MarketsandMarkets forecasts the AI Governance Market size to grow from USD 51 million in 2020 to USD 316 million by 2025, at a CAGR of 44.3% during the forecast period. The increasing government initiatives to leverage the benefits of AI technology, increasing need for building trust in AI systems, and growing demand for transparency in AI decisions are some of the major factors expected to drive the growth of this market.
The solution segment to hold the largest market size during the forecast period
The AI governance solution refers to the platform and software tools, which provides end-to-end AI governance solutions to AI developers, data scientists, business users, and IT architects across different verticals. This solution helps in collaborating, building, and running AI solutions, and enable companies integrate the Machine Learning (ML) capabilities to their existing applications.
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The automotive segment to grow at a higher CAGR during the forecast period
Autonomous transportation is one of the areas in the automotive vertical where the AI governance solutions are expected to be playing a major role because if autonomous vehicle makes a mistake in decision making it can directly lead to the loss of life. There are lot of initiatives happening in the development of self-driving cars. Unfortunately, various incidents of accidents are still there and require special attention. Therefore, as self-driving cars can have major role in making life and death-related decisions, they are expected to become major adopter of AI governance solution.
The AI governance market includes major vendors, such as IBM (US), Google (US), Facebook (US), AWS (US), Microsoft (US), Salesforce.com (US), SAP (Germany), FICO (US), SAS Institute (US), 2021.AI (Denmark), ZestFinance (US), Pymetrics (US), H2O.AI (US), and integrate.ai (Canada). These players have adopted different growth strategies to expand their global presence and increase their market shares. New product launches and partnerships/collaborations are some of the significant strategies adopted by the major players to grow further in the AI governance market.
IBM (US) is one of the leading AI and analytics solution providers. It offers AI-based solutions and services to help marketers automate and operationalize their business processes, thereby driving their revenues. The company entered into the AI governance market space by launching 2 products, namely AI Fairness 360 open-source toolkit and Watson-based OpenScale platform. In September 2018, the company launched AI Fairness 360 open-source toolkit, and in October 2018, it has launched Watson based OpenScale platform respectively, to help organizations govern their AI models across its life cycle and provide fair outcomes. The customers can avail the OpenScale platform through cloud or the on-premises deployment model. The platform comprises Machine Learning (ML) and deep learning frameworks, which help in gaining impartial outcomes in the production model. The OpenScale platform helps application developers, data scientists, and enterprises track and monitor AI models across its life cycle. Apart from this, IBM announced new software capability, Watson-based Business Automation Intelligence software, which would be available soon to help business leaders use AI into applications to automate business processes. These initiatives show that IBM is increasingly working toward innovation and product development to gain a competitive advantage.
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Google (US), a multinational technology company, has a strong presence in various regions. It is one of the key players in the AI governance market. It offers What-If Tool, an open-source toolkit, to govern the AI algorithm across its life cycle. The company has been adopting systematic approaches and undertaking various growth strategies to strengthen its product portfolio. For instance, the company has been continuously updating various APIs in the AI governance market. In April 2019, Google Cloud launched the beta version of the AI-powered Policy Intelligence solution to enable administrator to make required necessary changes for higher security. The solution uses ML techniques and cloud stipulations, and helps in data ingestion to improve system performance. In July 2019, the company added new capabilities to its What-If Tool to enable users to use this tool for XGBoost and Scikit-learn models that are deployed on the AI platform. The user can enable this capability by using the method call.
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