Four generative AI use cases for enterprises

As business leaders look to leverage AI to meet their business needs, generative AI has become an essential tool to gain a competitive advantage. This groundbreaking technology can understand and communicate in natural language, supporting the creation of personalized customer interactions and immersive virtual experiences while complementing employee skills.

What sets generative AI apart from traditional AI is not just the ability to generate new data from existing patterns. With generative AI, companies can now increase productivity and reduce costs, fundamentally changing the way they work.

Here’s how four use cases of generative AI are changing the business landscape:

Virtual Assistants

Companies are increasingly turning to AI-powered tools such as chatbots, copilots or virtual assistants to improve productivity and customer experience. These tools integrate generative AI with a company’s own data to provide precise answers. This makes it possible to create customized virtual assistants that can conduct interactive conversations.

Internally, these assistants complement and support employees by automating tasks and providing insights, freeing up time for more strategic tasks. Externally, they improve customer interactions by quickly understanding and answering queries through simple conversational prompts.

For example, Kore.ai, a conversational AI software company, has trained its BankAssist solution to interact via voice, web, mobile, SMS, and social media. This solution enables customers to complete tasks such as transferring money and paying bills. The AI-powered voice assistant boosts performance with personalized suggestions and reduces processing time for customers by 40%.

Intelligent search

People rely on intelligent search every day thanks to LLMs trained on Internet datasets. These models capture natural language and the nuances of user queries. Companies have reams of proprietary data in private documents and platforms like Snowflake Data Cloud or Oracle Cloud ERP that are critical to business operations. But until now, it has been virtually impossible to take full advantage of this data.

Generative AI allows companies to start with a standard LLM, also called a base model, that is trained using publicly available data. This training ensures that the model understands human languages ​​and learns a wide range of general knowledge. Once this model is customized with company data, it can develop customized applications that interpret business-specific terminology and provide relevant, up-to-date search results for employees and customers. Often, a second LLM is used for checks and balances to monitor the first and ensure that interactions stay within boundaries and inappropriate content is avoided.

Contents summary

Translating documents and meeting minutes into simple action points has traditionally been a manual and time-consuming process. But with generative AI models, companies can summarize documents, recordings, and videos within seconds.

Take healthcare, for example. Medical experts can now use generative AI to streamline patient record review, understand patient needs faster, and improve the quality of care. At NYU Langone Health, researchers are developing an LLM trained on a decade’s worth of patient records. It’s not just about summarizing; it’s also about predicting a patient’s risk of readmission within 30 days and other health outcomes.

In the financial sector, AI models are like high-speed analysts, sifting through thousands of data points in real time. This means sharper investment strategies and potentially better returns for investors and portfolio managers.

Document processing

Generative AI uses machine learning models such as natural language processing (NLP) tools to understand, interpret, and manipulate human language just like we do. AI-powered processing tools enable businesses to easily access and deliver data by translating, proofreading, automating content creation, extracting and analyzing data, and customizing documents to the preferences of individuals or audiences.

This is especially critical in industries that process large volumes of documents, such as legal and financial sectors. Integrating generative AI streamlines document processing and improves data timeliness and accuracy, fundamentally changing the way companies access, manage and use information.

Implementing generative AI to gain a competitive advantage can bring significant benefits to business leaders. This groundbreaking technology generates new data from existing patterns, increasing productivity and reducing costs. Key applications include virtual assistants for improved customer interactions, intelligent search for precise data insights, and content summarization for efficient information processing. By customizing LLMs to their specific needs, companies can revolutionize their operations and achieve strategic progress.

Learn more about why you should adopt generative AI as an essential tool for your business, whether it’s making sense of massive amounts of data or keeping up with the competition. The companies that adopt it now will set industry standards and drive innovation in the future.