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 2024-2033

Artificial Intelligence (AI) in Marketing Market Size and Growth 2024 to 2033

The global artificial intelligence (AI) in marketing market size was surpassed at USD 15.79 billion in 2023 and is expected to hit around USD 167.4 billion by 2033, growing at a CAGR of 26.63% from 2024 to 2033. Artificial intelligence (AI) is revolutionizing the marketing industry, offering unprecedented opportunities for businesses to engage with customers more effectively. From personalized recommendations to predictive analytics, AI is enabling marketers to create more targeted, efficient, and impactful campaigns. 

Artificial Intelligence (AI) in Marketing Market Size 2024 to 2033

Key Pointers

  • North America dominates the AI in marketing market, with a revenue share of 33% in 2023
  • Asia Pacific region is expected to grow with the fastest CAGR of 27.97% from 2024 to 2033. 
  • The content curation segment dominates the market with a revenue share of 24% in 2023.
  • The Machine learning (ML) segment dominates the market with a revenue share of 40% in 2023. 
  • The media & entertainment segment led the market with a revenue share of 25% in 2023. 
  • The IT and telecommunications industries is expected to grow with a CAGR of 24.94% from 2024 to 2033

What are the Growth Factors of Artificial Intelligence (AI) in Marketing Market?

The growth of the artificial intelligence (AI) in marketing market is primarily driven by an increasing demand for personalized customer experiences and the need for data-driven decision-making. AI technologies enable businesses to analyze vast amounts of data with remarkable speed and accuracy, facilitating highly targeted marketing strategies and enhancing customer engagement. The rise in consumer expectations for personalized interactions and the need for automation to streamline marketing processes further propel market growth. Additionally, advancements in machine learning, natural language processing, and predictive analytics are continuously expanding AI's capabilities, leading to innovative applications that enhance marketing effectiveness and efficiency.

What are the Trends is Artificial Intelligence (AI) in Marketing Market?

  • Personalization at Scale: AI is increasingly being used to deliver highly personalized content and recommendations, enhancing user engagement and satisfaction through tailored experiences based on individual behaviors and preferences.
  • Chatbots and Virtual Assistants: The adoption of AI-powered chatbots and virtual assistants is rising, providing real-time customer support, answering queries, and assisting in the sales process, thus improving customer service and operational efficiency.
  • Predictive Analytics: AI-driven predictive analytics is becoming more prevalent, helping marketers anticipate future trends, customer behaviors, and market shifts, which enables more strategic decision-making and targeted campaigns.
  • Content Generation: AI tools are being used to generate content, from automated social media posts to personalized email marketing messages, streamlining content creation processes and maintaining consistency across channels.
  • Visual and Voice Search: The integration of AI with visual and voice search technologies is growing, allowing users to search for products and services through images or voice commands, which is reshaping how consumers interact with brands.

What are the Challenges Faced by Artificial Intelligence (AI) in Marketing Market?

  • Data Privacy and Security: Ensuring the protection of consumer data and compliance with privacy regulations, such as GDPR and CCPA, is a significant challenge, as AI systems often rely on large amounts of personal data for analysis.
  • Data Quality and Integration: The effectiveness of AI in marketing depends on the quality and integration of data from various sources. Inconsistent or incomplete data can lead to inaccurate insights and ineffective marketing strategies.
  • High Costs and Complexity: Implementing and maintaining AI technologies can be expensive and complex, requiring significant investment in infrastructure, talent, and training, which can be a barrier for smaller businesses.
  • Algorithm Bias and Fairness: AI algorithms can inadvertently perpetuate biases present in the training data, leading to unfair or discriminatory marketing practices that may negatively impact certain customer groups.
  • Technology Integration: Integrating AI solutions with existing marketing systems and workflows can be challenging, requiring seamless compatibility and often necessitating changes to current processes.

Application Insights

The content curation segment dominates the market, with a revenue share of 24% in 2023.  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 40% in 2023. 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 25% in 2023. The rising AI advertising applications with significant traction are responsible for this high share. For example, in January 2023, 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 24.94% from 2024 to 2033. 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 2023. 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.

Artificial Intelligence (AI) in Marketing Market Share, By Region, 2023 (%)

Asia Pacific region is expected to grow with the fastest CAGR of 27.97% from 2024 to 2033. 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.

Who are the Top Manufactures in Artificial Intelligence (AI) in Marketing Market

  • Amazon.com, Inc.
  • Baidu, Inc.
  • Google LLC
  • Intel Corporation
  • International Business Machines Corporation
  • Microsoft Corporation
  • NVIDIA Corporation
  • Oracle Corporation
  • Salesforce, Inc.
  • Twitter, Inc.

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 Region

  • North Americ
  • Europe
  • Asia Pacific
  • Latin America
  • Middle East and 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.

The leading companies operating in the artificial intelligence (AI) in marketing market are Amazon.com, Inc., Baidu, Inc., Google LLC, Intel Corporation, International Business Machines Corporation, Microsoft Corporation, NVIDIA Corporation, Oracle Corporation, Salesforce, Inc., Twitter, Inc.

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, 2024-2033

8.1.1. Software

8.1.1.1. Market Revenue and Forecast (2021-2033)

8.1.2. Services

8.1.2.1. Market Revenue and Forecast (2021-2033)

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

9.1. Artificial Intelligence (AI) In Marketing Market, by Application, 2024-2033

9.1.1. Social Media Advertising

9.1.1.1. Market Revenue and Forecast (2021-2033)

9.1.2. Search Engine Marketing

9.1.2.1. Market Revenue and Forecast (2021-2033)

9.1.3. Virtual Assistant

9.1.3.1. Market Revenue and Forecast (2021-2033)

9.1.4. Content Curation

9.1.4.1. Market Revenue and Forecast (2021-2033)

9.1.5. Sales & Marketing Automation

9.1.5.1. Market Revenue and Forecast (2021-2033)

9.1.6. Analytics Platform

9.1.6.1. Market Revenue and Forecast (2021-2033)

9.1.7. Others

9.1.7.1. Market Revenue and Forecast (2021-2033)

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

10.1. Artificial Intelligence (AI) In Marketing Market, by Technology, 2024-2033

10.1.1. Machine Learning

10.1.1.1. Market Revenue and Forecast (2021-2033)

10.1.2. Natural Language Processing

10.1.2.1. Market Revenue and Forecast (2021-2033)

10.1.3. Computer Vision

10.1.3.1. Market Revenue and Forecast (2021-2033)

10.1.4. Others

10.1.4.1. Market Revenue and Forecast (2021-2033)

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, 2024-2033

11.1.1. BFSI

11.1.1.1. Market Revenue and Forecast (2021-2033)

11.1.2. Retail

11.1.2.1. Market Revenue and Forecast (2021-2033)

11.1.3. Consumer Goods

11.1.3.1. Market Revenue and Forecast (2021-2033)

11.1.4. Media & Entertainment

11.1.4.1. Market Revenue and Forecast (2021-2033)

11.1.5. IT & Telecommunications

11.1.5.1. Market Revenue and Forecast (2021-2033)

11.1.6. Others

11.1.6.1. Market Revenue and Forecast (2021-2033)

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 (2021-2033)

12.1.2. Market Revenue and Forecast, by Application (2021-2033)

12.1.3. Market Revenue and Forecast, by Technology (2021-2033)

12.1.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.1.5. U.S.

12.1.5.1. Market Revenue and Forecast, by Component (2021-2033)

12.1.5.2. Market Revenue and Forecast, by Application (2021-2033)

12.1.5.3. Market Revenue and Forecast, by Technology (2021-2033)

12.1.5.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.1.6. Rest of North America

12.1.6.1. Market Revenue and Forecast, by Component (2021-2033)

12.1.6.2. Market Revenue and Forecast, by Application (2021-2033)

12.1.6.3. Market Revenue and Forecast, by Technology (2021-2033)

12.1.6.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.2. Europe

12.2.1. Market Revenue and Forecast, by Component (2021-2033)

12.2.2. Market Revenue and Forecast, by Application (2021-2033)

12.2.3. Market Revenue and Forecast, by Technology (2021-2033)

12.2.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.2.5. UK

12.2.5.1. Market Revenue and Forecast, by Component (2021-2033)

12.2.5.2. Market Revenue and Forecast, by Application (2021-2033)

12.2.5.3. Market Revenue and Forecast, by Technology (2021-2033)

12.2.5.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.2.6. Germany

12.2.6.1. Market Revenue and Forecast, by Component (2021-2033)

12.2.6.2. Market Revenue and Forecast, by Application (2021-2033)

12.2.6.3. Market Revenue and Forecast, by Technology (2021-2033)

12.2.6.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.2.7. France

12.2.7.1. Market Revenue and Forecast, by Component (2021-2033)

12.2.7.2. Market Revenue and Forecast, by Application (2021-2033)

12.2.7.3. Market Revenue and Forecast, by Technology (2021-2033)

12.2.7.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.2.8. Rest of Europe

12.2.8.1. Market Revenue and Forecast, by Component (2021-2033)

12.2.8.2. Market Revenue and Forecast, by Application (2021-2033)

12.2.8.3. Market Revenue and Forecast, by Technology (2021-2033)

12.2.8.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.3. APAC

12.3.1. Market Revenue and Forecast, by Component (2021-2033)

12.3.2. Market Revenue and Forecast, by Application (2021-2033)

12.3.3. Market Revenue and Forecast, by Technology (2021-2033)

12.3.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.3.5. India

12.3.5.1. Market Revenue and Forecast, by Component (2021-2033)

12.3.5.2. Market Revenue and Forecast, by Application (2021-2033)

12.3.5.3. Market Revenue and Forecast, by Technology (2021-2033)

12.3.5.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.3.6. China

12.3.6.1. Market Revenue and Forecast, by Component (2021-2033)

12.3.6.2. Market Revenue and Forecast, by Application (2021-2033)

12.3.6.3. Market Revenue and Forecast, by Technology (2021-2033)

12.3.6.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.3.7. Japan

12.3.7.1. Market Revenue and Forecast, by Component (2021-2033)

12.3.7.2. Market Revenue and Forecast, by Application (2021-2033)

12.3.7.3. Market Revenue and Forecast, by Technology (2021-2033)

12.3.7.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.3.8. Rest of APAC

12.3.8.1. Market Revenue and Forecast, by Component (2021-2033)

12.3.8.2. Market Revenue and Forecast, by Application (2021-2033)

12.3.8.3. Market Revenue and Forecast, by Technology (2021-2033)

12.3.8.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.4. MEA

12.4.1. Market Revenue and Forecast, by Component (2021-2033)

12.4.2. Market Revenue and Forecast, by Application (2021-2033)

12.4.3. Market Revenue and Forecast, by Technology (2021-2033)

12.4.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.4.5. GCC

12.4.5.1. Market Revenue and Forecast, by Component (2021-2033)

12.4.5.2. Market Revenue and Forecast, by Application (2021-2033)

12.4.5.3. Market Revenue and Forecast, by Technology (2021-2033)

12.4.5.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.4.6. North Africa

12.4.6.1. Market Revenue and Forecast, by Component (2021-2033)

12.4.6.2. Market Revenue and Forecast, by Application (2021-2033)

12.4.6.3. Market Revenue and Forecast, by Technology (2021-2033)

12.4.6.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.4.7. South Africa

12.4.7.1. Market Revenue and Forecast, by Component (2021-2033)

12.4.7.2. Market Revenue and Forecast, by Application (2021-2033)

12.4.7.3. Market Revenue and Forecast, by Technology (2021-2033)

12.4.7.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.4.8. Rest of MEA

12.4.8.1. Market Revenue and Forecast, by Component (2021-2033)

12.4.8.2. Market Revenue and Forecast, by Application (2021-2033)

12.4.8.3. Market Revenue and Forecast, by Technology (2021-2033)

12.4.8.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.5. Latin America

12.5.1. Market Revenue and Forecast, by Component (2021-2033)

12.5.2. Market Revenue and Forecast, by Application (2021-2033)

12.5.3. Market Revenue and Forecast, by Technology (2021-2033)

12.5.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.5.5. Brazil

12.5.5.1. Market Revenue and Forecast, by Component (2021-2033)

12.5.5.2. Market Revenue and Forecast, by Application (2021-2033)

12.5.5.3. Market Revenue and Forecast, by Technology (2021-2033)

12.5.5.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

12.5.6. Rest of LATAM

12.5.6.1. Market Revenue and Forecast, by Component (2021-2033)

12.5.6.2. Market Revenue and Forecast, by Application (2021-2033)

12.5.6.3. Market Revenue and Forecast, by Technology (2021-2033)

12.5.6.4. Market Revenue and Forecast, by End-User Industry (2021-2033)

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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