Four generative AI use cases for businesses

As business leaders look to harness AI to meet business needs, generative AI has become an invaluable tool to gain a competitive edge. This breakthrough technology can comprehend and communicate in natural language, aiding the creation of personalized customer interactions and immersive virtual experiences while supplementing employee capabilities.

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

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

Virtual Assistants

Companies are turning to AI-powered tools like chatbots, copilots, or virtual assistants to improve productivity and customer experiences. These tools integrate generative AI with a company’s own data for precise responses, allowing the creation of customized virtual assistants that can handle interactive conversations.

Internally, these assistants complement and even empower employees by automating tasks and providing insights, which frees up time for more strategic work. Externally, they improve customer interactions by quickly understanding and responding to queries through simple conversational prompts.

For instance, a conversational AI software company, Kore.ai, trained its BankAssist solution for voice, web, mobile, SMS, and social media interactions. This solution enables customers to perform tasks like transferring funds and paying bills. The AI-powered voice assistant boosts performance with personalized suggestions, reducing customer handling time by 40%.

Intelligent Search

People rely on intelligent search every single day, thanks to LLMs trained on internet datasets. These models capture natural languages and the nuances of user queries. Enterprises have tons of proprietary data in private documents and platforms like Snowflake Data Cloud or Oracle Cloud ERP, crucial for business operations. But fully leveraging this data has been practically impossible—up until now.

Generative AI allows enterprises to start with a standard LLM, also called a foundation model, which is trained on publicly available data. This training ensures the model understands human languages and acquires a broad set of general knowledge. Once this model is tailored with company data, it can develop tailored applications that interpret business-specific terminology and provide relevant, up-to-date search results for employees and customers. Often, a second LLM is employed for checks and balances, to oversee the first, ensuring that the interactions stay within boundaries and avoid inappropriate content.

Content Summarization

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

Take healthcare, for instance. Medical experts can now use generative AI to streamline their review of patient notes to understand patient needs faster and enhance the quality of care. At NYU Langone Health, researchers are developing an LLM trained on a decade of patient records. This isn’t limited to summarizing; it’s 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, screening 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 like natural language processing (NLP) tools to understand, interpret, and manipulate human language just like we do. Using AI-powered processing tools, businesses can easily access and deploy data by translating, proofreading, automating content creation, extracting and analyzing data, and personalizing documents to individual or audience preferences.

This is particularly transformative in sectors where large volumes of documents are handled, such as the legal and financial sectors. The integration of generative AI streamlines document processing and enhances data currency and accuracy, fundamentally changing how businesses access, manage and utilize information.

Implementing generative AI to gain a competitive edge can significantly benefit business leaders. This game-changing technology generates new data from existing patterns, enhances productivity, and reduces costs. Key applications include virtual assistants for improved customer interactions, intelligent search for precise data insights, and content summarization for efficient information processing. By tailoring LLMs to their specific needs, businesses can revolutionize operations and drive strategic advancements.

Learn more about why you should adopt generative AI as an indispensable toolset for your organization, whether it’s making sense of mountainous data or keeping up with competition. The organizations embracing it now will be the ones setting industry standards and leading innovation in the future.