![References
Borkakoty, K. (2025, February 7). 4 best AI in marketing examples [+ use
cases]. Sprinklr. https://www.sprinklr.com/blog/ai-in-marketing-examples/
Davenport, T. H., Guha, A., & Grewal, D. (2021, July 1). How to design an
AI marketing strategy. Harvard Business Review.
https://hbr.org/2021/07/how-to-design-an-ai-marketing-strategy#
Jones, S. (2024, May 29). Harnessing AI to Revolutionise Your Digital
Marketing Strategy. LinkedIn. https://www.linkedin.com/pulse/harnessing-
ai-revolutionise-your-digital-marketing-strategy-jones-dhu8e/
Keenan, N. (2023, October 25). The impact of AI on Social Media, Pros &
Cons. The impact of AI on social media, pros & cons.
https://www.bornsocial.co/post/impact-of-ai-on-social-media
Mucci, T. (2025, June 18). The history of Artificial Intelligence. IBM.
https://www.ibm.com/think/topics/history](https://image.slidesharecdn.com/aiandsocialmedia-250818014239-6fb7544a/85/AI-usage-and-the-Social-Media-Marketing-World-16-320.jpg)
AI usage and the Social Media Marketing World
- 1. Artificial Intelligence and Social Media Marketing Nicholas A. Noviello Thomas Edison State University SOM 7020- Social Media Marketing Dr. David Castle August 17, 2025
- 2. Artificial Intelligence and Social Media Marketing AI-powered marketing is the way forward for many social media platforms. AI has vastly enhanced marketing activities for many companies, increasing their productivity and customer satisfaction. These primary focuses help build customer relationships through personalized content, data analysis, metrics that allow leaders to make informed decisions, and content creation and optimization based on customer needs and information collected. Building data sets linked to the strategies developed helps continuously analyze the needs of both the business goals and the customers through the social media platform. Personalizing the platforms for the customer using AI has transformed the marketing strategies to an all- time high. Increasing efficiency can vastly improve overall workload and sales, building long-lasting customer relationships and service reputation for the brand.
- 3. Concepts of Artificial Intelligence (AI) Machine Learning (ML) analyzes patterns in data to help make predictions and form algorithm sets. These algorithms are trained using large quantities of data to make relatively complex predictions and decisions to decipher text, segment customers, and anticipate how customers will respond (Davenport, 2021). Natural Language Processing (NLP) enables computers and digital devices to recognize, understand, and generate text and speech by combining computational linguistics, rule-based human language modeling, statistical modeling, machine learning, and deep learning(Stryker, 2024). Generative AI is helpful for the company because it uses data and sets that customers frequent to create new content that can be included in marketing campaigns that meet strategy goals. This process adds to the efficiency and timeliness when releasing multiple campaigns on different platforms. It can also be used for various audience demographics to meet their product needs and capture new customers, adding to the audience growth. Predictive Analytics is when the system uses historical data to help assess and predict future trends that may benefit the organization. This can help with future sales forecasting, predict the customer's needs or decisions before purchasing, and further solidify the relationship.
- 4. Future of Social Media Marketing AI is the future of marketing, and companies will need the tool to stay competitive in their industry and meet strategic business goals. By using AI tools, companies can enhance the social media experience to determine the customers' needs, build efficiencies for business practices within the organization, and improve customer satisfaction and relationships and longevity to the company's success. The focus of leadership is to collect data and use it in strategies and decision-making. Being a business that executes strategies based on data-driven decisions with AI will optimize results in both the campaigns on social media and the customer experience.
- 6. History of AI(continued) 1950s: The term Artificial Intelligence was coined. Marvin Minsky and Dean Edmunds built the first artificial neural network. 1960s: Research was expanded to include natural language processing. Joseph Weizenbaum developed ELIZA 9, a program that mimics human conversation by responding to typed input in natural language. 1970s and 1980s: AI experienced an “AI Winter.” At the annual meeting of the Association for the Advancement of Artificial Intelligence (AAAI), Roger Schank and Marvin Minsky cautioned about an impending "AI Winter," predicting that inflated expectations surrounding AI would soon lead to a collapse in investment and research. 1990s and 2000s: The development of Bayesian networks, the resurgence of neural networks, and the increasing data availability led to renewed interest and progress in AI. 2020- Present: The field has seen rapid growth, particularly with the rise of deep learning, large language models, and generative AI. These advancements have led to significant progress in image and speech recognition, natural language understanding, and game-playing.
- 7. Pros and Cons of AI
- 8. Pros and Cons of AI(continued) Pros: Personalization, Efficiency, Content Creation • One of AI’s best features is its ability to personalize users' experiences on social media platforms. AI algorithms customize news feeds and recommendations, tailoring content to user preferences, resulting in a more engaging experience (Keenan, 2023). • Efficiency with AI has helped streamline workflow by building data sets and analyzing information to help meet strategy delivery. From streamlining content to automatically releasing campaigns, the process is more efficient and structured with the help of AI tools. • Content creation is made by analyzing data and preferences, which can produce a high-quality visual aid or text that markets to the user. Cons: Data/Privacy breaches, Misinformation, Impact on Employment • Data and privacy breaches for both the user and the company are risks of AI. The amount of information online and in databases increases the chances of breaches. • If AI sets and data are not collected accurately, they can be algorithms that lead to misinformation or information that the company isn’t aligned with. • Concerns are that automation of content generation and moderation will lead to job loss in the coalition media and marketing industry (Keenan, 2023).
- 9. AI in Action LinkedIn has embraced AI and implemented it into its daily operations and marketing campaigns. LinkedIn offers AI-powered suggestions to help users optimize their profiles (Silver, 2024). AI helps create profiles promoting professional interest and future job opportunities. The building blocks of the profile then set algorithms for networks in career fields, job opportunities, career development, and continuing education. Once a profile is established, AI tools enhance mutual connections, articles of industry importance, future employment, and endless information for the career field.
- 10. AI in Action(continuned) Amazon is another company that uses AI in daily marketing to give customers a more personalized experience every time they open an account. Amazon uses its AI to line up products on your screen, betting on which ones will win your heart — and your wallet (Borkakoty, 2025). The AI sifts through the vast ocean of data: your past purchases, items lingering in your cart, products you've looked at but never bought, and the top-trending items among other shoppers. That's Amazon's AI playing matchmaker between you and things you didn't even know you needed!
- 11. AI Relevance Five relevant concepts are shaping AI and social media platforms for marketing. 1) Personalization: AI algorithms analyze user data, such as browsing behavior, purchase history, and demographic information, to create tailored content and recommendations (Jones, 2024). This approach is the way forward for all social media marketing; the customer audience and their preferences become a priority in the marketing strategy. 2) Enhancing Customer Experience with Chatbots: Customer experience is a top priority, and allowing AI to have a real-time connection with the customer to answer and assist with questions or tasks is highly beneficial for customer loyalty. These virtual assistants can handle customer inquiries, provide product recommendations, and even complete transactions. Offering 24/7 customer support significantly enhances customer.
- 12. AI Relevance(continued) 3) Predictive Analytics: Understanding the future and changing trends is vital for the organization and marketing team. By analyzing past customer interactions and transactions, AI can predict future actions, such as the likelihood of a purchase or churn (Jones, 2024). 4) Advertising and AI: Programmatic advertising, which uses AI to automate the buying and selling of online ads, has revolutionized digital advertising. AI algorithms analyze user data in real-time to deliver highly targeted ads to the right audience at the right time. This level of precision maximizes the return on ad spend. 5) Content Creation: Producing high-quality visuals or text that can reach customers with new products or concepts is key in the marketing strategy. Tools like GPT-3, developed by OpenAI, can generate human-like text based on given prompts, making it possible to create content at scale. These AI-driven tools can produce blog posts, social media updates, and even ad copy, reducing the time and effort required for content creation (Jones, 2024).
- 13. The Future Social media has become a part of most people's everyday lives. With the support of AI, the process can be personalized and enhanced to reach a larger audience more efficiently and promptly. Future of Generative AI • Generative AI has opened up new possibilities for content creators and marketers, allowing them to create personalized and engaging content at scale (Spair, 2024). Using a streamlined process that enhances productivity while meeting business goals and customer satisfaction is revolutionary. Future of Ethical Implications • Ethical concerns continue to challenge companies' use of AI. Moving into the future will not change these concepts. It’s essential to challenge implementation to protect the customer and company from ethical issues and privacy breaches. • Generative AI models learn from existing data, which may contain biases and prejudices. If these biases are not addressed, generative AI algorithms can perpetuate and amplify societal biases (Spair, 2024). • A human factor is the only way to address or prevent this. Ensure algorithms follow the proper pathway and that truthful information is maintained.
- 14. The Future(continued) Future of AI Marketing • Marketing through social media channels continues to expand, and AI will only enhance the effectiveness and efficiency of the delivery. • Traditional advertising methods often rely on demographic information such as age, gender, and location to target ads to specific audiences. At the same time, generative AI can take personalization to the next level by analyzing user data and preferences to create highly personalized ads (Spair, 2024). • Using the benefits of AI to enhance and streamline the delivery of marketing is key. The opportunities to release content, update information, and reach audiences with an algorithm change are powerful. They will only continue to go untapped resources if used correctly with the right marketing strategies.
- 15. Conclusion AI is here to stay, and like all tools and applications, the system needs to be used and monitored responsibly at the organizational level. The goal is to use the tool to enhance the customer experience, build sales, and sustain competitiveness, but doing so in a manner that doesn’t corrupt a system, breach privacy, or violate other ethical topics needs to be standardized. AI will continue transforming social media platforms, benefiting users and businesses. Still, the human factor must continue monitoring the process while making key data-driven decisions to build strategies that a computer function should never take over.
- 16. References Borkakoty, K. (2025, February 7). 4 best AI in marketing examples [+ use cases]. Sprinklr. https://www.sprinklr.com/blog/ai-in-marketing-examples/ Davenport, T. H., Guha, A., & Grewal, D. (2021, July 1). How to design an AI marketing strategy. Harvard Business Review. https://hbr.org/2021/07/how-to-design-an-ai-marketing-strategy# Jones, S. (2024, May 29). Harnessing AI to Revolutionise Your Digital Marketing Strategy. LinkedIn. https://www.linkedin.com/pulse/harnessing- ai-revolutionise-your-digital-marketing-strategy-jones-dhu8e/ Keenan, N. (2023, October 25). The impact of AI on Social Media, Pros & Cons. The impact of AI on social media, pros & cons. https://www.bornsocial.co/post/impact-of-ai-on-social-media Mucci, T. (2025, June 18). The history of Artificial Intelligence. IBM. https://www.ibm.com/think/topics/history
- 17. References Silver, T. K. (2024, September 4). The use of AI on linkedin: Current features and future prospects. LinkedIn. https://www.linkedin.com/pulse/use-ai-linkedin-current-features-future- prospects-tony-k-silver-wyl0f/ Spair, R. (2024, January 20). The future of social media: How generative AI is revolutionizing the way we connect. Medium. https://medium.com/@dxtoday/the-future-of-social-media-how- generative-ai-is-revolutionizing-the-way-we-connect-3df7a5489473# Stryker, C., & Holdsworth, J. (2025, July 24). What is NLP (Natural Language Processing)?. IBM. https://www.ibm.com/think/topics/natural- language-processing#:~:text=Natural%20language%20processing %20(NLP)%20is,Apple’s%20Siri%20and%20Microsoft’s%20Cortana.
Editor's Notes
- #6: 1950s :The Stochastic Neural Analog Reinforcement Calculator (SNARC) is an early attempt to model learning processes in the human brain, specifically through reinforcement learning(Mucci, 2024). 1960s: Although Weizenbaum intended to show the superficiality of human-computer communication, he was surprised by how many users attributed human-like emotions to the program, raising ethical questions about AI and human interaction.
- #12: Predictive Analytics: By having vital data and generating forecasts for the future, the marketing team and leadership can pivot and make sound decisions based on AI forces Advertising:: The delivery of specific campaigns to certain demographics automatically is a massive advance for marketing and advertising. By the slightest change in an algorithm, entirely new demographics can be reached for a product launch or campaign renewal.