AI Governance Market

Market Overview

The global AI governance market was valued at USD 130.10 million in 2022. It is projected to reach USD 1,712.85 million by 2031, growing at a CAGR of 32.1 during the forecast period (2023-2031). 

AI governance encourages the construction of legal frameworks to facilitate the ethical deployment of machine learning (ML) and other AI-based technologies. Businesses are becoming more aware of the benefits of integrating artificial intelligence (AI) into their operations to increase operational effectiveness and cut costs by automating process flows. As a result, businesses have begun utilizing autonomous processes to boost productivity and transform customer service (for instance, through AI-powered chatbots). Although technology advancements make it easier and more common than ever to implement AI systems, there are rising worries regarding their use, especially regarding problems like algorithmic bias. Ethical issues are raised by developing new AI capacities, including the ability to create images and films.

Highlights

• The solution segment is the major contributor to the market by component.
• The cloud segment is the major contributor to the market by deployment.
• The BFSI segment is the major contributor to the market by end-user vertical.
• North America is the major revenue contributor by region.

Market Dynamics

Global AI Governance Market Drivers

Increasing Demand of Transparency in AI Decision Making

The average spending on AI is anticipated to more than quadruple in the following three years, according to a poll of international executives conducted by IBM (Institute for Business Value). Transparency is seen as a vital facilitator to reduce issues of fairness, trust, and prejudice – all of which have garnered more attention recently. As with increased AI use, there is a raised risk associated with data stewardship. For instance, according to a survey by IBM, 75% of consumers are less likely to trust firms with their personal information, and 81% of consumers stated they have grown more concerned over the past year about how companies utilize their data.

One of the leading causes influencing the demand for AI governance is the rise in consumer concerns about privacy, misuse, and bias. One of the main goals of AI governance is to deliver moral and transparent AI to establish accountability, supervision, and responsibility. Furthermore, issues like prejudice from automated decision-making algorithms are becoming increasingly urgent due to the expanding application of artificial intelligence (AI) in many industries. It makes sense to demand more transparency to lessen the issues brought on by opacity.

Global AI Governance Market Restraint

Inadequate AI Expertise and Capabilities

Although most businesses have invested significantly in AI, over half, need more internal skills to carry out their strategy. 93% of U.S. and U.K. firms believe AI to be a business priority and have projects planned or already in production, according to the study on The AI Skills Gap. However, more than half of them (51%) admit they need more experienced AI personnel to implement their strategies. A lack of qualified people was identified as the biggest obstacle to the advancement of their AI programs, followed by a lack of funding, access to the appropriate technology, and a lack of meaningful data.

Private enterprise has become accustomed to lamenting the lack of AI talent in the US. Around 300,000 AI specialists work worldwide, but there are "millions" of open positions, according to Tencent. Only 25% of the 22,000 Ph.D.-educated researchers working on AI development and research worldwide, according to an estimate by Element AI from the year 2018, are "well-versed enough in the technology to work with teams to take it from study to application."

Global AI Governance Market Opportunities

Growing Implementing by Government

The world is being changed by two of the most revolutionary computing technologies: artificial intelligence and machine learning. AI is redefining what is possible today by efficiently using few resources and tackling complex problems as governments worldwide struggle to manage stretched budgets and fulfill public finance needs amid the slump. According to a study by Oxford Insights and the International Development Research Centre on the readiness of national governments to employ AI, the field of AI is dominated by nations with robust economies, sound government policies, and creative business sectors.

As a one-stop shop for its publicly available datasets from 70 public agencies, the Singapore government created "data.gov.sg," which is reachable via various application programming interface (API) options. Additionally, the portal exposes information and simple visualizations that show how the data can be used. The second iteration of Singapore's Model AI Governance Framework emphasizes stakeholder management, operations management, and human participation levels in addition to governance when evaluating applications for ethical AI use.

Regional Analysis

North America Dominates the Global Market

The global AI governance market is divided into four regions: North America, Europe, Asia-Pacific, and LAMEA. 

North America is the major revenue contributor and is expected to exhibit a CAGR of 31.40% during the forecast period. The goal of developing artificial intelligence and automated systems (AI) strategies and policies over the past few years has been to balance safeguarding the public from the possible negative consequences of AI technology and fostering positive innovation and competitiveness. North American businesses, notably those in the US, have used AI, ML, and deep learning technology to keep ahead of the competition. The nation's well-established economies allow vendors of AI and governance to invest in cutting-edge technologies.

Asia-Pacific is expected to exhibit a CAGR of 31.85% during the forecast period. AI research in China is projected to increase as more large Chinese AI businesses embrace open-sourcing, clearing the door for more innovation. With the aid of a pre-made and optimized framework, engineers may concentrate on the high-level structure of their model without becoming bogged down in the specifics of underlying methods. To support information services for the rising market, the government is accelerating the construction of "new infrastructure" projects, including 5G networks and data centers. The government has fostered the development of artificial intelligence by China's internet giants.

The U.K. holds a significant market share. In the business, public, and social sectors, developments in artificial intelligence (AI) technologies in the UK are expanding the bounds of what machines can achieve. These technologies have already permeated a wide range of industries and enterprises, and they have the potential to revolutionize processes and business models, ultimately driving economic development and higher productivity. The government aims to increase opportunities by launching a "great challenge" for better medical research and improved disease detection, prevention, and treatment. The UK also tops Europe for the density of AI firms created in the health and medical technology sectors.

Latin America, the Middle East, and Africa are the other world areas considered in this study. Latin America's energy, healthcare, and automotive industries are predicted to use artificial intelligence technologies. To remain competitive in the international economic market, Latin America is undergoing a digital transformation in both the public and private sectors. The market is expected to be fueled by Latin American countries working together to improve AI deployment and applications there to realize the technology's full potential. The nations of the Latin American area have national AI strategies that either precisely target AI in the public sector or focus on their overall strategy.

Segmental Analysis

The global AI governance market is segmented by component, deployment, and end-user.

Based on components, the global AI governance market is bifurcated into solutions and services.

The solution segment is the major contributor to the market and is estimated to exhibit a CAGR of 31.90% during the forecast period. Software tools and platforms make up the majority of the AI governance solution. By automating and standardizing the deployment, monitoring, governance, and validation of all AI models generated in any context, vendors in the AI governance sector provide solutions and platforms enabling customers to leverage AI and ML's power. These technologies are used by several market leaders in the financial services, insurance, pharmaceutical, and food and beverage sectors to operationalize and regulate AI solutions at scale and generate predictable and dependable business results. 

The vendors in the AI governance sector provide managed and professional services, as well as consultation, integration, support, and maintenance services. These services provide the assistance required to uphold corporate process effectiveness, improve system dependability, maintain infrastructure, and foster expansion while lowering undesirable and unforeseen operating costs. Integration services will experience rapid development due to difficulties in establishing AI governance platforms and software and the requirement to integrate them into their clients' IT infrastructure. Regarding the solutions the businesses choose, vendors in the AI governance sector provide certain client services. Due to the increasing adoption of AI governance solutions, companies need software integration, installation, deployment, maintenance, and upgrade services.

Based on deployment, the global AI governance market is bifurcated into cloud and on-premise.

The cloud segment is the major contributor to the market and is estimated to exhibit a CAGR of 32.30% during the forecast period. Cloud computing has changed how businesses utilize, share, and store data, apps, and workloads by providing a new medium for the influx of data. Companies must reevaluate their AI governance strategies in light of the significant amounts of data stored in the cloud and public cloud services. Only cutting-edge technology like AI and machine learning can facilitate effective governance at the cloud scale. The improved capabilities and scalability that cloud-based AI technologies bring enable the automatic cleansing, classification, and security of data in the cloud as it is ingested, ensuring high quality, integrity, and ethical handling.

In a conventional on-premise architecture, traffic management and security are handled by complicated physical equipment placed at choke points on a single monolithic network that is mainly static (regarding its physical location and IP addresses). The fact that they don't have control of the program is one of the main issues businesses frequently highlight when considering using a cloud provider for AI governance. Instead, customers typically sign a lease agreement, just as when renting a car. The best alternative for such a prospect of complete ownership is on-premise solutions. On-premise AI governance does offer the advantage of ownership. Still, an organization must be prepared to take on all the duties that come with it, such as maintaining enhanced data protection and keeping software up to date.

Based on end-user, the global AI governance market is bifurcated into healthcare, government and defense automotive, retail BFSI, and other end-user verticals.

The BFSI segment is the major contributor to the market and is estimated to exhibit a CAGR of 31.80% during the forecast period. Data plays a crucial role in the banking, financial, and insurance industries thanks to rapid digitization. According to a Lightico survey in March 2020–2021, 63% of respondents were now more inclined to use digital applications, while 82% of consumers were anxious about visiting their branch in person. These behavioral changes have sped up digitization in the BFSI industry. Data governance solutions are now required because of the rising data usage brought on by digitization in the investigated business. For instance, Michigan-based Flagstar Bank disclosed a data breach in January 2021 that was brought on by a flaw in the Accellion file-sharing program.

AI can help healthcare professionals provide better patient care, precise diagnoses, and optimized treatment plans, support pandemic preparedness, and educate health policy-makers on decisions or distribute resources within health systems. Healthcare professionals and health systems need a thorough knowledge of the environments in which such technologies might operate safely and effectively if they are to realize their promise fully. Although many governments also create and implement these technologies, AI technologies, like many other information technologies used in healthcare, are designed mainly by businesses or through public-private partnerships (PPPs).

There are several applications for artificial intelligence (AI) in government. It can help the public communicate with the government and achieve public policy goals (in fields like emergency services, health, and welfare) (through virtual assistants). Those who have created a roadmap for AI often concentrate on guiding concepts rather than specific objectives. Different G20 nations have other governance plans for digital technology, and these variations are already becoming apparent.

One of the most technologically developed industries globally is the automotive sector. The automobile market has come a long way to drive potential revenue out of it, from developing driverless electric cars to integrating autonomous robots on the production floor. Scaling AI into automotive technology will allow companies to take market share in the mass-market vehicle industry. Capgemini researched to comprehend the elements used by automakers as they scale AI at their corporate level.

The retail industry is undergoing a significant transition on a global scale. Customers' channel choices and purchasing behaviors alter as they grow more digitally literate. The concerns about data concerns generate issues and worries that are driving digital transformation. In retail and consumer products, IBM predicts that adopting AI-driven intelligent automation will increase from 40% of enterprises today to more than 80% in three years. Supply-chain planning is predicted to experience the fastest growth in retail, while manufacturing is expected to have the most significant penetration in consumer goods firms.

Recent Developments

• February 2022- Data2vec, a single framework for self-supervised deep learning on text, pictures, and spoken audio data, was open-sourced by Meta AI (formerly Facebook AI), according to a company announcement.
• February 2022- The technical firm Virtanen in California declared that it had created a platform for hybrid cloud management solutions to allow its clients to plan, implement, and manage their hybrid cloud implementations. To enable observability for managing app workloads across public, private, hybrid, and multi-cloud settings, the company also claimed to have combined AI, ML, and data analytics.