Generative AI has moved beyond the stages of experimentation as real use cases gain momentum in almost every industry. You can notice generative AI applications for enterprises in different business functions, whether it is marketing, user engagement or product innovation. Contrary to general assumptions that generative AI is an idea for the future, it has found applications with tangible benefits for businesses.
Generative AI is an integral component in business strategy with companies seeking enterprise solutions tailored to their business goals. Business owners want to learn how to use generative AI effectively to boost innovation and efficiency alongside enhancing customer experiences. An overview of the applications of generative AI for businesses in the real world can help you understand its significance for long-term growth.
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Unraveling the Applications of Generative AI for Businesses
Many people believe that generative AI represents ChatGPT and similar AI tools that have gained popularity in recent times. You can find answers to “What are the applications of generative AI in business?” as a sharp contrast to the general assumptions. Businesses would need special solutions built to achieve their goals in alignment with their business strategy and vision. Generative AI solutions for businesses must incorporate AI strategies, integrations and tools built for specific use cases.
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Software Development
Companies can leverage generative AI to write and refine code as well as implement solutions for automated software testing. You can use generative AI to write code snippets or complete functions with the help of simple prompts. As a result, developers can spend less time on repetitive tasks in software development. GitHub Copilot is the best example of generative AI in action for writing code with the facility of real-time code suggestions.
AI-powered testing tools can help businesses generate test cases automatically to cover diverse scenarios. As a result, a dedicated generative AI app for testing can detect security flaws and bugs in the early stages of development. Businesses can also accelerate their software development workflows with generative AI tools highlighting areas for improvement in code.
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Financial Services
The financial services industry is also another playground for showcasing adoption of AI in real world use cases. You can come across multiple examples of the applications of AI in financial services for compliance automation, fraud detection and personalizing financial advice. The real world applications of generative AI in banking and financial services industry help in maintaining regulatory compliance without delay. Big names in the banking industry leverage generative AI to identify new updates from regulatory authorities and create new compliance reports accordingly.
Another prominent application of generative AI in financial services points at personalization of financial advice. Wells Fargo utilizes generative AI to recommend optimal investment strategies according to the individual portfolios and risk appetite of investors. Furthermore, AI models can support comprehensive analysis of financial transactions to identify anomalies and patterns which indicate possibilities of fraud. Banks can use generative AI to simulate examples of fraudulent transactions and train models to recognize such transactions instantly.
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Customer Support
Customer support is the biggest concern for any business as it can make or break the brand identity of the business. The two prominent activities in customer support include responding to customer queries and resolving their issues. You can notice diverse examples of generative AI applications for enterprises in the domain of customer support, irrespective of the industry. Businesses can use generative AI for automation of customer support to improve complaint resolution rate and customer satisfaction. Most important of all, AI-powered customer support also helps businesses provide consistent service across multiple languages.
Managing customer queries is also another distinctive aspect of customer support, which businesses can improve with generative AI. Customers may ask for different types of information, including service explanation, pricing details or the order status. Generative AI can help businesses provide automated responses to routine queries, thereby reducing response times. On top of it, businesses can use generative AI to personalize inquiry management according to the customer’s context.
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Developing Content for Marketing
The common applications of generative AI for businesses in the real world are largely evident in the creation of marketing content. Many businesses use generative AI tools to create blogs, ad copies, and social media posts for their marketing campaigns. One of the top examples of real world applications of generative AI in developing marketing content is Coca Cola. The global beverage giant used AI to generate artwork from their brand assets for the “Create Real Magic” campaign.
Generative AI also serves as a powerful tool to create personalized email campaigns that reach individual customers. Businesses can use generative AI tools to analyze customer data, including details of browsing history and past transactions. Subsequently, businesses can rely on generative AI to write emails with relevant product recommendations and messages to each individual.
The biggest advantage of using generative AI to create marketing content is evident in the creation of social media content. You can just give a prompt with a topic and the platform you want to create the post for and generative AI will deliver exceptional posts.
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Healthcare and Life Sciences
Generative AI offers a completely new perspective for businesses in the healthcare and life sciences industry with diverse benefits. For example, you can find many instances where generative AI has helped in accelerative drug discovery. As compared to human researchers, generative AI can complete comprehensive analysis of new molecules and their interactions through different simulations. Insilico Medicine is one of the examples of businesses using generative AI to discover new medications.
The answers to “What are the applications of generative AI in business?” in the healthcare sector will also point towards scheduling and office management. Custom generative AI solutions can help healthcare providers manage their office operations from a central dashboard. In addition, generative AI tools can also provide personalized treatment plans for patients based on their medical history.
Another prominent application of generative AI in healthcare is evident in medical imaging analysis. Radiologists can use generative AI to scan medical images and discover patterns which may not be visible to humans. On top of it, generative AI also helps in reducing noise in medical images without losing any detail.
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Research and Development
Generative AI applications for businesses also cover different stages of research and development. Businesses can use generative AI for product design, feasibility studies, and prototype development in their R&D initiatives. The real world applications of generative AI can help with automation of different parts of the product design process. You can find more design options and accelerate the process from conceptualization to production with generative AI tools.
Businesses have also utilized generative AI to create detailed simulations for feasibility studies. The predictive analytics capabilities in generative AI help in analyzing data and predicting outcomes for different scenarios. As a result, businesses can make informed decisions about product development while reducing risks and ensuring efficient resource allocation.
Final Thoughts
The examples of applications of generative AI reveal how businesses use it in different capacities. You can find a generative AI app for almost every business function ranging from product development to marketing. Interestingly, businesses in different industries also leverage generative AI for enhancements in various areas. Learn more about the utility of generative AI in the modern technological landscape now.
About Author
David Miller is a dedicated content writer and customer relationship specialist at Future Skills Academy. With a passion for technology, he specializes in crafting insightful articles on AI, machine learning, and deep learning. David's expertise lies in creating engaging content that educates and inspires readers, helping them stay updated on the latest trends and advancements in the tech industry.
