Generative AI Use Cases and Applications

AI or Artificial Intelligence has come a long way in the last ten years. What started as problem-solving software is now the tech behind managing human-like work. We have seen multiple generative AI use cases in our daily lives like ChatGPT, Alexa, and many more. One of the wings, Generative AI, is gaining a lot of attention these days. In simple terms, generative AI specifically works on creating and ideating content that can be either a conversation, video, image, or story. This one is making a huge impact in sectors that deal with customer chains, business transitions, and more. Not to forget that it has also opened new career paths as companies hire generative AI engineers to seamlessly complete all the work related to it. Talking about the technical aspects, Generative AI uses machine learning principles to create content and is trained on datasets. The model is a self-learner and can recognize different patterns and structures without the need for human intervention.

How does Generative AI work?

Generative AI follows three simple steps – training, customizing, and creation. 

• In training, developers collect and dump enormous amounts of data from multiple sources, and then the AI model is supposed to learn. They learn by indulging in tasks like finding similar patterns, finding missing words in a sentence, and more. One of the most crucial things here is that an AI model needs hundreds of GPUs (even more than that) based on the amount of data it is dealing with.
• Then comes the customizing part, here the AI model is supposed to categorize different sets of data so that when a user sends a query, it doesn’t have to go through all the raw data time and again.
• The second step in tuning is Reinforcement Learning with Human Feedback (RLHF), where humans interact with the AI model and provide feedback on its output. This feedback helps AI models generate more accurate responses.

Moving forward in the article we will talk about the importance, use cases, challenges, and application of Generative AI followed by how Generative AI consulting services from A3Logics can be a game changer for you.

Importance of Generative AI

Generative AI is important for multiple businesses and it helps them in content creation, innovation, and grabbing customer attention. Here we have explained the importance of generative AI from a business point of view:

• Automation of generic coding

Yes, I can be used to write basic codes for the developers in your organization. Developers can use generative AI to write repetitive or common algorithm codes, allowing them to focus on reducing task timelines. Furthermore, the members of the team who are not from a technical brand will be able to use the low-code or no-code tools to create applications as well.

• Improved marketing campaigns

Generative AI in marketing can help you create content like texts, videos, images, and a lot more. Now, these content ideas can be used for posting on the official social media channels of a business. Generative AI models will undoubtedly assist team members in creating new concepts for social media and marketing campaigns.

• Gathering data and skyrocketing sales

Generative AI in sales helps in creating call summaries and shooting follow-up emails, thus making the work of the sales team easier. The executives will be able to automate most of the tasks and then focus on gathering more customers to increase the sales ratio. According to Statista, the current value of the generative AI market is $44.89 billion. Another report by Bloomberg Intelligence said the market could reach $1.3 trillion by the year 2032. Gartner also mentioned in research that involved around 821 businesses that the ones who use generative AI have achieved around 15.7 percent cost savings in a period of one to one and a half years. 

Top Use Cases of Generative AI Across Industries

Content Creation and Marketing

What’s better than working with a gen AI model that understands what you want and with little effort, can create content around your ideas? There are multiple Gen AI tools available in the global market that can be used to create content. These tools acquire knowledge from the existing data that is available on the internet. These tools can handle regular tasks like creating product descriptions and editing content, allowing creative team members to focus on new ideas.

Drug Discovery

The best part is that in the medical industry, generative AI use cases are not limited to healthcare only but it also expands to drug discovery. Generative AI algorithms can significantly speed up drug discovery by creating compound libraries and showcasing their properties.  Apart from that, it can also aid in generating new chemical structures that may have been missed by human researchers in the past. Moreover, generative AI models can be trained on large datasets related to specific diseases or drug-test targets. With this, the gen AI model can help researchers and doctors in picking the best candidates for drug tests.

Customer Service

Generative AI is a crucial part of customer service and we’ve seen many examples in the form of customer-facing chatbots. We all remember the times when the chatbots were so frustrating that they never understood our problems. However, with the intervention of generative AI, the same chatbots can provide you accurate answers for any and every query that you have regarding your orders, or anything on an application. 

Personalized responses play a major role in customer satisfaction and this further helps in building customer loyalty. In the current market, most of the companies that provide generative AI consulting services use ChatGPT for any solutions that are being created for customer service. 

Anomaly Detection

Anomaly detection is the process of identifying data that deviates from expected behavior. To understand it with an example, anomaly detection can help users identify fraudulent transactions and other fishy stuff.  Now, generative AI can help in generating new data points by identifying the distribution pattern of a dataset. Gen AI models and algorithms can generate realistic synthetic data that can prove beneficial for the anomaly detection processes. 

These Gen AI models can be trained on the normal data so they already know all its characteristics. After that, they could be asked to go through large amounts of data and find issues, if there are any. This will help companies in achieving improved accuracy, real-time problem detection, and more. Gen AI for anomaly detection is useful in various disciplines including finance, cybersecurity, healthcare, etc. 

Emerging Applications of Generative AI

• Healthcare

The use cases of generative AI in healthcare are countless. For example, it can be used for all the clinical documentation along with maintaining records. It can automate all the mundane tasks and make most of them error-free so neither the patient nor the doctor has to get confused with lots of paperwork and other stuff. At this point, hospitals and other medical facilities should collaborate with a company that can build custom generative AI apps to sort their patient management systems along with reducing the human intervention for the same. 

• Education

Generative AI is going to give the current educational scenario an overhaul without a doubt. It will be able to offer personalized learning schedules for different students as each one has a learning curve.  The new age generative AI applications will understand what a student is looking for by analyzing their learning patterns and choices, and then change the pace and procedure of content explanation accordingly. Moreover, the virtual tutors backed by gen AI will be able to give real-time support and feedback to the students.

• Finance

Generative AI applications, with their power to manage large datasets without breaking a sweat, will help the finance sector grow at an exponential pace. Financial institutions can create detailed reports and identify missed investment opportunities. Additionally, the inclusion of AI chatbots in banking applications for better customer service.

• Multi-modal generative AI

Well, we already have seen generative AI applications that can create content, write, read, speak, hear, and even see. In the future, the multi-modal aspect of generative AI models will cover more things so that it can deliver a human-like experience. We’ve seen various iterations, like text-to-speech and text-to-image, used across multiple sectors for different functions.

• Real estate

While you will get to see multiple emerging applications of generative AI, one of the main implementations of the same is in real estate. Gen AI applications can change the whole scene of real estate and how customers are dealt with and interacted with. For example, gen AI can be used to deal with all the documentation that goes on in real estate firms. Generative AI can handle leases, and tenant requests, communicate with staff, and monitor customer interactions to improve real estate experiences.

Gaming and Entertainment

Yes, Generative AI use cases include both gaming and entertainment. Developers can use generative AI to create interactive stories based on players’ choices and actions in the game. Gen AI doubled up with machine learning algorithms can easily generate storylines that offer an immersive experience to the users. Moreover, gen AI can also go through gameplay data and list down the potential issues that gamers could face while playing a game. 

It can also adjust the skill level, playstyle, and preferences based on the experience of the gamer. Hence, it will provide the players with a personalized experience. Generative AI can create 3D models, textures, animations, and stunning assets for game developers.

Challenges and Ethical Considerations in Generative AI

While applications of generative AI are increasing with each passing day in popular sectors like real estate, finance, entertainment, and gaming, we just cannot forget that every coin has two sides. One major threat posed by generative AI is the increasingly sophisticated output of deepfakes.

Generative AI can create life-like images and videos, potentially becoming a major source of misinformation and public chaos. And that’s not it, using generative AI for content creation could also make you fall into the copyright trap. If generative AI creates music identical to a copyrighted artist’s work, you could face legal trouble. Every generative AI development company is working on creating gen AI models that work without bias and go through regulations so that the content produced by them is not out of the line.

How A3Logics can help you leverage the power of Generative AI?

A software development company like A3Logics offers you Generative AI integration services with which your organization can reach new heights. The tools created by A3Logics will help you automate mundane tasks so that the employees can focus on other important tasks. 

Furthermore, they can also be used to generate content, fasten developmental aspects in the company, provide better code quality, etc. Other disciplines where the artificial intelligence services from A3Logics can help your business are data analysis, insights, quality assurances, designing, and prototyping, and a lot more. 

Conclusion

The generative AI market cap is going to increase along with the increasing use cases of generative AI all over the globe. While there are a few challenges at this point. Future developments in generative AI are expected to address biases and content plagiarism found in current models. The audience eagerly awaits the next advancement, known as Interactive AI.

Frequently Asked Questions (FAQ)

What are generative AI examples?

What are the future use cases of generative AI?

Some of the most important use cases of generative AI that we will see in the future are its use in drug discovery and development, personalized treatment plans for different diseases, use of the same in creating in-game elements, anomaly detection in cybersecurity and finance environments. 

What problems can generative AI solve?

Can generative AI replace humans?

This could be dubbed one of the biggest questions related to use cases of generative AI in general. No, generative AI can only handle repetitive tasks and recognize trained patterns. It can’t match human intelligence or express ideas the way humans do, especially in arts and entertainment.