Commercial Artificial Intelligence Market Size, Share & Segmentation by Technology (Deep Learning, Machine Learning, Natural Language Processing (NLP), Others), by Implementation (Cloud-hosting and On-premises), by Application (Customer relationship management, Supply chain analysis, Merchandising, virtual personal assistant, Warehouse automation, Others), by End-User(BFSI, Retail & Commerce, Food & beverages, Manufacturing, Healthcare, Transportation & Logistics, Others ) by Regions and Global Market Forecast 2023-2030

Report Scope & Overview:

The Commercial Artificial Intelligence market size was valued at USD 3.69 Bn in 2022 and is expected to reach USD 50.42 Bn by 2030, and grow at a CAGR of 38.9% over the forecast period 2023-2030.

Even as global corporations continue to embrace big data and data analytics, many are grappling with the question of how to get the most value out of it. The latter refers to extremely big data sets that are inaccessible using typical approaches. Machine learning is one option firms have today to handle their massive data since artificial intelligence (AI) and its subset machine learning (ML) are becoming mainstream, i.e., migrating from the laboratory to the commercial sector. For greater corporate insight, analytics has progressed from old approaches to automated solutions. In fact, it has surpassed the capabilities of a single human analyst. Because ML-based algorithms live on large data – both structured and unstructured – adopting ML for analytics allows businesses to realize the full potential of their big data.

Renesas Electronics Corporation, a leading producer of advanced semiconductor solutions, said today that it has reached a formal agreement to acquire Reality Analytics, Inc. (Reality AI), a leading provider of embedded AI solutions. Customers are increasingly seeking highly tailored solutions that include embedded machine learning, signal processing, high-capability processors, and hardware integration and solution development help. "Having collaborated with Renesas for some time now, we look forward to being able to provide customers with more complete solutions - especially in the areas of IIoT, consumer, and automotive products, where machine learning is rapidly growing."

MARKET DYNAMICS:

KEY DRIVERS:

• Machine learning is becoming more popular in a variety of sectors and production units.

• Many industrial companies have begun to implement modern technologies such as IoT, AI, and machine learning.

• Assists manufacturers in reducing machine downtime and failures, as well as increasing asset ROI.

RESTRAINTS:

• Commercial adoption is quite limited because of the expensive cost of AI installation.

• Because Artificial Intelligence is a complicated system, businesses need employees with certain skill sets.

OPPORTUNITY:

• Investments in AI technology are increasing.

• Increasing research and development spending.

CHALLENGES:

• Concerns about data security and privacy

IMPACT OF COVID-19:

Because of COVID-19, businesses have been moving forward with plans to digitize and automate elements of their operations, not just to improve operational efficiencies but also to defend themselves from interruptions. Various organizations saw considerable increases in consumer pressure during the epidemic, but their number of available personnel reduced. Various contact centers were unable to meet demand or were forced to close due to lockdown limitations, resulting in high wait times for customer support inquiries and a negative impact on the customer experience. As a result, commercial AI has risen to the top of the list of technological enablers.

MARKET ESTIMATION:

During the projection period, cloud-hosting AI is predicted to develop at the fastest rate, with a positive CAGR. Because of its flexibility and scalability, cloud-based AI is widely used across most sectors. Large businesses have a lot of data on their customers and clients, and AI allows them to not only store that data but also analyze it effectively, allowing them to extract useful information and develop a business plan.

Cloud-AI, on the other hand, is less expensive than on-premises AI since it doesn't require IT people or infrastructure to run. Other considerations such as vendor-provided full support and maintenance, frequent data backup, and upgrades are likely to improve the cloud-hosting market for commercial AI.

By 2028, retail and eCommerce are predicted to have the highest market share percentage. Customers' tastes and behavior toward their goods are analyzed using AI, which collects and analyses various data from them. By utilizing RFID and NFC technologies, AI can give real-time data about items and consumers. For example, beer providers may learn where the beer bottle is and who is drinking it.

Many eCommerce service providers, on the other hand, are implementing chatbots to assist customers and improve their purchasing experience. AI allows businesses to improve inventory amount, forecasting, and pricing customization based on consumer preferences and market rivalry, which is likely to promote commercial AI in the retail and eCommerce industries.

KEY MARKET SEGMENTS:

On The Basis of Technology        

• Deep Learning

• Machine Learning

• Natural Language Processing (NLP)

• Others

On The Basis of Implementation

• Cloud-hosting

• On-premises

On The Basis of Application        

• Customer relationship management

• Supply chain analysis

• Merchandising

• virtual personal assistant

• Warehouse automation

• Others

On The Basis of End-User

• BFSI

• Retail & Commerce

• Food & beverages

• Manufacturing

• Healthcare

• Transportation & Logistics

• Others

REGIONAL ANALYSIS:

During the predicted period, North America is expected to increase the most. Developed countries in the area, such as the United States and Canada, are noted for being early adopters of innovative technology and linked gadgets in a variety of sectors and enterprises. The emergence of massive AI software firms in the United States is related to the rising demand for sophisticated technologies such as machine learning, IoT, AI, and so on. The commercial AI market in North America is predicted to grow as major firms expand and demand industrial automation develops in the area.

Due to the rising demand for automation in industrial units, Asia Pacific is predicted to rise rapidly throughout the forecast period. Manufacturing industries are headquartered in countries such as China and Japan. Advanced technologies are frequently used by manufacturers to automate processes, enhance productivity, improve product quality, and minimize waste and downtime in heavy machinery, which is likely to generate several attractive prospects for the Asia Pacific market.

REGIONAL COVERAGE:

• North America

  • USA

  • Canada

  • Mexico

• Europe

  • Germany

  • UK

  • France

  • Italy

  • Spain

  • The Netherlands

  • Rest of Europe

• Asia-Pacific

  • Japan

  • south Korea

  • China

  • India

  • Australia

  • Rest of Asia-Pacific

• The Middle East & Africa

  • Israel

  • UAE

  • South Africa

  • Rest of Middle East & Africa

• Latin America

  • Brazil

  • Argentina

  • Rest of Latin America

KEY PLAYERS:

The major key players of the market are IBM, Google, Microsoft, AWS, General Vision, Siemens, Accenture, Agralogics, Agrible,Lurkin

Frequently Asked Questions (FAQ) :