Authors : Emmanuel Israel Ansah

Volume/Issue : Volume 10 - 2025, Issue 3 - March

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DOI : https://doi.org/10.38124/ijisrt/25mar1108

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Abstract : Artificial intelligence led to a marketing revolution by providing organizations with capabilities to personalize user experiences as well as optimize marketing operations and extract meanings from massive data pools for business choices. The marketing efficiency increases in parallel with automation of repetitive tasks by artificial intelligence solutions which contain machine learning algorithms predictive analytics and chatbots. Several disadvantages related to AI marketing innovations exist which include privacy concerns combined with ethical problems combined with environmental sustainability challenges. Algorithms generate ethical problems by sending discriminatory targeted advertisements which lead to biased treatment of specified customer groups during marketing campaigns. AI marketing solutions need large data collections that produce challenges regarding consumer privacy protection and regulatory requirements and data protection issues. Large- scale machine learning operations using AI models produce substantial carbon emissions which drives marketing stakeholders to adopt sustainable approaches in AI usage. To implement ethical sustainable AI businesses should use responsible AI frameworks along with bias mitigation solutions and clear AI policies that incorporate sustainable computing methods. The establishment of proper legislation creates necessary safeguards to address present-day difficulties. The General Data Protection Regulation (GDPR) along with AI governance law formations enables businesses to receive vital guidance for responsible implementation of AI in marketing activities. All companies must obey the regulations to protect their customer trust and prevent legal matters. The field of AI marketing solutions will evolve under three distinctive developments which include XAI for explainable AI initiatives coupled with green AI projects and governance models for ethical AI use. Businesses that use sustainable ethics with AI-driven marketing achieve better marketing performance and earn improved customer trust together with a more favourable lasting brand image. The study covers multiple aspects related to sustainable AI marketing solutions while providing forecasts about marketing AI development paths.

Keywords : AI-Powered Marketing; Hyper-Personalization; Predictive Analytics; Machine Learning in Marketing; Conversational AI; AI-driven Video Marketing; Dynamic Pricing; Sentiment Analysis; AI in Customer Engagement; Automated Ad Optimization; AI-Powered Loyalty Programs; Neuromarketing; AI in AR/VR Shopping; Ethical AI in Marketing; AI-driven Consumer Insights

References :

1. Business Insider. (2023). How Domino’s Uses AI to Optimize Voice Search Orders. Business Insider Tech Reports.
2. Business Insider. (2023). IKEA’s AR App and the Future of Online Shopping. Business Insider Tech Reports.
3. Deloitte. (2023). AI and AR: Transforming E-Commerce with Immersive Experiences. Deloitte Digital Insights.
4. Deloitte. (2023). AI-Powered Consumer Insights: The Future of Market Research. Deloitte Insights.
5. Deloitte. (2023). AI-Powered Voice Search Optimization: The Next Digital Frontier. Deloitte Digital Reports.
6. Forbes. (2023). McDonald's utilization of AI for market research highlights the adjustments this technology enables in market research regarding the plant-based trend. Forbes Business Review.
7. Google. (2023). AI technology with BERT allows companies to optimize voice search technology for future applications. Google Research Blog.
8. Li, X., Chen, Y., & Zhao, P. (2023). AI in Customer Sentiment Analysis: Applications and Trends. Journal of Digital Marketing, 15(3), 98-115.
9. Li, X., Chen, Y., & Zhao, P. (2023). AI-Powered Augmented Reality in Retail: Enhancing Consumer Engagement. Journal of Digital Marketing, 16(2), 105-123.
10. Li, X., Chen, Y., & Zhao, P. (2023). Natural Language Processing in AI-Driven Search: A Comprehensive Analysis. Journal of AI Research, 16(2), 80-105.
11. Smith, J., & Patel, R. (2023). AI-Driven Market Research: Transforming Consumer Feedback into Actionable Insights. Journal of Business Analytics, 19(2), 145-162.
12. Smith, J., & Patel, R. (2023). The Impact of AI-Driven AR on Online Shopping Behavior. Journal of Consumer Technology, 19(1), 89-112.
13. Smith, J., & Patel, R. (2023). The Role of AI in Voice Search Optimization: Trends and Strategies. Journal of Digital Marketing, 18(3), 95-118.
14. Smith, J., & Patel, R. (2023). Virtual Reality shopping receives a modern retail engagement through the implementation of personalization capabilities from artificial intelligence. Journal of Retail Technology, 17(2), 110-129.
15. TechCrunch. (2023). The Next-Generation Shopping Solution Alibaba Has Launched Is Known As 'Buy+ And Functions Through AI-Powered Virtual Technology. TechCrunch Retail Report.