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Commercial Artificial Intelligence Market

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 2022-2028

Report Id: SNS/ICT/1665 | June 2022 | Region: Global | 135 Pages

Report Scope & Overview:

The Commercial Artificial Intelligence market size was valued at USD 2.62 Bn in 2021 and is expected to reach USD 26.18 Bn by 2028, and grow at a CAGR of 38.9% over the forecast period 2022-2028.

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.

Commercial artificial intelligence market

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

Commercial Artificial Intelligence Market

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

Commercial Artificial Intelligence Market Report Scope:
Report Attributes Details
Market Size in 2021  US$ 2.62 Bn
Market Size by 2028  US$ 26.18 Bn
CAGR   CAGR of 38.9% From 2022 to 2028
Base Year  2021
Forecast Period  2022-2028
Historical Data  2017-2020
Report Scope & Coverage Market Size, Segments Analysis, Competitive  Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook
Key Segments • 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)
Regional Analysis/Coverage North America (USA, Canada, Mexico), Europe
(Germany, UK, France, Italy, Spain, 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)
Company Profiles IBM, Google, Microsoft, AWS, General Vision, Siemens, Accenture, Agralogics, Agrible, Lurkin
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
Market Opportunities • Investments in AI technology are increasing
• Increasing research and development spending

 


Frequently Asked Questions (FAQ) :

Ans: - The Commercial Artificial Intelligence market size was valued at USD 2.62 Bn in 2021.

Ans: - Investments in AI technology is increasing and Increasing research and development spending.

Ans: - The primary growth tactics of Commercial Artificial Intelligence market participants include merger and acquisition, business expansion, and product launch.

Ans: - Key Stakeholders Considered in the study are Raw material vendors, Regulatory authorities, including government agencies and NGOs, Commercial research, and development (R&D) institutions, Importers and exporters, etc.


Table of Contents

 

1. Introduction

1.1 Market Definition

1.2 Scope

1.3 Research Assumptions

 

2. Research Methodology

 

3. Market Dynamics

3.1 Drivers

3.2 Restraints

3.3 Opportunities

3.4 Challenges

 

4. Impact Analysis

4.1 COVID 19 Impact Analysis

4.2 Impact of the Ukraine- Russia war

 

5. Value Chain Analysis

 

6. Porter’s 5 forces model

 

7. PEST Analysis

 

8. Commercial Artificial Intelligence Market Segmentation, by Technology       

8.1 Deep Learning

8.2 Machine Learning

8.3 Natural Language Processing (NLP)

8.4 Others

 

9. Commercial Artificial Intelligence Market Segmentation, by Implementation

9.1 Cloud-hosting

9.2 On-premises

 

10. Commercial Artificial Intelligence Market Segmentation, by Application     

10.1 Customer relationship management

10.2 Supply chain analysis

10.3 Merchandising

10.4 virtual personal assistant

10.5 Warehouse automation

10.6 Others

 

11. Commercial Artificial Intelligence Market Segmentation, by End-User

11.1 BFSI

11.2 Retail & Commerce

11.3 Food & beverages

11.4 Manufacturing

11.5 Healthcare

11.6 Transportation & Logistics

11.7 Others

 

12. Regional Analysis

12.1 Introduction

12.2 North America

12.2.1 USA

12.2.2 Canada

12.2.3 Mexico

12.3 Europe

12.3.1 Germany

12.3.2 UK

12.3.3 France

12.3.4 Italy

12.3.5 Spain

12.3.6 The Netherlands

12.3.7 Rest of Europe

12.4 Asia-Pacific

12.4.1 Japan

12.4.2 South Korea

12.4.3 China

12.4.4 India

12.4.5 Australia

12.4.6 Rest of Asia-Pacific

12.5 The Middle East & Africa

12.5.1 Israel

12.5.2 UAE

12.5.3 South Africa

12.5.4 Rest

12.6 Latin America

12.6.1 Brazil

12.6.2 Argentina

12.6.3 Rest of Latin America

 

13. Company Profiles

13.1 IBM

13.1.1 Financial

13.1.2 Products/ Services Offered

13.1.3 SWOT Analysis

13.1.4 The SNS view

13.2. Google

13.3 Microsoft

13.4 AWS

13.5 General Vision

13.6 Siemens

13.7 Accenture

13.8 Agralogics

13.9 Agrible,

13.10 Lurkin

 

14. Competitive Landscape

14.1 Competitive Benchmarking

14.2 Market Share Analysis

14.3 Recent Developments

 

15. Conclusion

An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.

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The 5 steps process:

Step 1: Secondary Research:

Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.

Secondary Research

Step 2: Primary Research

When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data.  This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.

We at SNS Insider have divided Primary Research into 2 parts.

Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.

This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.

Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.

Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.

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