Table. Technology-Driven Capabilities of Businesses via GAI Use.

Technology-Driven Capabilities Developed by Businesses Due to GAI Use Description Typical GAI Models Used Exemplar Cases by Companies
Data-driven marketing By using GAI, businesses can analyze user data, purchase records, browsing patterns, and demographics to create personalized messages that build trust and strong relationships with customers over time. Recommender systems using collaborative filtering, natural language generation models, recurrent neural networks, GANs Coca-Cola's GAI program, which allowed fans to engage with various branded components, generated 120,000 images in 11 days without paid ads, with users spending an average of eight minutes on the platform.
Predictive marketing Predictive marketing uses algorithms to analyze data from diverse sources like social media, search engines, and customer behavior. The data are used to create predictive models for forecasting future trends and consumer behavior. These models strengthen targeted marketing campaigns, thereby increasing their chances of success. Deep learning models such as CNNs or recurrent neural networks, GANs, probabilistic graphical models Jet Blue has used GAI to improve its chat operations, saving 280 seconds per chat and 73,000 agent hours in one quarter. This has given agents more time to help customers with complex issues.
Contextual marketing Businesses can create personalized marketing campaigns by understanding how consumers interact with their brands. This is possible using GAI, which allows for unique and tailored experiences for each customer. Reinforcement learning models, graph neural networks, context-aware recommender systems, sequence-to-sequence models with attention mechanisms Seedtag's AI platform, Liz, enables brands and agencies to create personalized and tailored creative content that matches the surrounding page-level context. This optimizes advertisements and seamlessly integrates them into the online environment, enhancing user experience.
Augmented marketing GAI algorithms create captivating content, enabling marketers to personalize ads, suggest products, and develop interactive experiences based on individual preferences. GANs, variational autoencoders; natural language generation models, content creation transformers such as GPT, interactive recommender systems, AI-powered augmented reality (AR) and virtual reality experiences RizzGPT is an eyepiece that uses AR to help with social anxiety in intense social situations. It combines GAI and AR to assist individuals during difficult conversations. The eyepiece has a camera, a microphone, and an internal projector screen that displays text in front of the user's eye. Using audio-to-text software, the glasses generate and show appropriate responses on the screen of the AR glasses.
Agile marketing The inclusion of GAI within the agile marketing process enables the utilization of decentralized, cross-functional teams to rapidly conceive, design, build, and validate products and marketing campaigns. Generative design systems, AI-powered content generation tools, natural language processing models Mitsui Chemicals Inc. has used GAI and IBM Watson to enhance its application discovery process. By integrating over 5 million data points from external sources into IBM Watson, the company has effectively analyzed these data alongside a dedicated product dictionary. This has led to a substantial expansion of their dictionary, increasing it nearly tenfold.

Source: V. Kumar, Philip Kotler, Shaphali Gupta, and Bharath Rajan, https://journals.sagepub.com/doi/10.1177/07439156241286499
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