Artificial Intelligence (AI) In Marketing Market (By Component; By Application; By Technology; By End-User Industry) - Global Industry Analysis, Size, Share, Growth, Trends, Revenue, Regional Outlook and Forecast 2023-2032

The global artificial intelligence (AI) in marketing market was surpassed at USD 12.66 billion in 2022 and is expected to hit around USD 134.11 billion by 2032, growing at a CAGR of 26.62% from 2023 to 2032. The artificial intelligence (AI) in marketing market in the United States was accounted for USD 2.7 billion in 2022.

Artificial Intelligence (AI) In Marketing Market Size 2023 to 2032

Key Pointers

  • North America dominates the AI in marketing market, with a revenue share of 33% in 2022
  • Asia Pacific region is expected to grow with the fastest CAGR of 27.96% from 2023 to 2032. 
  • The content curation segment dominates the market, with a revenue share of 23% in 2022.
  • The Machine learning (ML) segment dominates the market, with a revenue share of 39% in 2022. 
  • The media & entertainment segment dominates the market, with a revenue share of 24% in 2022. 
  • The IT and telecommunications industries is expected to grow with a CAGR of 24.93% from 2023 to 2032

Report Scope of the Artificial Intelligence (AI) In Marketing Market

Report Coverage Details
Revenue Share of North America in 2022  33%  
CAGR of Asia Pacific from 2023 to 2032 27.96%
Revenue Forecast by 2032 USD 134.11 billion
Growth Rate from 2023 to 2032 CAGR of 26.62%
Base Year 2022
Forecast Period 2023 to 2032
Market Analysis (Terms Used) Value (US$ Million/Billion) or (Volume/Units)
Companies Covered Amazon.com, Inc.; Baidu, Inc.; Google LLC; Intel Corporation; International Business Machines Corporation; Microsoft Corporation; NVIDIA Corporation; Oracle Corporation; Salesforce, Inc.; Twitter, Inc.

 

The growing adoption of machine learning and artificial intelligence to offer increased acceptance of social networking platforms, individualized consumer experiences, and the rise of online shopping are the primary factors driving the market expansion. For instance, Google Responsive Search Ads is a text ad format available in Google Ads, an online advertising platform developed by Google that enables advertisers to generate multiple headlines and descriptions for a single advertisement. Using the Google advertisement feature, entrepreneurs can start their ads by tailoring them to a geographic range, budgetary needs, and other factors.

AI assists marketers in better targeting and segmenting audiences and providing more personalized experiences. AI has been used to drive success in various industries, including automotive, insurance, finance, retail, and healthcare. AI is poised to increase the effectiveness, efficiency, and impact of advertising, from more precise targeting audiences to automating ad creation and delivery. For instance, IBM Watson, a data analytics processor developed in IBM's DeepQA project, uses artificial intelligence to assist retail companies in creating more personalized purchasing experiences by utilizing real-time data that more accurately reflect a customer's current purchasing status.  

The healthcare industry marketing can benefit from Artificial intelligence in many areas of medicine. Chatbots can assist healthcare marketers by increasing on-site engagement and conversion or directing potential patients to answers online, improving the overall patient experience. Predictive analytics enables forecasting of particular demographic groups' future behavior and creating marketing campaigns specific to each demographic or analyzing spikes in patient visits by town or time by analyzing demographic trends. Youper is a healthcare technology company dedicated to making mental health care. Youper's A.I. tracks and improves users' emotional health using quick, personalized conversations and psychological techniques.

Companies have gradually shifted from a product-driven marketing strategy to a customer-centric one. Businesses focus on developing long-term relationships with their customers to survive in the competitive AI in the marketing industry. The motivation for the change is to understand their customers better and predict consumer behavior based on product purchases. A customer-centric strategy focuses on providing an exceptional customer experience before and after the sale to increase order repetition and customer loyalty and encourage business development. AI-powered tools can produce ad copy, images, and videos based on the advertiser's objectives, target market, and messaging. This can help advertisers create ads more quickly and efficiently and lower the cost of working with advertising agencies. Component Insights

The services segment dominates the market, with a revenue share of 59.3% in 2022. The service segment of AI in marketing refers to using AI to enhance customer service and support. AI-powered customer service tools are helping companies to deliver highly personalized service experiences. AI algorithms can provide customized recommendations and solutions by analyzing customer data, including purchase history and browsing behavior, improving customer satisfaction. Moreover, AI is helping companies to deliver faster, more efficient, and more personalized customer service experiences. As AI technology continues to evolve, we can expect to see even more innovative solutions in the service segment of AI in marketing.

AI marketing software uses artificial intelligence technology to make automated decisions. Moreover, the decisions are based on data collected, analyzed, and interpreted based on market trends. For instance, Seventh Sense, a Virginia-based sales and marketing software platform, provides AI software to assist in optimizing the performance and engagement of email marketing campaigns and programs. The increasing use of AI software in various applications, including voice and image recognition apps on social networks, smartphone assistants, and software that serves advertisements on various websites, drives the segment's growth.

Application Insights

The content curation segment dominates the market, with a revenue share of 23% in 2022.  AI-powered content recommendation engines are becoming more sophisticated, using machine learning algorithms to analyze user behavior and preferences to provide personalized content recommendations. This allows marketers to deliver more relevant and engaging content to their audience, increasing the demand for AI in marketing. Moreover, AI is being used to generate content, from blog posts to social media updates. Using natural language processing and machine learning algorithms, AI can create optimized content for specific audiences and channels, making it easier for marketers to produce content at scale.

Virtual assistants can be chatbots, digital avatars, or voice assistants that understand and respond to user requests using natural language processing, computer vision, and machine learning algorithms. Virtual assistance can improve the efficiency and effectiveness of human-computer interactions in various domains, including customer service, healthcare, finance, and education, which is responsible for segment growth. Alexa, Siri, and Google Assistant are examples of virtual assistants. With rising demand for convenience and personalized experiences, virtual assistance is expected to play a growing role in developing AI in the marketing Market over the forecasted period.

Technology Insights

The Machine learning (ML) segment dominates the market, with a revenue share of 39% in 2022. Computers can use ML technologies to understand, interpret, and generate human language, allowing them to perform tasks such as machine translation, sentiment analysis, question answering, and text generation. These technologies are commonly used in various applications, including virtual assistants, chatbots, and personalized recommendation systems. With the increasing volume of unstructured text data generated each day, ML is expected to grow and play an essential role in the development of AI.

The computer vision segment is expected to grow at the fastest CAGR during the forecast period.  Computer vision solutions can be adapted to specific aspects of social media. It can provide marketers with real-time information directly related to consumer behavior. For example, Meta Platforms, Inc., a U.S.-based technology company, employs a technology known as a DINO to train vision transformers (Vit). Moreover, without human intervention, this model can detect and classify objects in a video and image.

End-User Industry Insights

The media & entertainment segment dominates the market, with a revenue share of 24% in 2022. The rising AI advertising applications with significant traction are responsible for this high share. For example, in January 2022, Cadbury, a U.K.-based confectionery company, launched an initiative that enabled small business owners to create their ads for free using a celebrity's voice and facial features using AI tools. In BFSI, AI virtual assistants track transactions, observe customer behavior, and audit and log data to numerous compliance and regulatory systems, which propels the expansion of the BFSI segment.

The IT and telecommunications industries is expected to grow with a CAGR of 24.93% from 2023 to 2032. The industry has significant players in the AI in marketing market. The industry's major players are Google LLC, Facebook, Inc., Amazon.com, Inc., Microsoft Corporation, and IBM. The industry uses AI technologies to improve its marketing efforts and provides AI-powered marketing solutions to other companies. The IT & Telecommunications industry is experiencing significant growth in AI in Marketing because of the increasing demand for personalized and data-driven marketing solutions.

Regional Insights

North America dominates the AI in marketing market, with a revenue share of 33% in 2022. The factor attributed to the region’s growth is the expansion of retail, BFSI, healthcare, automotive, and other industries. The region's numerous well-known technology firms are aware of the promising possibilities presented by AI in marketing. Moreover, small and large companies are using AI significantly in the region, especially compared to the rest of the world. North America significantly influences the AI market, and this region is predicted to continue expanding.

Asia Pacific region is expected to grow with the fastest CAGR of 27.96% from 2023 to 2032. Rapid technological development and digitalization, the expansion of the e-commerce and online retail sectors, rising investment in artificial intelligence, and increasing business awareness and adoption of AI-powered marketing solutions are key factors influencing growth in this region. In particular, China's AI industry is expanding quickly, and it is anticipated that China will soon take the lead in AI technology. With a rising need for individualized and data-driven marketing solutions, the Asia Pacific region's retail and e-commerce sectors are a key industry vertical for AI in marketing.

Artificial Intelligence (AI) In Marketing Market Segmentations:

By Component 

  • Software
  • Services

By Application 

  • Social Media Advertising
  • Search Engine Marketing
  • Virtual Assistant
  • Content Curation
  • Sales & Marketing Automation
  • Analytics Platform
  • Others

By Technology 

  • Machine Learning
  • Natural Language Processing
  • Computer Vision
  • Others

By End-User Industry 

  • BFSI
  • Retail
  • Consumer Goods
  • Media & Entertainment
  • IT & Telecommunications
  • Others

By Artificial Intelligence in Marketing Regional 

  • North America
    • U.S.
    • Canada
  • Europe
    • UK
    • Germany
    • France
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
  • Latin America
    • Brazil
    • Mexico
  • Middle East and Africa
    • Kingdom of Saudi Arabia (KSA)
    • UAE
    • South Africa

Frequently Asked Questions

The global artificial intelligence (AI) in marketing market size was reached at USD 12.66 billion in 2022 and it is projected to hit around USD 134.11 billion by 2032.

The global artificial intelligence (AI) in marketing market is growing at a compound annual growth rate (CAGR) of 26.62% from 2023 to 2032.

The North America region has accounted for the largest artificial intelligence (AI) in marketing market share in 2022.

Chapter 1. Introduction

1.1. Research Objective

1.2. Scope of the Study

1.3. Definition

Chapter 2. Research Methodology

2.1. Research Approach

2.2. Data Sources

2.3. Assumptions & Limitations

Chapter 3. Executive Summary

3.1. Market Snapshot

Chapter 4. Market Variables and Scope 

4.1. Introduction

4.2. Market Classification and Scope

4.3. Industry Value Chain Analysis

4.3.1. Raw Material Procurement Analysis 

4.3.2. Sales and Distribution Channel Analysis

4.3.3. Downstream Buyer Analysis

Chapter 5. COVID 19 Impact on Artificial Intelligence (AI) In Marketing Market 

5.1. COVID-19 Landscape: Artificial Intelligence (AI) In Marketing Industry Impact

5.2. COVID 19 - Impact Assessment for the Industry

5.3. COVID 19 Impact: Global Major Government Policy

5.4. Market Trends and Opportunities in the COVID-19 Landscape

Chapter 6. Market Dynamics Analysis and Trends

6.1. Market Dynamics

6.1.1. Market Drivers

6.1.2. Market Restraints

6.1.3. Market Opportunities

6.2. Porter’s Five Forces Analysis

6.2.1. Bargaining power of suppliers

6.2.2. Bargaining power of buyers

6.2.3. Threat of substitute

6.2.4. Threat of new entrants

6.2.5. Degree of competition

Chapter 7. Competitive Landscape

7.1.1. Company Market Share/Positioning Analysis

7.1.2. Key Strategies Adopted by Players

7.1.3. Vendor Landscape

7.1.3.1. List of Suppliers

7.1.3.2. List of Buyers

Chapter 8. Global Artificial Intelligence (AI) In Marketing Market, By Component

8.1. Artificial Intelligence (AI) In Marketing Market, by Component, 2023-2032

8.1.1. Software

8.1.1.1. Market Revenue and Forecast (2020-2032)

8.1.2. Services

8.1.2.1. Market Revenue and Forecast (2020-2032)

Chapter 9. Global Artificial Intelligence (AI) In Marketing Market, By Application

9.1. Artificial Intelligence (AI) In Marketing Market, by Application, 2023-2032

9.1.1. Social Media Advertising

9.1.1.1. Market Revenue and Forecast (2020-2032)

9.1.2. Search Engine Marketing

9.1.2.1. Market Revenue and Forecast (2020-2032)

9.1.3. Virtual Assistant

9.1.3.1. Market Revenue and Forecast (2020-2032)

9.1.4. Content Curation

9.1.4.1. Market Revenue and Forecast (2020-2032)

9.1.5. Sales & Marketing Automation

9.1.5.1. Market Revenue and Forecast (2020-2032)

9.1.6. Analytics Platform

9.1.6.1. Market Revenue and Forecast (2020-2032)

9.1.7. Others

9.1.7.1. Market Revenue and Forecast (2020-2032)

Chapter 10. Global Artificial Intelligence (AI) In Marketing Market, By Technology 

10.1. Artificial Intelligence (AI) In Marketing Market, by Technology, 2023-2032

10.1.1. Machine Learning

10.1.1.1. Market Revenue and Forecast (2020-2032)

10.1.2. Natural Language Processing

10.1.2.1. Market Revenue and Forecast (2020-2032)

10.1.3. Computer Vision

10.1.3.1. Market Revenue and Forecast (2020-2032)

10.1.4. Others

10.1.4.1. Market Revenue and Forecast (2020-2032)

Chapter 11. Global Artificial Intelligence (AI) In Marketing Market, By End-User Industry 

11.1. Artificial Intelligence (AI) In Marketing Market, by End-User Industry, 2023-2032

11.1.1. BFSI

11.1.1.1. Market Revenue and Forecast (2020-2032)

11.1.2. Retail

11.1.2.1. Market Revenue and Forecast (2020-2032)

11.1.3. Consumer Goods

11.1.3.1. Market Revenue and Forecast (2020-2032)

11.1.4. Media & Entertainment

11.1.4.1. Market Revenue and Forecast (2020-2032)

11.1.5. IT & Telecommunications

11.1.5.1. Market Revenue and Forecast (2020-2032)

11.1.6. Others

11.1.6.1. Market Revenue and Forecast (2020-2032)

Chapter 12. Global Artificial Intelligence (AI) In Marketing Market, Regional Estimates and Trend Forecast

12.1. North America

12.1.1. Market Revenue and Forecast, by Component (2020-2032)

12.1.2. Market Revenue and Forecast, by Application (2020-2032)

12.1.3. Market Revenue and Forecast, by Technology (2020-2032)

12.1.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.1.5. U.S.

12.1.5.1. Market Revenue and Forecast, by Component (2020-2032)

12.1.5.2. Market Revenue and Forecast, by Application (2020-2032)

12.1.5.3. Market Revenue and Forecast, by Technology (2020-2032)

12.1.5.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.1.6. Rest of North America

12.1.6.1. Market Revenue and Forecast, by Component (2020-2032)

12.1.6.2. Market Revenue and Forecast, by Application (2020-2032)

12.1.6.3. Market Revenue and Forecast, by Technology (2020-2032)

12.1.6.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.2. Europe

12.2.1. Market Revenue and Forecast, by Component (2020-2032)

12.2.2. Market Revenue and Forecast, by Application (2020-2032)

12.2.3. Market Revenue and Forecast, by Technology (2020-2032)

12.2.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.2.5. UK

12.2.5.1. Market Revenue and Forecast, by Component (2020-2032)

12.2.5.2. Market Revenue and Forecast, by Application (2020-2032)

12.2.5.3. Market Revenue and Forecast, by Technology (2020-2032)

12.2.5.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.2.6. Germany

12.2.6.1. Market Revenue and Forecast, by Component (2020-2032)

12.2.6.2. Market Revenue and Forecast, by Application (2020-2032)

12.2.6.3. Market Revenue and Forecast, by Technology (2020-2032)

12.2.6.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.2.7. France

12.2.7.1. Market Revenue and Forecast, by Component (2020-2032)

12.2.7.2. Market Revenue and Forecast, by Application (2020-2032)

12.2.7.3. Market Revenue and Forecast, by Technology (2020-2032)

12.2.7.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.2.8. Rest of Europe

12.2.8.1. Market Revenue and Forecast, by Component (2020-2032)

12.2.8.2. Market Revenue and Forecast, by Application (2020-2032)

12.2.8.3. Market Revenue and Forecast, by Technology (2020-2032)

12.2.8.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.3. APAC

12.3.1. Market Revenue and Forecast, by Component (2020-2032)

12.3.2. Market Revenue and Forecast, by Application (2020-2032)

12.3.3. Market Revenue and Forecast, by Technology (2020-2032)

12.3.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.3.5. India

12.3.5.1. Market Revenue and Forecast, by Component (2020-2032)

12.3.5.2. Market Revenue and Forecast, by Application (2020-2032)

12.3.5.3. Market Revenue and Forecast, by Technology (2020-2032)

12.3.5.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.3.6. China

12.3.6.1. Market Revenue and Forecast, by Component (2020-2032)

12.3.6.2. Market Revenue and Forecast, by Application (2020-2032)

12.3.6.3. Market Revenue and Forecast, by Technology (2020-2032)

12.3.6.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.3.7. Japan

12.3.7.1. Market Revenue and Forecast, by Component (2020-2032)

12.3.7.2. Market Revenue and Forecast, by Application (2020-2032)

12.3.7.3. Market Revenue and Forecast, by Technology (2020-2032)

12.3.7.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.3.8. Rest of APAC

12.3.8.1. Market Revenue and Forecast, by Component (2020-2032)

12.3.8.2. Market Revenue and Forecast, by Application (2020-2032)

12.3.8.3. Market Revenue and Forecast, by Technology (2020-2032)

12.3.8.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.4. MEA

12.4.1. Market Revenue and Forecast, by Component (2020-2032)

12.4.2. Market Revenue and Forecast, by Application (2020-2032)

12.4.3. Market Revenue and Forecast, by Technology (2020-2032)

12.4.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.4.5. GCC

12.4.5.1. Market Revenue and Forecast, by Component (2020-2032)

12.4.5.2. Market Revenue and Forecast, by Application (2020-2032)

12.4.5.3. Market Revenue and Forecast, by Technology (2020-2032)

12.4.5.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.4.6. North Africa

12.4.6.1. Market Revenue and Forecast, by Component (2020-2032)

12.4.6.2. Market Revenue and Forecast, by Application (2020-2032)

12.4.6.3. Market Revenue and Forecast, by Technology (2020-2032)

12.4.6.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.4.7. South Africa

12.4.7.1. Market Revenue and Forecast, by Component (2020-2032)

12.4.7.2. Market Revenue and Forecast, by Application (2020-2032)

12.4.7.3. Market Revenue and Forecast, by Technology (2020-2032)

12.4.7.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.4.8. Rest of MEA

12.4.8.1. Market Revenue and Forecast, by Component (2020-2032)

12.4.8.2. Market Revenue and Forecast, by Application (2020-2032)

12.4.8.3. Market Revenue and Forecast, by Technology (2020-2032)

12.4.8.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.5. Latin America

12.5.1. Market Revenue and Forecast, by Component (2020-2032)

12.5.2. Market Revenue and Forecast, by Application (2020-2032)

12.5.3. Market Revenue and Forecast, by Technology (2020-2032)

12.5.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.5.5. Brazil

12.5.5.1. Market Revenue and Forecast, by Component (2020-2032)

12.5.5.2. Market Revenue and Forecast, by Application (2020-2032)

12.5.5.3. Market Revenue and Forecast, by Technology (2020-2032)

12.5.5.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

12.5.6. Rest of LATAM

12.5.6.1. Market Revenue and Forecast, by Component (2020-2032)

12.5.6.2. Market Revenue and Forecast, by Application (2020-2032)

12.5.6.3. Market Revenue and Forecast, by Technology (2020-2032)

12.5.6.4. Market Revenue and Forecast, by End-User Industry (2020-2032)

Chapter 13. Company Profiles

13.1. Amazon.com, Inc.

13.1.1. Company Overview

13.1.2. Product Offerings

13.1.3. Financial Performance

13.1.4. Recent Initiatives

13.2. Baidu, Inc.

13.2.1. Company Overview

13.2.2. Product Offerings

13.2.3. Financial Performance

13.2.4. Recent Initiatives

13.3. Google LLC

13.3.1. Company Overview

13.3.2. Product Offerings

13.3.3. Financial Performance

13.3.4. Recent Initiatives

13.4. Intel Corporation

13.4.1. Company Overview

13.4.2. Product Offerings

13.4.3. Financial Performance

13.4.4. Recent Initiatives

13.5. International Business Machines Corporation

13.5.1. Company Overview

13.5.2. Product Offerings

13.5.3. Financial Performance

13.5.4. Recent Initiatives

13.6. Microsoft Corporation

13.6.1. Company Overview

13.6.2. Product Offerings

13.6.3. Financial Performance

13.6.4. Recent Initiatives

13.7. NVIDIA Corporation            

13.7.1. Company Overview

13.7.2. Product Offerings

13.7.3. Financial Performance

13.7.4. Recent Initiatives

13.8. Oracle Corporation

13.8.1. Company Overview

13.8.2. Product Offerings

13.8.3. Financial Performance

13.8.4. Recent Initiatives

13.9. Salesforce, Inc.

13.9.1. Company Overview

13.9.2. Product Offerings

13.9.3. Financial Performance

13.9.4. Recent Initiatives

13.10. Twitter, Inc.

13.10.1. Company Overview

13.10.2. Product Offerings

13.10.3. Financial Performance

13.10.4. Recent Initiatives

Chapter 14. Research Methodology

14.1. Primary Research

14.2. Secondary Research

14.3. Assumptions

Chapter 15. Appendix

15.1. About Us

15.2. Glossary of Terms

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