AI Governance Market vendors by Share & Growth Strategies – 2025 | MarketsandMarkets

[107 Pages Report] AI governance market size, analysis, trends, & forecast. The global market for AI governance categorized by solutions as platforms & software tools, by services, by verticals & by region.

AI Governance Market

Northbrook, IL 60062, USA, 2020-Sep-08 — According to a research report AI Governance Market by Component (Solutions (Platforms and Software Tools) and Services), Vertical (BFSI, Healthcare and Life Sciences, Government and Defense, Telecom, Retail, and Automotive), and Region – Global Forecast to 2025″, published by MarketsandMarkets, the AI governance market size is expected 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 and increasing need for building trust in AI systems are some of the major factors driving the growth of the AI governance market.

Browse 28 market data Tables and 41 Figures spread through 107 Pages and in-depth TOC on “AI Governance Market – Global Forecast to 2025″

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North America estimated to lead the AI governance market size during the forecast period

North America is estimated to account for the highest market share of the AI governance market in 2019. The region comprises developed countries, such as the US and Canada, and is considered the most advanced region in terms of adopting digital technologies. North America exhibits a wide presence of key industry players offering AI governance solutions and services, and its financial position enables it to invest majorly in leading tools and technologies for effective business operations.

Market Players

IBM (US), Google (US), Facebook (US), AWS (US), Microsoft (US), (US), SAP (Germany), FICO (US), 2021.AI (Denmark), ZestFinance (US), SAS Institute(US), Pymetrics (US), H2O.AI (US), and are some of the leading companies operating in this market.

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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.

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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