50 Useful Generative AI Examples in 2024

Written by
Ema Lukan
Published on
May 17, 2024
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Generative AI has become a hot topic in the past few months, and for good reason — it is changing the world right before our eyes. 

The AI revolution is impacting every sector, including healthcare, education, finance, agriculture, and construction, with new AI solutions emerging daily. 

In this article, we will explore 50 practical applications of generative AI across different industries

To demonstrate the real impact of AI, we have also integrated real-world generative AI examples that are already leaving a profound imprint on people's work processes. 

Are you ready to dive right in? Let’s go!

But wait - what exactly is generative AI? 🤖

Generative AI refers to a form of artificial intelligence that prioritizes the creation of original data rather than solely processing and organizing pre-existing data. By utilizing large language models, it has the ability to generate diverse outputs, including unique written content, images, videos, and music.

Generative AI examples in healthcare

The world of healthcare certainly has its fair share of challenges, doesn't it?

We're talking about rising healthcare costs, a fragmented system, struggles with health information exchange and interoperability, and limited access to care, just to name a few.

However, AI presents an opportunity to address these challenges.

While it is not a magical solution, generative AI can be leveraged in various ways to make a meaningful impact. 

Here are some examples:

#1 Conversational AI apps for patients

👉 Example: Ada 

Ada is a doctor-developed symptom assessment app that offers medical guidance in multiple languages. Optimized with the expertise of human doctors, Ada utilizes AI to support improved health outcomes and deliver exceptional clinical excellence.

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Generative AI applications in healthcare span from conversational AI chatbots to medical education. In the image, you can see Ada, a conversational healthcare app designed for individuals.

#2 AI applications for early detection of certain diseases

👉 Example: SkinVision app 

SkinVision is an app for early detection of skin cancer. With its regulated medical service, AI technology, and expert input, it teaches users to self-examine, understand risks, and address immediate concerns.

#3 AI for accessibility

👉 Example: Virtual volunteer / Be My Eyes

It’s an AI app designed for visually impaired individuals that harnesses the power of GPT-4 to convert images into text instantly. Users can send images through the app for immediate identification, interpretation, and conversational visual assistance. 

#4 AI for patient interactions and support

👉 Example: Hyro

This conversational AI is designed specifically for health systems to enhance patient engagement and address staffing challenges. With HIPAA-compliant conversational AI, users can automate common interactions, scale operations, and overcome staffing shortages.

#5 AI for medical product development and design

👉 Example: Uizard 

Uizard leverages AI for quickly and easily prototyping various digital products, such as apps and landing pages. With its intuitive interface, it greatly simplifies the once manual design process.

#6 AI-generated media for enhanced medical training and simulation

👉 Example: PEDAL 

PEDAL is an AI-driven platform that helps with better decision making in oncology. With a biobank of 150,000 tumor samples across 137 cancer types, the platform predicts drug responses with unmatched precision.

Generative AI examples in education

So, there's a class of 20+ students sitting in a classroom. 

Some of them are visual learners, while others prefer reading. Some are introverted and freeze when put in the spotlight, and others need extra help with biology. It's quite a diverse group of people, and they have a diverse range of needs, don't you think?

There's no doubt that education today faces many challenges, including unequal access, outdated methods, and the need for personalized learning. Fortunately, with the advent of AI, the solutions seem closer each day. 

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AI video is an emerging form of media that holds great potential for educational purposes. With Synthesia, you can create videos with realistic AI avatars in 120+ languages by simply typing in text.

Here's how we can use generative AI in education:

#7 AI apps for personalized learning experiences

👉 Example: Knowji 

Knowji is an AI-driven app that enhances vocabulary acquisition for learners of all ages. With captivating content and a state-of-the-art spaced repetition algorithm, this tool ensures the long-lasting retention of words.

#8 AI apps for innovative learning approaches

👉 Example: Hello History

Hello History is an app that offers a unique approach to learning history. Users can engage in conversations with historical personalities, which makes the study of history much more engaging and interactive.

#9 AI generators for creating more engaging training materials

👉 Example: Synthesia 

Synthesia is an AI video generator that creates videos from text. And not just any videos, but videos with real human presenters - AI avatars. It’s a great online tool that helps educators effortlessly transform their text-based documents into an engaging video training featuring a human face, establishing a deeper connection with the viewers.

Here’s how it works:

Synthesia STUDIO product demo

#10 AI solutions for assessment, grading, and giving feedback to students

👉 Example: Gradescope 

Gradescope is an AI-powered tool that simplifies assessment grading for teachers. It efficiently grades both digital and paper-based assignments, providing quick and accurate results. Additionally, Gradescope offers valuable insights into students' knowledge levels across various subjects.

#11 AI summarization tools

👉 Example: Genei 

Genei leverages AI to accelerate research by automating time-consuming tasks. This app instantly summarizes PDFs and websites, saving students and researchers a significant amount of time. Additionally, Genei can provide concise and summarized responses to questions based on relevant resources.

#12 AI learning companions and personal tutors for individualized support

👉 Example: Duolingo Max 

Duolingo Max is a conversational AI for learning languages that leverages GPT-4. Learners can choose from two innovative features: Explain My Answer and Roleplay. These additions provide a deeper learning experience alongside the existing benefits of Duolingo. 

Generative AI examples in tourism and hospitality

How many hours did you spend planning your last trip? ✈️

Let me guess - quite a lot. 

While some people enjoy it, the majority find it to be a time-consuming and unenjoyable task.

Browsing through numerous pages, searching for locations, finding suitable restaurants, and dealing with car rentals, all while trying to organize a schedule around it, can be incredibly exhausting.

Fortunately, generative AI is poised to provide different solutions. 

While there are already some applications available, we anticipate a significant surge in development in the coming years

Here are some concrete use cases of generative AI in the tourism sector:

#13 AI apps for streamlining reservations and itineraries

👉 Example: Tripnotes.ai 

Tripnotes is a data-powered travel planner that simplifies, well… trip planning. Users can paste their travel inspiration from text messages, social media, or blogs, and the app automatically saves and researches each mentioned place leveraging generative AI.

#14 AI search

👉 Example: Microsoft Bing 

Microsoft Bing is an advanced search engine that incorporates cutting-edge AI technology. With its web, video, image, and map search functionalities, Bing offers a comprehensive search experience, and also includes real-time chat and co-creation features.

#15 AI business solutions for the travel industry

👉 Example: Bloomreach

Bloomreach is a cloud-based software for the travel industry that personalizes customer touch-points, drives business growth, and supports different providers. It helps identify frequent travelers, create personalized experiences, and gain valuable customer insights.

#16 AI for marketing

👉 Example: Runway 

Marketing tourist destinations and services requires a significant amount of multimedia content, with video being the most popular format at the moment. Fortunately, AI can assist with video editing. One example is Runway, which offers over 30 integrated AI tools to facilitate smooth and accessible video editing for everyone, regardless of their previous knowledge and video editing skills.

#17 AI chatbots for customer service and support

👉 Example: ChatBot  

ChatBot is an AI customer support tool that improves service by streamlining processes and offering support across various channels and languages. It leverages large language models to enhance the user experience with visual explanations and interactive forms.

#18 Virtual guides for personalized guided tours

👉 Example: P.A.D.D.Y 

P.A.D.D.Y. is an AI-powered tour guide created by a group of tour guides in Ireland. This multifaceted AI brings character to the experience of Ireland, tailoring it to individual interests and preferences.

Generative AI examples in marketing and advertising

From the Mad Men era to the age of the internet, social media, and hyperconnectedness, marketing has undergone a remarkable transformation. 

Traditional methods have been replaced by digital strategies, personalized messaging, and interactive experiences that businesses must navigate in order to connect and resonate with their target audiences.

The constantly evolving landscape demands an abundance of localized, niche, and relatable content – and this is where generative AI can play a crucial role:

#19 AI for content creation (text, images, video, audio…)

👉 Example: AI video generators 

Generative AI enables innovative methods of content creation. One such example is AI video generation. What used to be a physical process (cameras, actors, studios…) has now transitioned into a fully digital realm, making video creation convenient and accessible to all.

#20 AI for content repurposing

👉 Example: Jasper Campaigns   

Omnichannel marketing is at the core of today's marketing. This feature by Jasper enables users to create end-to-end marketing campaigns in their brand's tone and voice with a single brief. Based on the brief, the AI can generate as many assets as needed, including emails, case studies, Facebook and Google ads, press releases, and more.

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One generative AI example that can be used in marketing is Jasper Campaigns. With just a single brief, this AI can generate content tailored for various communication channels.

#21 AI for personalized marketing strategies

👉 Example: RAD AI 

RAD AI merges data-driven insights and authentic content to assist marketing teams in crafting impactful campaigns. By analyzing past performance and formulating effective strategies, it aims to establish genuine and emotional connections with the target audience across various marketing channels.

#22 Generative AI for content localization 

👉 Example: Lokalise AI  

Lokalise AI is an automated localization and translation platform designed for various applications, including web apps, customer service, documents, mobile apps, games, and marketing assets. With its advanced features like contextual translation, alternative variants, rephrasing, and concise adaptations, it enables seamless communication with global audiences in different languages.

Generative AI examples in finance and business

AI is also transforming the finance and banking sectors, making them more user-friendly than ever before. 

AI is providing a significant upgrade to banking operations by automating tasks that were previously performed manually, resulting in more efficient processes.

With the help of generative AI, we are witnessing exciting communication possibilities, including new and improved ways to present information, highly useful real-time AI assistants, and streamlined content optimization processes.

#23 AI solutions for business owners

👉 Example: Yooz 

Yooz is an automated AI solution designed to assist accounting and finance leaders in managing invoices. The solution aims to streamline and automate the invoice processing workflow, reducing manual effort and enhancing overall efficiency.

#24 AI for content optimization

👉 Example: AdCreative.ai 

AdCreative.ai is a generative AI app that quickly generates conversion-focused ad creatives and social media posts. With the ability to specify the target audience and platform, it selects the ideal message aligned with specific business goals.

#25 AI for personal finance

👉 Example: Cleo

Cleo, an AI money app designed for individuals, evolutionizes how people manage their financial lives. With a simple chat interface, Cleo assists users in saving money, budgeting effectively, and gaining financial knowledge.

#26 AI chatbots and virtual assistants for enhanced customer service

👉 Example: Boost.ai 

Boost.ai is an AI-powered conversation builder that delivers accurate responses to customers using advanced natural language processing and your customized training inputs. It seamlessly operates across various platforms, including websites, Slack channels, Zendesk, and Teams.

#27 AI-generated presentations

👉 Example: Tome 

Tome is a revolutionary generative AI solution that takes the hassle out of creating presentations. By providing a simple prompt, users can instantly generate captivating slides for product presentations, sales pitches, training sessions, client proposals, and more.

Generative AI examples in media and entertainment

In the dynamic landscape of media and entertainment, a clear trend is unfolding: a continuous evolution towards more immersive and interactive content. 

As our attention spans diminish, innovative content formats are surfacing to captivate audiences, such as concise tweets, engaging TikToks, and creative reels.

Generative AI is playing a transformative role in the production processes, democratizing creativity and empowering individuals to generate a wide range of content, including images, videos, articles, and music. ✍ 📹 🎶

Let's delve into some tangible examples of how generative AI is reshaping the media landscape:

#28 AI-based content personalization

👉 Example: BuzzFeed’s Infinity Quizzes 

One example of how media outlets can utilize generative AI for their content is BuzzFeed. In February 2023, they launched their first "Infinity Quizzes," which create personalized quizzes for users based on a few inputs.

#29 AI solutions for more immersive user experiences

👉 Example: My AI on Snapchat

Snapchat has recently introduced My AI, an AI chatbot that can answer users' questions and engage in conversations. Whether it's answering trivia questions, offering gift advice, providing trip planning assistance, or suggesting dinner options, My AI offers a personalized experience driven by AI.

#30 AI apps for scalable content creation

👉 Example: Canva

Canva is a design platform that offers AI-powered solutions for content creation. Through its AI capabilities, Canva streamlines the process of creating visual content by providing features for resizing, image and video editing, generating AI avatars, and converting text to images.

#31 AI for ideating different solutions, formats, concepts… 

👉 Example: Sudowrite

Sudowrite is an interactive AI writing assistant that offers valuable features like rewriting paragraphs in various styles, creative brainstorming, and character generation. Developed by writers, it provides an enjoyable user experience and produces remarkably human-like stories.

#32 AI-generated art

👉 Example: Midjourney

Midjourney is a cutting-edge image generator that transforms text descriptions into captivating images. With its advanced capabilities in generating intricate compositions, realistic edits, and incorporating diverse details, it is pushing the boundaries of visual art creation.

Want to know more about how generative AI is going to transform the media industry?

Check out this article: 

Generative AI examples in retail

Generative AI is redefining the way we shop and interact with brands, bringing convenience and efficiency to consumers while empowering retailers to deliver targeted marketing campaigns, optimize pricing strategies, and gain valuable insights into consumer behavior.

The possibilities that generative AI offers in the retail sector are unprecedented, and here are some of the notable examples:

#33 AI-generated product images

👉 Example: Lalaland

Lalaland transforms product creation for the fashion industry by eliminating the need for physical samples. Users can effortlessly select a model/avatar, apply their design, and generate the final image. The app provides diverse plans with options for various body sizes, hairstyles, body shapes, custom poses, and more.

#34 AI-generated mockups

👉 Example: Dall-E 

Dall-E is an AI image generator that creates images based on text descriptions. This means that a process that previously required a physical product can now be replaced by generative AI. It can generate hyper realistic images and mockups that are literally impossible to distinguish from actual photographs.

#35 AI-generated product descriptions

👉 Example: Copy.ai 

Catering to the diverse needs of marketers, this AI text generator proves to be a valuable asset for crafting various types of product descriptions. Whether it's for emails, product pages, Instagram, or ads, it covers a wide range of writing requirements.

#36 AI-powered customer service chatbots 

👉 Example: Conversica 

Conversica is an AI-powered solution that automates customer follow-ups and drives meaningful engagements. It seamlessly integrates with multiple tools commonly used in retail, such as Hubspot, Marketo and Salesforce.

#37 AI-supported search results for enhanced shopping experiences

👉 Example: Bard 

Bard, a conversational AI chatbot created by Google, is changing the shopping experience thanks to its interactive user interface. Available in three languages and accessible in over 180 countries and territories, Bard engages in natural conversations and fetches information from the web to assist users in making informed purchasing decisions.

Generative AI examples in manufacturing

Gone are the days of traditional manufacturing as we knew it. Today, the manufacturing industry is a vibrant and rapidly evolving landscape, where technological advancements and streamlined processes are revolutionizing production. 

One such advancement is generative AI, which brings forth multiple benefits. Here's how it can be used:

#38 AI-driven product development and design 

👉 Example: Midjourney 

Midjourney is an AI image generator that can create realistic images based on detailed text inputs. Manufacturers can utilize it to generate prototypes, quick mockups, and visualizations without the necessity of physical samples.

#39 AI apps for enhanced training and simulation

👉 Example: 3D simulation by Protostar.ai 

This AI app leverages extensive data collected from diverse sensors and sources to construct a digital replica of a facility or factory. By utilizing real-world information, it can create simulations that provide predictive insights into product performance and process outcomes.  

#40 AI for customer interactions and support 

👉 Example: Tidio 

Tidio is a customer support AI software that empowers small and medium-sized organizations with real-time chat, personalized recommendations, and task automation. It’s easy to set up and their basic plan is free to use.

#41 AI solutions for finding answers to complex issues

👉 Example: Wizdom.ai

Wizdom is an AI solution that analyzes vast amounts of data from the global research ecosystem to offer valuable insights for decision-making. With its comprehensive approach, it empowers users to make informed decisions and stay at the forefront of advancements in their field.

#42 AI apps for streamlined communications

👉 Example: Hyperwrite 

HyperWrite is a user-friendly online platform and Chrome extension that assists with copywriting, enabling users to refine their writing and enhance productivity. It can write different types of text, from emails to social media posts to long articles.

Generative AI examples in construction and real estate sector

The construction and real estate sector has experienced a substantial transformation in recent years. 

Through the integration of advanced technologies such as modeling, drones, and prefabrication methods, the industry has transitioned from traditional manual processes to a more efficient and digitally-driven approach. This shift has facilitated enhanced project management, cost control, and accelerated construction timelines.

However, the transformation does not end there - generative AI is another technology poised to make a tremendous impact in this field.

#43 AI for rendering

👉 Example: Vizcom 

It enables designers and architects to swiftly create and render designs with a multitude of options, including color, material, finish, and part-specific modifications. The result is faster and more versatile design iterations than ever before and thus better user experience for clients.

#44 AI chatbots

👉 Example: ChatGPT

ChatGPT is a state-of-the-art AI chatbot that utilizes natural language processing to generate human-like conversations. Users can participate in interactive dialogues, asking questions, seeking additional information, or even requesting alternative responses. Although ChatGPT's knowledge is based on data available until 2021, its exceptional accuracy is truly remarkable.

#45 AI design solutions

👉 Example: Maket.ai  

Maket is an AI tool that empowers architects, designers, builders, contractors, and developers in the residential industry. Its core feature is automated floorplan generation. Additionally, Maket assists users in navigating zoning codes and offers a wide range of styles to explore.

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Generative AI has numerous applications in construction and real estate. One example is Maket.ai, which helps architects and designers generate various visual styles and floor plans. 

#46 AI-powered communication and marketing solutions for the industry

👉 Example: NeuralText 

NeuralText is a versatile generative AI app equipped with three powerful features: Paragraph Generator, Content Outline, and Product Description. It also goes beyond content creation by assisting with SEO optimization.

Generative AI examples in agriculture

Despite the revolution in the agricultural industry, it continues to face challenges such as climate change, resource scarcity, market volatility, and labor shortages, to name just a few.

However, by harnessing advanced technologies, including the integration of generative AI, farmers can overcome these hurdles and achieve optimized crop production, efficient resource management, and sustainable practices.

#47 AI for agricultural education

👉 Example: Farmer.chat  

Farmer.CHAT is an AI-based farmer advisory service that connects governments and farmers for real-time communication. It provides data-driven insights and decision-making tools to optimize crop management, reduce waste, and increase yields. With a combination of documents, videos, and vetted data sources, Farmer.CHAT delivers actionable recommendations to farmers in India, Ethiopia, and Kenya.

#48 AI for marketing and content generation

👉 Example: AdCreative.ai  

This generative AI app can be used to create compelling ad creatives as well as organic social media posts. It’s very easy to use - based on target audience and platform preferences, the AI algorithm generates visuals and text in minutes.

#49 AI for streamlining business operations

👉 Example: Zia 

Zia is an AI-powered virtual assistant that provides a comprehensive suite of business support services. Zia helps users with many business-related tasks, including data gathering, insightful analytics, email translation, and proficient writing assistance.

#50 AI for decision support in farming

👉 Example: Semantic Scholar 

Semantic Scholar is an invaluable resource for researchers seeking expedited access to emerging scientific knowledge. With a comprehensive index of over 2 million academic research papers, this AI-powered application swiftly extracts key insights, enabling users to stay abreast of the latest trends in their respective fields.

Conclusion

In conclusion, it is evident that the generative AI landscape is flourishing with a wide range of tools catering to diverse industries. 

With new tools emerging daily, we will continue to monitor and expand our list to stay up-to-date in this dynamic realm of AI.

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