Enterprise AI Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)

Enterprise AI Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022 - 2027)

Enterprise AI Market has registered a CAGR of 52.17 % during the forecast period. Enterprises are recognizing the value associated with incorporating artificial intelligence (AI) into their business processes, as they improve operational efficiency and reduce cost through automation of process flows.

Key Highlights

• Digitalization of enterprises is the most dominant trend in the market. The fourth industrial revolution (Industry 4.0) is characterized by a combination of physical and advanced digital technologies, such as the Internet of Things, artificial intelligence, intelligent robots, ubiquitous mobile supercomputing, information management, and analytics, which have a significant impact across various industries. The boom of industrial automation, with the widespread adoption of Industry 4.0, is driving the adoption of robots and automated technologies to enhance the efficiency of manufacturing processes.
• For instance, According to the Bank of America, the industrial robot segment of robotics and AI is expected to be valued at about USD 24 billion by 2025. This trend has augmented the use of robotic process automation (RPA) among enterprises, which is a significant aspect of AI.
• Enterprise AI is a significant enabler of digital transformation. Nearly every enterprise software application will be AI-enabled in the years to come. Developing competencies in the capability to build, deploy, and operate enterprise AI applications at scale, therefore, is becoming imperative for business survival.
• According to O’Reilly's 2022 report on enterprise AI adoption (based on the answers given by recipients of its newsletters to a questionnaire on enterprise AI adoption), 31% of companies report not using AI (up from 13% in 2021), 43% are evaluating adoption, and 26% have implemented AI applications. The primary increase, from 18% to 31%, of manufacturing respondents with AI was in Oceania. A considerable number of organizations lack AI governance. Of the 26% of respondents with AI products in production, only 49% have a governance plan to oversee how projects are created, measured, and observed (49%) versus 51% for those without.
• However, enterprise AI market manufacturers face enormous underlying intellectual challenges in creating and modifying such technology. The artificial intelligence market is mainly propelled by enhanced productivity, diversified applications, customer satisfaction, and extensive data integration.
• The COVID-19 pandemic caused many organizations to accelerate their migrations to public cloud solutions since cloud service elasticity can meet unexpected spikes in service demand. Migrations to the cloud helped companies reinvent the way they conduct their businesses in the time of COVID-19.​

Key Market TrendsCloud Deployment is Expected to Experience a Faster Growth Rate

• The AI cloud, which was previously a concept, has now started to be implemented by enterprises, combining AI with cloud computing. Some of the significant factors driving it to include AI tools and software that deliver new, increased value to cloud computing, which is not only an economical option for data storage and computation but also plays a role in AI adoption. ​
• An AI cloud primarily consists of a shared infrastructure for AI use cases, supporting multiple projects and AI workloads simultaneously on cloud infrastructure at any given point in time. The AI cloud brings together AI hardware and software in order to deliver AI software-as-a-service on hybrid cloud infrastructure, providing organizations with access to AI and enabling them to harness AI capabilities more.​
• One of the most compelling advantages of AI in the cloud is the challenges it addresses. It significantly democratizes AI, making it more accessible. Lowering the adoption costs and facilitating co-creation and innovation are driving AI-powered transformation for enterprises.
• Organizations across the world are increasingly adopting cloud solutions. For instance, in December 2021, Kyndryl announced a strategic partnership with Google Cloud that would see the service provider develop a series of new digital transformation services with a specific emphasis on data analytics, machine learning, and AI. With Google Cloud, Kyndryl plans to expand its managed SAP services, develop a newer edge and data-centric applications, and help its largest financial customers accelerate their cloud migrations.
• In October 2021, Teradata, a connected multi-cloud data platform for an enterprise analytics company, and artificial intelligence cloud platform provider H2O.ai announced the integration of H2O AI Hybrid Cloud, the company’s advanced AI platform, with Vantage, Teradata’s multi-cloud data platform. The integration allows Teradata and H2O.ai’s customers to quickly and easily make, deploy, and operate AI solutions that solve business problems and drive business value.

Europe is Expected to Hold a Significant Market Share in the Forecast Period

• The European region is witnessing increased demand due to mainstream trends, such as the industrial revolution and automation. The regional firms have been identified to invest in various automation technologies, such as robotics, artificial intelligence, etc., with developments in machine learning.
• The European Union introduced Artificial Intelligence Act in April 2021, which will come into effect from the beginning of 2023. the act will have a broad impact on the use of AI and machine learning for citizens and companies around the world. Initiatives like these are expected to boost the Enterprise AI market positively.
• According to Eurostat, In 2021, large enterprises will use AI more than small and medium enterprises. Due to the complexity of implementing AI technologies in an enterprise, it was witnessed that 28 % of large enterprises, 13 % of medium enterprises, and 6% of small enterprises used AI.
• Moreover, major regional players are investing and expanding their capabilities in the Enterprise AI market. For instance, in May 2022, Hewlett Packard Enterprise announced the launch of its new site in the Czech Republic to strengthen Europe's Supercomputer Supply Chain. The new factory will manufacture the company's custom-designed solutions to advance scientific research, mature AL/ML initiatives, and accelerate innovation.
• This rise in cognitive computing is expected to enable the replication of human sensory perception, deduction, thinking, learning, and decision-making capabilities across regional enterprises. The ability to harness considerable amounts of computing power is poised to take this paradigm beyond human replication, both in terms of speed and capacity, to distinguish patterns and provide potential solutions that individuals may not be equipped to perceive, thus augmenting the use of AI solutions.

Competitive Landscape

The competitive rivalry in the Enterprise AI Market is high due to many major players. Players like IBM, SAP SE, Hewlett Packard Enterprise, Google Inc., Microsoft Corporation, Oracle Corporation, and many more are trying to achieve maximum market share by designing new and innovative products for users. Their significant investments in research and Development, mergers & acquisitions, strategic expansion, funding, a strategic partnership, etc., have allowed them to gain a competitive advantage.

• October 2021 - Nvidia stated that with the latest updates to VMware vSphere with Tanzu, enterprises would now be able to run trials of their AI projects in conjunction with the NVIDIA AI Enterprise software suite. Launched in Aug 2021, NVIDIA AI Enterprise is an end-to-end, cloud-native suite of AI and data analytics frameworks and tools optimized, certified, and supported by NVIDIA to enable rapid deployment, management, and scaling of AI/ML applications in the modern hybrid cloud.
• August 2021 - IBM announced the launch of its On-Chip accelerated artificial intelligence processor. It is designed to help customers achieve business insights at scale across banking, finance, trading, insurance applications, and customer interactions.

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• The market estimate (ME) sheet in Excel format
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