their positions during the forecast period as well. Strong IT infrastructure in the developed nations such as the U.S., Germany, U.K., France, Japan, and Canada is a major factor supporting growth of the explainable AI market in these countries. In addition, strong support from the governments in these countries in order to ramp the IT infrastructure is another factor boosting market growth of explainable AI in these countries. However, developing nations such as China, and India are expected to display a higher growth during the forecast period. Favorable economic growth in these countries are attracting a lot of investments in these countries that are suitable for the expansion of explainable AI market.

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