Revolutionising Business: Four Generative AI Use Cases in Asia

Generative AI is transforming businesses by boosting productivity and reducing costs. Key applications include virtual assistants, intelligent search, content summarization, and document processing. Companies like Kore.ai and NYU Langone Health are already leveraging generative AI for significant benefits.

Generative AI: The Future of Business Efficiency

Artificial Intelligence (AI) has become a game-changer for businesses worldwide, and Asia is no exception. Among the various AI technologies, generative AI stands out for its ability to comprehend and communicate in natural language, enhancing customer interactions and employee capabilities. This breakthrough technology is not just about generating new data from existing patterns; it's about fundamentally changing how businesses operate, boosting productivity, and reducing costs. For more insights into regional trends, explore APAC AI in 2026: 4 Trends You Need To Know.

Virtual Assistants: Enhancing Customer Interactions

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

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

For instance, Kore.ai, a conversational AI software company, 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%. This mirrors a broader trend of customer service AI agent growth.

Intelligent Search: Unlocking Proprietary Data

People rely on intelligent search every day, thanks to large language models (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 Summarisation: Streamlining Information Processing

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. A study by the National Institutes of Health provides further context on the application of AI in clinical settings here.

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: Transforming Data Management

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. This shift is part of a larger trend where AI is recalibrating the value of data.

Prompt: Creating a Personalized Virtual Assistant

Rationale: Creating a personalized virtual assistant can significantly enhance customer interactions and internal efficiency. Here’s a prompt to help you get started:

Prompt: "Design a virtual assistant that can handle customer queries related to banking services. The assistant should be able to understand and respond to questions about account balances, fund transfers, and bill payments. It should also provide personalized suggestions based on the customer's transaction history."

The Future of Generative AI in Asia

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.

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