20 examples of generative AI applications across industries

Important points

Generative artificial intelligence (GenAI) creates unique results in response to user prompts in a variety of applications across industries.

• Generative artificial intelligence has applications across a variety of industries, including healthcare, manufacturing, software development, financial services, media and entertainment, and advertising and marketing.

• To bring generative AI to your company, you can use an existing model and learn how to design prompts according to your needs, or you can customize the solution to fit your business processes.

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What is generative AI?

Generative AI is artificial intelligence designed to create unique text or image results in response to user prompts. This technology uses machine learning to return output based on user prompts. AI engineers use large datasets to train their technology. The model references that dataset when determining the best answer to a prompt. Another way to look at generative AI is as a type of predictive artificial intelligence. Based on the information you provide, the generative AI predicts which words and in what order will provide the best answer to your prompt.

Generative AI can be used to create new written, visual, and audio content, summarize complex data, generate code, assist with repetitive tasks, or make customer service more personalized. McKinsey concluded that this technology could add up to $4.4 trillion worth of value to the global economy annually. [1].

Example of generative AI

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

• Chat GPT or DALL-E: Generative artificial intelligence created by OpenAI. OpenAI is a Microsoft-backed, limited-profits company with a mission to develop artificial intelligence to benefit humanity.

• Google Gemini: Google’s generative AI integrated with Google products like Google Lens and Gmail. Initially, it will be powered by a language model called PaLM-2, trained on the largest dataset of all generative AI models available at the time of release.

20 examples of generative AI applications

Generative artificial intelligence has applications in a variety of industries, including healthcare, manufacturing, software development, financial services, media and entertainment, and advertising and marketing. Let’s take a look at some of the different ways these industry professionals are applying generated AI to their fields.

1. Healthcare and Pharmaceuticals

Generative artificial intelligence can be applied to every part of the healthcare and pharmaceutical industry, from discovering and developing new life-saving drugs, to customizing treatment plans for individual patients, to creating predictive images to chart disease progression. The possibilities for generative AI in healthcare include:

• Enhance your medical images: Generative AI can enhance medical images such as X-rays and MRIs, synthesize images, reconstruct images, and create reports about images. The technology can also generate new images that show how the disease progresses over time.

• Simplify tasks with patient notes and information. Healthcare professionals record and record patients’ medical care. Generative AI can build summaries of patient information, create transcripts of verbal notes, and find important details in medical records more efficiently than human efforts.

• Personalize your treatment: Generative AI can take into account large amounts of patient information, such as medical images and genetic testing, to provide treatment plans customized to the patient’s needs.

What are the main uses of generative AI in healthcare?

Healthcare professionals are using generative AI for a variety of tasks, depending on resources and patient needs. This means you won’t find just one primary use. However, generative AI is often used for data generation, such as generating text or images, and is widely used in creating synthetic data, patient education, drug discovery, and assisting with clinical documentation.

2. Advertising and Marketing

Generative artificial intelligence offers many solutions for advertising and marketing professionals, such as generating the text and images needed for marketing and 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 helps marketing professionals create consistent, on-brand text and images for use in marketing campaigns. The technology also provides translation tools to spread marketing messages into new territories.

• Generate personalized recommendations. Generative AI helps create powerful recommendation engines that can discover new products that your customers might like. Generative AI makes this process more interactive for customers.

• Enhance search engine optimization. SEO professionals can use generative AI for tasks like image tags and page titles, as well as draft content. You can also use tools like ChatGPT and Gemini to recommend changes you can make to your content to improve your SEO rankings.

3. Manufacturing

In manufacturing, experts can use generative AI to explore ways to improve efficiency, predict maintenance needs before problems occur, help engineers create better designs faster, and build more resilient supply chains. Let’s explore these potential manufacturing solutions.

• Accelerate your design process. Generative AI allows engineers and project managers to move through the design process faster by generating design ideas and asking AI to evaluate them based on project constraints.

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

• Supply chain improvement: Generative AI can be used to talk to technology that sorts through vast amounts of transactional and product data to trace the source of supply chain problems. Generative AI can also help generate delivery schedules and recommendations to suppliers.

4. Software development

For software development teams, generative AI can provide tools to write and optimize code more quickly, even with less experience using programming languages. Examples of applications of generative AI in software development include:

• Generate code: Software developers can use generative AI to write, optimize, and autocomplete code. Generative AI can create blocks of code by comparing them to libraries of similar information. It can also predict the rest of the code the developer will start typing, similar to how autocomplete works when sending a text message on a smartphone.

• Automate your tests: Developers can use generative AI to improve automated testing processes, highlight potential issues, and run test sequences faster than other AI techniques. Generative AI can learn the logic of the software and how users interact with it, and create test cases to demonstrate different user scenarios.

5. Financial services

According to PwC, banks that implement AI can increase efficiency by up to 15 percentage points [2]. Applications of generative AI in the financial services industry include artificial intelligence investment strategies, document creation and monitoring of regulatory changes, and the use of generative AI as an interpreter to facilitate communication between customers and investors.

• Quickly draft documents and monitor regulations. Generative AI can monitor regulatory activities, keep you informed of changes, and draft documents such as investment research and insurance policies.

6. Media and Entertainment

Media and entertainment could adopt generative AI in several ways, given that the industry is primarily working on the same task as technology: generating unique content. Generative AI can help create and edit visual content, create short highlight videos of sporting events, and facilitate the operation of content management systems.

• Create audio and visual content. Generative AI can create new video content from scratch. This technology also helps you quickly create visual content by creating visual effects, adding graphics, or streamlining editing.

• Generate highlights of sports and events. When it comes to sports and live events, Gen AI instantly creates highlight reels and allows fans to create their own custom highlights. For example, fans can create highlights of specific plays or tournament series.

• Manage tags to improve content management. Generative AI can tag and index your extensive media library, so you can easily find the files you need at any time. Similar to the manufacturing example above, generative AI allows you to use conversational language to find the information or media you are looking for in a complex media library.

How to find solutions with generative AI

If you’re interested in implementing generative AI in your company, you can approach the technology in two ways. First, you can use an existing model to learn how to design prompts according to your needs. Or, you can customize the solution to fit your business processes.

• You can use existing generative AI tools such as ChatGPT. In this scenario, we’ll focus on learning how to create prompts that get the best possible answers from technology. For example, you can identify who your audience is and the appropriate tone for your work so that your application provides the correct results.

• Integrate custom solutions for enterprise-level companies or build your own generative AI tools. While creating your own generative AI solution is not feasible or practical for many businesses, many generative AI companies offer solutions that can be customized to fit your business needs. Generative models vary in functionality, cost, and security or privacy criteria.

read more: How generative AI impacts your business

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