Explainable AI Market worth $16.2 billion by 2028 - Exclusive Report by MarketsandMarkets™

CHICAGO, Nov. 10, 2023 /PRNewswire/ -- The Explainable AI Market is expected to grow in the future because to the development of methodologies, increased standardisation, and wider applicability across various AI models and domains. XAI will be crucial in determining how artificial intelligence is used responsibly and ethically as the need for open, accountable systems of intelligence grows.

The global Explainable AI Market size is to grow from USD 6.2 billion in 2023 to USD 16.2 billion by 2028, at a Compound Annual Growth Rate (CAGR) of 20.9% during the forecast period, according to MarketsandMarkets. Explainable AI is at the intersection of AI, machine learning, ethics, and psychology. Collaboration across these fields is driving innovation in making AI systems more interpretable and user-friendly.

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269 - Tables
58 - Figures
284 - Pages

 

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Scope of the Report

 

As per verticals, the healthcare & life sciences segment is to grow at the highest CAGR during the forecast period.

The healthcare & life sciences vertical is expected to grow at the highest CAGR during the forecast period. The healthcare and life sciences industry stands at the forefront of leveraging Explainable AI to enhance decision-making processes and improve patient outcomes. In this vertical, Explainable AI technologies are employed to make the predictions and recommendations generated by AI models more transparent and interpretable for clinicians, researchers, and regulatory bodies. As the application of AI in healthcare becomes increasingly widespread, ensuring that AI-driven diagnostics, treatment recommendations, and drug discovery processes are explainable is crucial to build trust and mitigate risks.

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By Solutions by type, Software toolkits and frameworks Segment to grow at the largest market size during the forecast period.

Software toolkits and frameworks for Explainable AI are more developer-centric solutions. They offer libraries, APIs, and pre-built algorithms that data scientists and machine learning engineers can integrate into their existing machine learning workflows. These toolkits provide flexibility and customization options for those who want to implement transparency and interpretability in AI models. Toolkits provide a variety of algorithms for explaining and interpreting AI model predictions, such as feature importance, partial dependence plots, and saliency maps.

By Methods, the Model-Agnostic Methods segment is to grow at the highest CAGR during the forecast period.

Model-agnostic methods are techniques that can be applied to any machine learning model, irrespective of the underlying architecture. They are often used when a black-box model, like a deep neural network, is in place, and the goal is to provide explanations without altering the model itself. Companies utilize these methods to make AI models more interpretable and to build trust with users and stakeholders.

Asia Pacific to account to grow at the highest CAGR during the forecast period.

By region, Asia Pacific countries, especially China, South Korea, and Japan, are at the forefront of technological innovation. They are quick to adopt and adapt to emerging AI technologies, including XAI, in various industries. The APAC region is home to a significant portion of the global population, with diverse industries ranging from manufacturing to healthcare, finance, and e-commerce. This diversity creates a wide array of use cases for XAI. Governments are actively promoting AI research and development. They are also introducing regulations that require AI systems to be transparent and explainable, contributing to the growth of the Explainable AI Market.

Top Key Companies in Explainable AI Market:

Some major players in the Explainable AI Market include Microsoft (US), IBM (US), Google (US), Salesforce (US),Intel Corporation(US), NVIDIA(US), SAS Institute(US), Alteryx(US), AWS(US), Equifax(US), FICO(US), Temenos(Switzerland),Mphasis(India), C3.AI(US), H2O.ai(US), Fiddler(US), Zest AI(US), Seldon(London), Squirro(Switzerland), Kyndi(US), DataRobot(US),Databricks(US), Tredence(US), DarwinAI(Canada), Tensor AI solutions(Germany), . EXPAI(Spain), Abzu(Denmark), Arthur(US), and Intellico(Italy.

Recent Developments:

·  In April 2023, Epic has strategic partnership with Microsoft, aiming to integrate generative AI technology into the healthcare domain. This expanded collaboration will harness the capabilities of the Azure OpenAI Service and Epic's widely recognized electronic health record (EHR) software, with the objective of delivering the advantages of AI to the healthcare industry.

·  In May 2023, SAP and IBM entered into a collaborative partnership where IBM's Watson technology will be seamlessly integrated into SAP's solutions. The goal of this integration is to empower users with advanced AI-driven insights and automation features.

·  In April 2023, Google announced the launch of new AI enables Claims Acceleration Suite to streamline health insurance prior authorization and claims processing.

·  In May 2023, Esquire Bank will use Salesforce Customer 360 to unify its customer data from across its various systems, including its core banking system, CRM system, and marketing automation system.

·  In May 2023, NVIDIA announced a collaboration with Microsoft to accelerate enterprise-ready generative AI. The collaboration involves integrating NVIDIA AI Enterprise software into Microsoft's Azure Machine Learning to help enterprises create AI models.

·  In January 2023, SAS Institute collaborated with Erasmus MC to develop an AI algorithm to predict whether patients should remain in the hospital after oncological surgery or could be safely dismissed.

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Explainable AI Market Advantages:

·  When users are able to understand and analyse the output of AI models, their confidence and trust in the technology grows.

·  XAI promotes increased acceptance and implementation of AI technology by helping users and stakeholders develop confidence by providing explanations for AI predictions and judgements.

·  By assisting in the identification and resolution of ethical issues like prejudice and fairness, XAI makes sure that AI models adhere to moral principles.

·  XAI solutions reduce legal risks by supporting adherence to rules and guidelines that demand responsibility and transparency from AI systems.

·  By identifying and minimising the risks connected to AI models, users can lessen the possibility of inaccurate or biassed predictions.

·  Through the discovery of faults in AI models, XAI helps organisations make the necessary corrections and enhance the models' performance over time.

·  XAI offers comprehensible explanations that may be successfully shared with a range of stakeholders, including regulatory agencies and non-technical users.

·  As a result of users' increased ability to comprehend and engage with AI-driven applications, clear and interpretable AI models enhance the user experience.

Report Objectives

·  To determine and forecast the Explainable AI Market by offering, software type, methods, vertical, and region, and analyze the various macroeconomic and microeconomic factors that affect market growth.

·  To forecast the size of the market segments with respect to five main regions: North America, Europe, Asia Pacific, Middle East & Africa, and Latin America

·  To provide detailed information about the major factors influencing the growth of the market (drivers, restraints, opportunities, and challenges)

·  To analyze each submarket with respect to individual growth trends, prospects, and contributions to the overall market

·  To analyze the opportunities in the market for stakeholders by identifying the high-growth segments of the market

·  To profile the key market players and provide a comparative analysis on the basis of their business overviews, regional presence, product offerings, business strategies, and key financials, and illustrate the competitive landscape of the market

·  To track and analyze competitive developments, such as acquisitions; expansions; new product launches and product enhancements; agreements, collaborations, and partnerships; and R&D activities in the market.

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