Enterprise Artificial Intelligence Market Size to Reach $64.5 Billion at a CAGR of 34.1% by 2028

The Global Enterprise Artificial Intelligence Market was valued at USD 11.1 Billion in 2021 and is projected to reach USD 64.5 Billion by 2028 at a CAGR (Compound Annual Growth Rate) of 34.1% over the forecast period.

Enterprise Artificial Intelligence Market Overview

The market for enterprise AI is being driven by several factors, including the increasing demand for automation, the need for predictive analytics, and the growing amount of data generated by businesses. In addition, the adoption of cloud-based AI solutions, the development of advanced natural language processing and image recognition technologies, and the integration of AI with other technologies such as the Internet of Things (IoT) are also driving the growth of the market.

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The enterprise AI market is segmented into various application areas, including customer service, supply chain management, fraud detection, risk management, and marketing. The customer service segment is expected to account for the largest share of the market due to the increasing use of chatbots and virtual assistants to provide personalized and efficient customer service.

Geographically, North America is expected to dominate the enterprise AI market due to the presence of large tech companies and a highly developed IT infrastructure. However, Asia Pacific is expected to witness the highest growth rate due to the increasing adoption of AI technologies by businesses in the region.

Top Companies in Enterprise Artificial Intelligence Market

• Amazon Web Services Inc. (U.S.)
• Microsoft Corporation (U.S.)
• IBM Corporation (U.S.)
• Oracle Corporation (U.S.)
• Intel Corporation (U.S.)
• C3.ai Inc. (U.S.)
• Alphabet (U.S.)
• SAP SE (Germany)
• DataRobot Inc. (U.S.)
• Hewlett Packard Enterprise (U.S.)

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Enterprise Artificial Intelligence Market Dynamics:

Enterprise Artificial Intelligence Market is helping business change the way they work. By incorporating AI, companies can save money, boost their efficiency, and will be able to generate insights that help them enter new markets. Enterprise Artificial Intelligence Market applications enable a change to maximize sales, optimize the supply chain, improve products, enhance customer service, sharpen cybersecurity, and several other tasks. Enterprise AI helps companies to make data-driven decisions. Major factors contributing to the market's growth include a shift in business models from traditional to traditional will increase the forecast of the global Enterprise Artificial Intelligence Market during the forecast period.

The rising adoption of artificial intelligence within enterprises for enhancing customer satisfaction for providing better organization better will fuel the growth of the global Enterprise Artificial Intelligence Market. Additionally, organizing data sets is the most pivotal task to boost the market's growth. Numerous AI service providers are expected to continuously innovate and develop the next generation of products and services by collaborating with many government institutes and research & development departments. These collaborations are expected to occur due to the rising demand for AI in the market during the forecast period.

Increasing investments by dominant players in the market are further expected to push the global Enterprise Artificial Intelligence Market boundary during the forecast period. For instance, in May 2022, IBM Corporation announced that they were collaborating with Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), the first research university of AI based in Abu Dhabi, UAE. This strategic collaboration is expected to focus on developing fundamental AI research and accelerating various scientific breakthroughs that would enhance the potential of artificial intelligence.

What is Enterprise Artificial Intelligence?

Enterprise Artificial Intelligence (AI) refers to the use of advanced machine learning and cognitive computing technologies to help businesses automate tasks, gain insights, and make better decisions. Enterprise AI can be applied in various areas, such as customer service, supply chain management, fraud detection, risk management, and marketing.

Some of the technologies that are commonly used in enterprise AI include natural language processing, computer vision, machine learning, and deep learning. These technologies can help businesses to process large amounts of data, identify patterns, and make predictions.

One of the main benefits of enterprise AI is that it can help businesses to improve efficiency and reduce costs by automating routine tasks. It can also help businesses to improve customer satisfaction by providing personalized and timely service. Additionally, enterprise AI can help businesses to identify new opportunities and reduce risk by providing insights into trends and patterns in data.

However, the implementation of enterprise AI can also pose challenges such as data privacy and security concerns, ethical considerations, and the need for specialized skills and expertise. Therefore, it is important for businesses to carefully evaluate the benefits and risks of enterprise AI before implementing it.

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Enterprise Artificial Intelligence Market Challenges

Data quality and availability: One of the biggest challenges for enterprise AI is ensuring the quality and availability of data. AI models require large amounts of high-quality data to train effectively, but many organizations struggle to access and manage this data.

Data privacy and security: As AI relies on large amounts of data, privacy and security concerns are paramount. Companies need to ensure that their data is protected and that AI systems are not being used to breach privacy laws or regulations.

Ethical considerations: As AI is used more widely, ethical considerations become more important. Companies must ensure that AI systems are not used in ways that are discriminatory, biased, or harmful.

Lack of skilled professionals: The adoption of AI requires highly skilled professionals, including data scientists, AI developers, and machine learning engineers. However, there is a shortage of skilled professionals in these areas, making it difficult for companies to implement and maintain AI systems.

Integration with existing systems: Integrating AI with existing enterprise systems can be challenging. AI systems need to be compatible with a wide range of existing technologies and data sources, which can be complex and time-consuming.

Cost: AI technologies can be expensive to implement and maintain, which can be a barrier to adoption for many organizations. The costs of developing and training AI models, as well as maintaining them over time, can be significant.

Regulatory environment: As AI technologies become more widespread, regulatory frameworks are emerging to govern their use. Companies need to keep up to date with changing regulations and ensure that their AI systems comply with legal requirements.

Key Developments:

• February 2022: IBM Corporation acquired Sentaca, IBM plans to accelerate the growth of its cloud business with this acquisition. Sentaca's consulting services are anticipated to help IBM's clients solve their technology and other strategic challenges regarding revenue, expense, infrastructure, and scalability issues.
• December 2021: Google Cloud and Kyndryl announced a strategic partnership. Kyndryl will use Google Cloud to create a digital transformation service focusing on data analytics, machine learning, and AI. Kyndryl further announced that they would use Google Cloud to grow their managed SAP services and create a new data-centric app to assist their financial clients with hastening their cloud migrations.
• October 2021: H20 AI Hybrid Cloud announced partnering with Teradata's multi-cloud data platform – Vantage. Customers of Teradata and H20.ai can apply rapidly to creating, implementing, and running AI solutions for increasing company value.

Enterprise Artificial Intelligence Market Regional Analysis

North America: North America is the largest market for enterprise AI due to the presence of large tech companies and a highly developed IT infrastructure. The US is the major contributor to the growth of the market in North America, followed by Canada. The demand for enterprise AI in North America is driven by factors such as the increasing adoption of cloud-based AI solutions, the development of advanced natural language processing and image recognition technologies, and the integration of AI with other technologies such as the Internet of Things (IoT).

Europe: Europe is the second-largest market for enterprise AI. The region is witnessing significant growth due to the increasing adoption of AI technologies by various industries, such as healthcare, banking, and retail. The UK, Germany, and France are the major contributors to the growth of the enterprise AI market in Europe. Factors driving the growth of the market in Europe include the increasing use of AI for automation, predictive analytics, and customer service.

Asia Pacific: The Asia Pacific region is witnessing the highest growth rate in the enterprise AI market. The region is seeing significant adoption of AI technologies by businesses in various industries, such as healthcare, retail, and manufacturing. The major contributors to the growth of the enterprise AI market in Asia Pacific include China, Japan, and India. The demand for enterprise AI in the region is driven by factors such as the increasing adoption of cloud-based AI solutions, the development of advanced natural language processing and image recognition technologies, and the integration of AI with other technologies such as the Internet of Things (IoT).

Middle East and Africa: The Middle East and Africa are witnessing moderate growth in the enterprise AI market. The growth is driven by factors such as the increasing adoption of AI technologies by various industries, such as healthcare and banking, and the increasing government initiatives to promote AI adoption. The major contributors to the growth of the enterprise AI market in the Middle East and Africa include the UAE, Saudi Arabia, and South Africa.

Latin America: Latin America is witnessing slow growth in the enterprise AI market. The growth is driven by factors such as the increasing adoption of AI technologies by various industries, such as healthcare and banking, and the increasing government initiatives to promote AI adoption. The major contributors to the growth of the enterprise AI market in Latin America include Brazil and Mexico.

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