20 Examples of Generative AI Applications Across Industries

Key takeaways

Generative artificial intelligence (GenAI) creates unique results in response to user prompts, with various applications across industries.

• McKinsey predicts that generative AI could add up to $4.4 trillion in value to the global economy each year [1].

• Generative artificial intelligence has applications across diverse industries, including health care, manufacturing, software development, financial services, media and entertainment, and advertising and marketing.

• To bring generative AI to your company, you can use existing models and learn to engineer prompts according to your needs, or you can customize solutions to fit your business processes.

Explore 20 examples of generative AI applications in various industries and learn how to start using generative AI for your organization. If you’re ready to learn more about or prepare for a career in generative AI, consider the Generative AI Fundamentals Specialization from IBM. In just one month, you can build an understanding of the fundamental concepts, capabilities, models, tools, applications, and platforms of generative AI foundation models. Upon completion, you’ll earn a shareable certificate to display on your resume or LinkedIn profile.

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. McKinsey concluded that the technology could add up to $4.4 trillion worth of value to the global economy annually [1].

Examples of generative AI

Examples of generative artificial intelligence that you may have heard of include Google’s Gemini, 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 Gemini: Google’s generative AI with integrations to Google products like Google Lens and Gmail, initially 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

20 examples of generative AI applications

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.

1. Health care and pharmaceuticals

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

• Enhance 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.

• Discover new drugs: Researchers can use generative artificial intelligence via a related field called generative design to research and develop new medicines.

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

• Personalize 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.

What are the primary applications of generative AI in health care?

Health care professionals use generative AI for a variety of tasks, depending on their resources and patient needs, meaning you won’t find one primary application. However, generative AI is often used for data generation, such as text and image generation, which leads to its popular use in creating synthetic data, educating patients, discovering drugs, and helping with clinical documentation.

2. 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.

• 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, page titles, or to create content drafts. You could also use a tool like ChatGPT or Gemini to recommend changes you could make to content to improve SEO ranking.

3. Manufacturing

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:

• Accelerate 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.

4. 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:

• Generate 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.

5. Financial services

According to PwC, banks that adopt AI could see an increase of up to 15 percentage points in their efficiency ratio [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. Generative 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.

6. 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.

What is one thing current generative AI applications cannot do​?

While generative AI can assist with a variety of tasks, these algorithms don’t have true human intelligence, meaning they struggle with tackling ethical dilemmas or making more strategic decisions for broader, less-defined challenges. The best uses of generative AI typically have a refined scope and clear directions, while human oversight is still needed for more nuanced decision-making.

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 according 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 generative AI companies offer solutions you can tailor to your business needs. Generative models will vary on features, cost, and security or privacy standards.

Read more: Generative AI Impact on Business

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