20 Examples of Generative AI Applications Across Industries

Written by Coursera Staff • Updated on

Explore 20 generative AI applications across six industries, including health care, advertising and marketing, manufacturing, software development, financial services, and entertainment.

[Featured Image] A doctor uses a generative AI application on her tablet to help with early detection of disease.

Generative artificial intelligence (AI) is a trend just beginning its journey to the mainstream. Gartner projects that by 2026, over 100 million people will use generative AI to help them complete their work [1]. McKinsey looked at 63 different uses for generative AI and concluded that, if they were all implemented, the technology could add $2.6 trillion to $4.4 trillion worth of value to the global economy [2].

In this article, you’ll learn 20 examples of generative AI applications in various industries and how to start using generative AI for your organization.

What is generative AI?

Generative AI is artificial intelligence designed to create unique text or image results in response to user prompts. The technology uses machine learning to return an output based on the user’s prompt. AI engineers train the technology using large data sets, which the model consults when determining the best possible answer to a prompt. Another way to look at generative AI is as a form of predictive artificial intelligence. Based on the information provided, generative AI will predict which words and in which order will give the best answer to the user's prompts.

You can use generative AI to create new written, visual, or audio content, summarize complex data, generate code, assist with repetitive tasks, or make customer service more personalized.

Examples of generative AI

Examples of generative artificial intelligence that you may have heard of include Google’s Bard, ChatGPT, or DALL-E from OpenAI.

  • ChatGPT or DALL-E: Generative artificial intelligence created by OpenAI, a Microsoft-backed, profit-capped company with the mission to develop artificial intelligence to serve humankind

  • Google Bard: Google’s generative AI with integrations to Google products like Google Lens and Gmail, operating with a language model called PaLM-2 that was trained on the largest data set out of all generative AI models available at the time of its release

Applications of generative AI

Generative artificial intelligence has applications in diverse industries such as health care, manufacturing, software development, financial services, media and entertainment, and advertising and marketing. Let’s examine some of the different ways professionals in these industries apply generative AI to their field.

Health care and pharmaceuticals

Generative artificial intelligence has applications for all parts of the health care and pharmaceutical industry, from discovering and developing new life-saving medicine to personalizing treatment plans for individual patients to creating predictive images for charting disease progression. Some of the possibilities for generational AI in health care include:

  • Enhancing medical images: Generative AI can augment medical images like X-rays or MRIs, synthesize images, reconstruct images, or create reports about images. This technology can even generate new images to demonstrate how a disease may progress in time.

  • Discovering new drugs: Researchers can use generative artificial intelligence via a related field called generative design to research and develop new medicines. Gartner projects that 30 percent of the new drugs created by researchers in 2025 will use generative design principles [1].

  • Simplify tasks with patient notes and information: Healthcare professionals keep and take notes about patient medical care. Generational AI can build patient information summaries, create transcripts of verbally recorded notes, or find essential details in medical records more effectively than human efforts.

  • Personalized treatment: Generative AI can consider a large amount of patient information, including medical images and genetic testing, to deliver a customized treatment plan tailored to the patient's needs.

Advertising and marketing

Generative artificial intelligence offers many solutions to professionals working in advertising and marketing, such as generating text and images needed for marketing or finding new ways to interact with customers. Here are some examples of generative AI applications in advertising and marketing:

  • Generate marketing text and images: Generative AI can help marketing professionals create consistent, on-brand text and images to use in marketing campaigns. This technology also offers translation tools to spread your marketing message into new territories. Gartner predicts that marketing professionals will use generative AI to create 30 percent of outbound marketing materials by 2025 [1].

  • Generate personalized recommendations: Generative AI helps create powerful recommendation engines to help customers discover new products they might like. With generative AI, this process is more interactive for customers.

  • Create product descriptions: Beyond flashy advertising campaigns, generative artificial intelligence can help with tedious or time-consuming content requirements like creating product descriptions.

  • Enhance search engine optimization: SEO professionals can use generative AI for tasks like image tags or page titles or to create content drafts. You could also use a tool like ChatGPT or Bard to recommend changes you could make to content to improve SEO ranking.


In manufacturing, professionals can use generative AI to look for ways to improve efficiency, anticipate maintenance needs before they cause problems, help engineers create better designs faster, and create a more resilient supply chain. Let’s explore these potential manufacturing solutions:

  • Accelerating the design process: Using generative AI, engineers and project managers can work through the design process much faster by generating design ideas and asking the AI to assess ideas based on the constraints of the project.

  • Provide smart maintenance solutions for equipment: Maintenance professionals can use generative AI to track the performance of heavy equipment based on historical data, potentially alerting them to trouble before the machine malfunctions. Generative AI can also recommend routine maintenance schedules.

  • Improve supply chain: You could use generative AI to track down the cause of problems in the supply chain by speaking conversationally with the technology to sort through a vast amount of transactional or product data. Generative AI can also help generate delivery schedules or recommendations for suppliers.

Software development

For a software development team, generative AI can provide tools to create and optimize code faster and with less experience using programming languages. A few examples of the applications of generative AI in software development include:


  • Generating code: Software developers can create, optimize, and auto-complete code with generative AI. Generative AI can create code blocks by comparing them to a library of similar information. It can also predict the rest of the code a developer begins to type, much like how auto-complete works while texting on a smartphone.

  • Translate programming languages: Generative AI can be a tool for developers to interact with software without needing a programming language. The generative AI would act as a translator.

  • Automate testing: Developers can improve their automated testing processes using generative AI to highlight potential problems and execute testing sequences faster than other AI methods. Generative AI can learn the logic of the software and how users will interact with it and create test cases to demonstrate various user scenarios.

Financial services

According to McKinsey, generative AI could add $200 billion to $340 billion of value to the banking industry annually [2]. Some of the applications of generative AI in the financial services industry include artificial intelligence investment strategies, drafting documentation and monitoring regulatory changes, and using generative AI as an interpreter to facilitate communications between clients and investors.

  • Create investment strategies: Generative AI can recommend the best investments according to your or your client’s goals. This technology can find and execute trades much faster than human investors and can do so within the parameters you set for the kind of transaction you want.

  • Communicate and educate clients and investors: Financial services professionals sometimes need to communicate complex information to clients and colleagues. Generational AI can provide hyperpersonalized customer service without adding more customer service professionals.

  • Quickly draft documentation and monitor regulation: Generative AI can monitor regulatory activity, keep you informed of any changes, and create drafts of documents such as investment research or insurance policies.

Media and entertainment

Media and entertainment could embrace generative AI in several ways, considering the industry primarily engages in the same task as the tech: generating unique content. Generative AI can help create and edit visual content, create short highlight videos of sporting events, and make working with content management systems easier.

  • Create audio and visual content: Generative AI can create new video content from scratch. This tech can also help you make visual content faster by creating visual effects, adding graphics, or streamlining editing.

  • Generate highlights for sports and events: When it comes to sporting and live events, gen AI can create highlight reels instantly and allow fans to create their own custom highlights. For example, fans could generate highlights of a particular play or a tournament series.

  • Manage tags for better content management: Generative AI can tag and index extensive media libraries, making locating the files you need at any time easier. Similar to our manufacturing example above, generative AI allows using conversational language to find the information or media you’re looking for in a complex media library.

How to find solutions with generative AI

If you’re interested in bringing generative AI to your company, you can approach the technology in two ways. First, you can use existing models and learn to engineer prompts to your needs. Or, you can customize solutions to fit your business processes.

  • You can use existing generative AI tools like ChatGPT. In this scenario, you’ll focus on learning how to write prompts that get the best answer possible from the technology. For example, you might identify who your audience is and the appropriate tone of the piece to help the application deliver the correct results.

  • You can integrate custom solutions from an enterprise-level company or build your own generative AI tools. While it won’t be feasible or practical for many companies to create their own generative AI solutions, many gen AI companies offer solutions you can tailor to your business needs. Generative models will vary on features, cost, and security or privacy standards.

Learn more with Coursera.

If you’re ready to take the next step and find generative AI applications for your company, consider taking a microlearning course. Introduction to Generative AI offered by Google Cloud on Coursera is a one-hour introduction to generative AI for beginners interested in learning more.

Article sources


Gartner. “Gartner Experts Answer The Top Generative AI Questions For Your Enterprise, https://www.gartner.com/en/topics/generative-ai.” Accessed January 9, 2024.

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