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Global Artificial Intelligence (AI) In Marketing Market to reach USD 83.4 billion by the end of 2030.

Global Artificial Intelligence (AI) In Marketing Market Size study & Forecast, 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) and Regional Analysis, 2023-2030

Product Code: ICTNGT-19415901
Publish Date: 20-07-2023
Page: 200

Global Artificial Intelligence (AI) In Marketing Market is valued approximately at USD 12.64 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 26.6% over the forecast period 2023-2030. The artificial intelligence (AI) in marketing market refers to the use of advanced technologies, such as machine learning, natural language processing, and predictive analytics, to enhance and automate marketing activities and processes. It involves the application of AI algorithms and models to analyze customer data, predict consumer behavior, personalize marketing campaigns, optimize customer experiences, and improve overall marketing effectiveness, ultimately enabling businesses to make data-driven decisions and drive customer engagement and conversions. The Artificial Intelligence (AI) In Marketing Market is being driven by factors such as increasing investment in AI technology, rising spending on digital marketing and increasing adoption of AI on digital platforms for giving customize experience to customers.

Artificial Intelligence (AI) In Marketing involves the use of machine learning, data analysis, natural language processing, and other AI tools to automate tasks, gain insights from data, personalize marketing campaigns, improve customer targeting, and enhance overall marketing effectiveness. According to NetBase Quid via AI Index Report, Annual global corporate investment in artificial intelligence in 2020 was, USD 125.15 billion and in 2021 was USD 176.47. Further, the increasing investment in digital advertising activities has provided a fertile ground for the integration of AI technologies in marketing. AI’s ability to analyze data, automate processes, and deliver personalized experiences has driven its adoption and growth in the marketing industry. According to Statista, in year 2021 the global spending on digital advertisement stood at USD 522.5 billion which is projected to reach at USD 835.82 billion by year 2026. Thus rising spending on digital marketing is driving the market growth. Along with that increasing adoption of AI on digital platforms for giving customize experience to customers such as logical suggestion on e-commerce platforms for instance, Google Responsive Search Ads is a text ad format within Google Ads, an online advertising platform by Google. It allows advertisers to create dynamic ads with multiple headlines and descriptions for optimal customization. This feature empowers entrepreneurs to tailor their ads based on location, budget constraints, and other relevant factors. Thus, increasing investment in AI technology and increasing adoption of AI on digital platforms are. fueling the market growth. In addition to increasing adoption of marketing automation and increasing trend of advanced analytics & predictive modeling in marketing is create lucrative opportunities for the market growth. However, the data privacy and security concerns may hinders the market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Artificial Intelligence (AI) In Marketing Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the robust network of technology companies, startups, research institutions, and venture capital funding. This conducive environment fosters the development and adoption of AI technologies, including in the marketing sector. Asia Pacific is considered as the fastest growing region during the forecasted period due to rapid technology advancement and increasing business awareness and adoption of AI-powered marketing solutions are key factors influencing growth in this region.

Major market player included in this report are:
Amazon.com, Inc.
Baidu, Inc.
Google LLC
Intel Corporation
International Business Machines Corporation
Microsoft Corporation
NVIDIA Corporation
Oracle Corporation
Salesforce, Inc.
Twitter, Inc.

Recent Developments in the Market:
Ø In February 2023, Bain & Company and OpenAI have partnered to help businesses harness the power of AI. The Coca-Cola Company intends to leverage this collaboration to develop personalized advertising content through OpenAI’s ChatGPT and DALL-E platforms.
Global Artificial Intelligence (AI) In Marketing Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Component, Application, Technology, End User Industry, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

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 America
U.S.
Canada

Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC

Latin America
Brazil
Mexico

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Artificial Intelligence (AI) In Marketing Market, by region, 2020-2030 (USD Billion)
1.2.2. Artificial Intelligence (AI) In Marketing Market, by Component, 2020-2030 (USD Billion)
1.2.3. Artificial Intelligence (AI) In Marketing Market, by Application, 2020-2030 (USD Billion)
1.2.4. Artificial Intelligence (AI) In Marketing Market, by Technology, 2020-2030 (USD Billion)
1.2.5. Artificial Intelligence (AI) In Marketing Market, by End User Industry, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Artificial Intelligence (AI) In Marketing Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Artificial Intelligence (AI) In Marketing Market Dynamics
3.1. Artificial Intelligence (AI) In Marketing Market Impact Analysis (2020-2030)
3.1.1. Market Drivers
3.1.1.1. Increasing investment in AI technology.
3.1.1.2. Increasing adoption of AI on digital platform.
3.1.1.3. Rising investment on digital marketing
3.1.2. Market Challenges
3.1.2.1. Data Privacy and Security Concerns.
3.1.3. Market Opportunities
3.1.3.1. Increasing adoption of marketing automation.
3.1.3.2. Increasing trend of advanced analytics & predictive modeling in marketing.
Chapter 4. Global Artificial Intelligence (AI) In Marketing Market: Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economic
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Artificial Intelligence (AI) In Marketing Market, by Component
5.1. Market Snapshot
5.2. Global Artificial Intelligence (AI) In Marketing Market by Component, Performance – Potential Analysis
5.3. Global Artificial Intelligence (AI) In Marketing Market Estimates & Forecasts by Component 2020-2030 (USD Billion)
5.4. Artificial Intelligence (AI) In Marketing Market , Sub Segment Analysis
5.4.1. Software
5.4.2. Services
Chapter 6. Global Artificial Intelligence (AI) In Marketing Market, by Application
6.1. Market Snapshot
6.2. Global Artificial Intelligence (AI) In Marketing Market by Application, Performance – Potential Analysis
6.3. Global Artificial Intelligence (AI) In Marketing Market Estimates & Forecasts by Application 2020-2030 (USD Billion)
6.4. Artificial Intelligence (AI) In Marketing Market , Sub Segment Analysis
6.4.1. Social Media Advertising
6.4.2. Search Engine Marketing
6.4.3. Virtual Assistant
6.4.4. Content Curation
6.4.5. Sales & Marketing Automation
6.4.6. Analytics Platform
6.4.7. Others
Chapter 7. Global Artificial Intelligence (AI) In Marketing Market, by Technology
7.1. Market Snapshot
7.2. Global Artificial Intelligence (AI) In Marketing Market by Technology, Performance – Potential Analysis
7.3. Global Artificial Intelligence (AI) In Marketing Market Estimates & Forecasts by Technology 2020-2030 (USD Billion)
7.4. Artificial Intelligence (AI) In Marketing Market , Sub Segment Analysis
7.4.1. Machine Learning
7.4.2. Natural Language Processing
7.4.3. Computer Vision
7.4.4. Others
Chapter 8. Global Artificial Intelligence (AI) In Marketing Market, by End User Industry
8.1. Market Snapshot
8.2. Global Artificial Intelligence (AI) In Marketing Market by End User Industry, Performance – Potential Analysis
8.3. Global Artificial Intelligence (AI) In Marketing Market Estimates & Forecasts by End User Industry 2020-2030 (USD Billion)
8.4. Artificial Intelligence (AI) In Marketing Market , Sub Segment Analysis
8.4.1. BFSI
8.4.2. Retail
8.4.3. Consumer Goods
8.4.4. Media & Entertainment
8.4.5. IT & Telecommunications
8.4.6. Others
Chapter 9. Global Artificial Intelligence (AI) In Marketing Market, Regional Analysis
9.1. Top Leading Countries
9.2. Top Emerging Countries
9.3. Artificial Intelligence (AI) In Marketing Market , Regional Market Snapshot
9.4. North America Artificial Intelligence (AI) In Marketing Market
9.4.1. U.S. Artificial Intelligence (AI) In Marketing Market
9.4.1.1. Component breakdown estimates & forecasts, 2020-2030
9.4.1.2. Application breakdown estimates & forecasts, 2020-2030
9.4.1.3. Technology breakdown estimates & forecasts, 2020-2030
9.4.1.4. End User Industry breakdown estimates & forecasts, 2020-2030
9.4.2. Canada Artificial Intelligence (AI) In Marketing Market
9.5. Europe Artificial Intelligence (AI) In Marketing Market Snapshot
9.5.1. U.K. Artificial Intelligence (AI) In Marketing Market
9.5.2. Germany Artificial Intelligence (AI) In Marketing Market
9.5.3. France Artificial Intelligence (AI) In Marketing Market
9.5.4. Spain Artificial Intelligence (AI) In Marketing Market
9.5.5. Italy Artificial Intelligence (AI) In Marketing Market
9.5.6. Rest of Europe Artificial Intelligence (AI) In Marketing Market
9.6. Asia-Pacific Artificial Intelligence (AI) In Marketing Market Snapshot
9.6.1. China Artificial Intelligence (AI) In Marketing Market
9.6.2. India Artificial Intelligence (AI) In Marketing Market
9.6.3. Japan Artificial Intelligence (AI) In Marketing Market
9.6.4. Australia Artificial Intelligence (AI) In Marketing Market
9.6.5. South Korea Artificial Intelligence (AI) In Marketing Market
9.6.6. Rest of Asia Pacific Artificial Intelligence (AI) In Marketing Market
9.7. Latin America Artificial Intelligence (AI) In Marketing Market Snapshot
9.7.1. Brazil Artificial Intelligence (AI) In Marketing Market
9.7.2. Mexico Artificial Intelligence (AI) In Marketing Market
9.8. Middle East & Africa Artificial Intelligence (AI) In Marketing Market
9.8.1. Saudi Arabia Artificial Intelligence (AI) In Marketing Market
9.8.2. South Africa Artificial Intelligence (AI) In Marketing Market
9.8.3. Rest of Middle East & Africa Artificial Intelligence (AI) In Marketing Market

Chapter 10. Competitive Intelligence
10.1. Key Company SWOT Analysis
10.1.1. Company 1
10.1.2. Company 2
10.1.3. Company 3
10.2. Top Market Strategies
10.3. Company Profiles
10.3.1. Amazon.com, Inc.
10.3.1.1. Key Information
10.3.1.2. Overview
10.3.1.3. Financial (Subject to Data Availability)
10.3.1.4. Product Summary
10.3.1.5. Recent Developments
10.3.2. Baidu, Inc.
10.3.3. Google LLC
10.3.4. Intel Corporation
10.3.5. International Business Machines Corporation
10.3.6. Microsoft Corporation
10.3.7. NVIDIA Corporation
10.3.8. Oracle Corporation
10.3.9. Salesforce, Inc.
10.3.10. Twitter, Inc.
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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