What is Artificial Intelligence in Marketing?

The Artificial Intelligence in Marketing Market integrates machine learning, NLP, computer vision, and predictive analytics to revolutionize marketing functions, enabling hyper-personalized, data-driven, and autonomous decision-making across customer journeys. It elevates marketing from reactive to predictive and prescriptive strategies, reshaping customer engagement, loyalty, and lifetime value.

AI in marketing is acting as a disruptive force by introducing new intelligent content creation tools (New), simplifying campaign optimization through automated platforms (Easy), ensuring safer compliance via explainable AI (Safe), and unlocking massive scale personalization across millions of touchpoints (Big). This shift is compelling CMOs and business leaders to reimagine customer-centricity with AI-first mindsets.

Market Size:

Artificial Intelligence in Marketing Market was valued at USD 35.11 billion in 2024 and is projected to reach USD 211.77 billion by 2030 at a CAGR of 35%.

Key Companies:

•    Oculus360 (US)
•    Twitter (US)
•    Oracle (US)
•    InsideSales (US)
•    Persado (US)
•    Mariana (US)
•    Drawbridge (US)
•    Narrative Science (US)
•    Appier (US)
•    GumGum (US)
•    Zensed (Sweden)
•    NVIDIA (US)
•    Intel (US)
•    IBM (US)
•    Micron (US)
•    Samsung Electronics (Korea)
•    Xilinx (US)
•    Amazon (US)
•    Alphabet (US)
•    Facebook (US)
•    Microsoft (US)
•    Salesforce (US)
•    Baidu (China)
•    Sentient Technologies (US)
•    Albert Technologies (Israel)

Case Study:

Albert Technologies empowered a retail brand to autonomously optimize digital campaigns, leading to a 30% improvement in ROAS within 60 days by leveraging real-time adaptive learning.

Popularity & Key Statistics:

•    72% of enterprises are actively integrating AI in customer experience strategies.
•    High demand for AI-driven personalization, content intelligence, and sentiment analysis.
•    AI-generated content expected to drive 50% of marketing outputs by 2026.

Market Segmentation:

By Type

•    Machine Learning
o    Supervised Learning
o    Unsupervised Learning
o    Reinforcement Learning
•    Natural Language Processing (NLP)
•    Computer Vision
•    Predictive Analytics
•    Context-Aware Computing
•    Speech Recognition
•    Generative AI
•    Chatbots & Virtual Assistants
•    Intelligent Customer Data Platforms
•    Others (including Knowledge Graphs, Decision Engines)

By End User

•    Retail & E-Commerce
•    BFSI (Banking, Financial Services & Insurance)
•    Media & Entertainment
•    Telecom & IT
•    Healthcare & Life Sciences
•    Automotive & Transportation
•    Consumer Goods
•    Travel & Hospitality
•    Real Estate
•    Others (including Education, Energy & Utilities)

What’s in It for You?

•    Identify white spaces in AI-driven MarTech stacks and revenue models.
•    Leverage insights on emerging customer behavior driven by AI personalization.
•    Understand strategic shifts in ad-tech, content tech, and customer data platforms.
•    Benchmark key players’ AI innovation approaches and partnership ecosystems.