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    Generative AI is a powerful tool that can automate tasks, generate new ideas, and provide insights. This can help businesses innovate faster, improve productivity, and reduce costs. For example, generative AI can be used to automate customer service tasks, create personalized shopping experiences, and optimize inventory and pricing. As generative AI continues to develop, it will become even more powerful and versatile. Businesses that embrace this technology will be well-positioned to succeed in the future.

    Generative AI models have been successfully integrated into various existing business frameworks. However, in order to unlock their full potential, businesses need to ensure the followings while integrating it to the existing frameworks:

    • Identifying the right use cases: The first step is to identify the right use cases for generative AI. This means identifying tasks that can be automated, or areas where new ideas and insights are needed.
    • Gathering the right data: Once the use cases have been identified, enterprises need to gather the right data. This data will be used to train the generative AI models.
    • Building the right infrastructure: Enterprises also need to build the right infrastructure to support generative AI models. This includes ensuring that there is enough computing power and storage space.
    • Testing and iterating: Once the models are built, they need to be tested and iterated. This means testing the models on different datasets and making changes as needed

    How Much Profits Can Generative AI Generate?

    According to our recent survey, most of the business owners ask, can generative AI generate revenue? But the question should be how much profits it can generate, because it is quite obvious that generative AI has full potential to generate revenue.

    The actual profits that generative AI can generate will vary depending on the specific application and the business that is using it. However, some estimates suggest that the generative AI market could be worth up to $4.4 trillion by 2028. This is due to the many potential applications of generative AI, which can help businesses to save time and money, improve productivity, and create new products and services.

    Key Insights:

    • A study by Gartner found that 40% of marketing and advertising professionals are already using generative AI, and that number is expected to grow to 70% by 2025.

    • Grand View Research found that the global market for generative AI in technology is expected to reach $18.2 billion by 2025. 

    • Studied by several organizations predict that global market for generative AI in finance, healthcare and retail industry is expected to reach $10 billion by 2025. 

     

     

    Generative AI Applications in Various Industries

    As mentioned above, the actual profits that generative AI can generate varies on the application and the business strategy. We have developed and implemented various generative AI-powered applications which are helping enterprises to solve real-world industry problems and boost their revenue. Browse through the applications for better understanding and choose the suitable application for your business needs.

    Customer Churn Predictions

    Stop Losing Customers

    Using generative AI to predict the customers that are more likely to churn based on the historical data collected and curated from different data sources.

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    Sentiment Analysis

    Know Your Customers

    Leveraging generative AI, NLP and ML models to perform sentiment analysis on various types of text, such as customer reviews, social media posts, or support tickets.

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    Predictive Maintenance

    Lower Operational Costs

    With generative AI-powered predictive maintenance systems, we can identify potential equipment failures or maintenance needs before they occur, enabling timely repair.

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