Generative AI Applications and Use Cases for Business in 2023

Once trained, the model can produce new images from the dataset by taking samples from the hidden space and mapping them back to the original space. Generative AI commonly works by training a deep learning model on a dataset of pictures, which is then applied to create new images. It utilizes several Generative AI models like BERT and Transformer or Autoregressive models. However, Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) are two of the most prominent generative AI model types. Generative AI models can help with the labor-intensive
tasks of data classification, tagging, anonymization, segmentation, and
enrichment. Moreover, auxiliary products for data cataloging and management can
help improve data lineage and accessibility.

Partner with Mission Cloud to learn how to reach your AI goals while reducing risk and maximizing ROI. This is just one of countless examples, with new applications for IDP with genAI emerging constantly. High-potential industries like mortgage processing, insurance claims handling, loan applications and legal agreements stand to gain immensely. IDP, widely used across industries, revolutionizes tasks like sorting, processing and analyzing medical forms.

Ensure responsible, transparent, and explainable knowledge management systems

Instead of having disparate AI solutions, watsonx offers an approach that is open, based on foundation models that are multi-model on multi-cloud and targeted for a range of business use cases. The importance of Generative AI in the healthcare industry cannot be overemphasized. Generative AI can assist radiologists in detecting cancer, heart diseases, and neurological disorders by analyzing medical images, such as X-rays, CT scans, and MRIs. This way, diagnoses can be made more accurately and are less likely to be missed or delayed. The advent of Artificial Intelligence (AI) has significantly impacted the way businesses operate and manage daily workflows. The emergence of diverse AI applications and tools has enabled businesses to make wiser decisions and automate repetitive tasks, making operations more efficient and effective.

This can be especially useful for catching dangerous diseases like cancer in their early stages. And by 2027, a whopping 30% of manufacturers will be using it to improve their product development process. By 2025, generative AI is expected to generate 10% of all data (currently, less than 1%) and 20% of all test data for consumer-facing applications. In a recent Gartner webinar poll of more than 2,500 executives, 38% indicated that customer experience and retention is the primary purpose of their generative AI investments. This was followed by revenue growth (26%), cost optimization (17%) and business continuity (7%). Gartner sees generative AI becoming a general-purpose technology with an impact similar to that of the steam engine, electricity and the internet.

Practical Use Cases of Generative AI for Business Today

Further, about 32% mitigate the accuracy of these generative AI tools, and we all know how big a deal that can be with generative AI having a mind of its own and even perhaps getting dumber as some reports say. In short, the potential uses for generative AI are varied and diverse, limited only by the human imagination needed to conceptualize them. Arguably the hottest topic in computer science right now, generative AI has been hailed as the solution to repetitive work, a ubiquitous AI assistant, a new way to approach design, and much more. Business leaders everywhere are wondering how to take advantage of this exciting technology and situate themselves ahead of what appears to be a bloom of innovation. 3 min read – The process of introducing new features to the US Open digital experience has never been smoother than it was this year, thanks to watsonx. 3 min read – Identify specific problems that AI can help solve so you can begin to realize its limits, challenges, and undeniable advantages.

These connections can be adjusted (tuned) to help the neural network perform a specific task. Generative AI can help with client segmentation, predicting the response of a target group to advertisements and Yakov Livshits marketing campaigns. This can be a valuable tool for companies targeting specific audiences and increasing sales. ChatGPT and other tools like it are trained on large amounts of publicly available data.

Step 3. Prepare the data

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

Preventing students from using it is likely to become even more challenging – and might even hinder their development. Some teaching staff have recently been trialing the effectiveness of generative AI as a feedback tool. The tool assesses student assignments or submissions, and provides useful feedback on a range of criteria, including punctuation, spelling, grammar, sentence and paragraph structure, tone, and more. It is extremely time-consuming to comb through all learning materials on a regular basis to ensure there are no inaccuracies or out-of-date information.

Generative AI can create new product designs based on the analysis of current market trends, consumer preferences, and historic sales data. The AI model can generate multiple variations, allowing companies to shortlist the most appealing options. These can be useful for mitigating the data imbalance issue for the sentiment analysis of users’ opinions (as in the figure below) in many contexts such as education, customer services, etc. The TTS generation has multiple business applications such as education, marketing, podcasting, advertisement, etc. For example, an educator can convert their lecture notes into audio materials to make them more attractive, and the same method can also be helpful to create educational materials for visually impaired people.

Updating learning materials

Generative AI is reshaping the world of language processing, enabling accurate translations and natural interactions that transcend traditional communication boundaries. As a result, manufacturers can deliver high-quality products with improved safety and reliability. This automation enhances efficiency and productivity across industries, allowing professionals to focus on higher-value tasks. According to Team Whistle’s EVP of content Noah Weissman, the company makes 30 to 50 TikTok videos a day, and generative AI helps the company determine which keywords would make the videos most successful.

Cem’s work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School. When a customer sends a message, ChatGPT or other similar tools can use this profile to provide relevant responses tailored to the customer’s specific needs and preferences.

#7 AI apps for personalized learning experiences

For example, a generative AI system could be used to generate social media posts that are intentionally positive or negative in order to influence public opinion or shape the sentiment of a particular conversation. In this article, we have gathered the top 100+ generative AI applications that can be used in general or for industry-specific purposes. We focused on real-world applications with examples but given how novel this technology is, some of these are potential use cases. For other applications of AI for requests where there is a single correct answer (e.g. prediction or classification), read our list of AI applications. For example, most users aren’t familiar with how the models are trained or what data goes into their training. BioNeMo is currently only available through limited early access, so it’s unclear who current customers are and how they are using the service.

• Generative AI-based tools can generate new music by learning the patterns and styles of input music and creating fresh compositions for advertisements or other purposes in the creative field.
• These tools can help control which data is consumed by GenAI models
  and prevent accidental disclosures.
• Further complicating matters, the uses of data have become more varied, and companies are faced with managing complex or poor-quality data.
• By analyzing the previous database the AI model can provide the voice for the content the user provides.
• AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
• These models can learn from existing designs and generate new ones, speeding up the design process.

They are not designed to be compliant with General Data Protection Regulation (GDPR) and other copyright laws, so it’s imperative to pay close attention to your enterprises’ uses of the platforms. Generative AI can be used to generate contracts based on pre-defined templates and criteria. This can save time and effort for procurement departments and help to ensure consistency and accuracy in contract Yakov Livshits language. The video below is generated by AI and shows its visual potentials to be used for marketing purposes. Tools like ChatGPT can create personalized email templates for individual customers with given customer information. When the company wants to send an email to a customer, ChatGPT can use a template to generate an email that is tailored to the customer’s individual preferences and needs.