Skip to content
Tiatra, LLCTiatra, LLC
Tiatra, LLC
Information Technology Solutions for Washington, DC Government Agencies
  • Home
  • About Us
  • Services
    • IT Engineering and Support
    • Software Development
    • Information Assurance and Testing
    • Project and Program Management
  • Clients & Partners
  • Careers
  • News
  • Contact
 
  • Home
  • About Us
  • Services
    • IT Engineering and Support
    • Software Development
    • Information Assurance and Testing
    • Project and Program Management
  • Clients & Partners
  • Careers
  • News
  • Contact

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.


Read More from This Article: Four generative AI use cases for businesses
Source: News

Category: NewsAugust 9, 2024
Tags: art

Post navigation

PreviousPrevious post:Five generative AI tips for every business leaderNextNext post:The role of accelerated computing in reducing energy consumption

Related posts

Barb Wixom and MIT CISR on managing data like a product
May 30, 2025
Avery Dennison takes culture-first approach to AI transformation
May 30, 2025
The agentic AI assist Stanford University cancer care staff needed
May 30, 2025
Los desafíos de la era de la ‘IA en todas partes’, a fondo en Data & AI Summit 2025
May 30, 2025
“AI 비서가 팀 단위로 지원하는 효과”···퍼플렉시티, AI 프로젝트 10분 완성 도구 ‘랩스’ 출시
May 30, 2025
“ROI는 어디에?” AI 도입을 재고하게 만드는 실패 사례
May 30, 2025
Recent Posts
  • Barb Wixom and MIT CISR on managing data like a product
  • Avery Dennison takes culture-first approach to AI transformation
  • The agentic AI assist Stanford University cancer care staff needed
  • Los desafíos de la era de la ‘IA en todas partes’, a fondo en Data & AI Summit 2025
  • “AI 비서가 팀 단위로 지원하는 효과”···퍼플렉시티, AI 프로젝트 10분 완성 도구 ‘랩스’ 출시
Recent Comments
    Archives
    • May 2025
    • April 2025
    • March 2025
    • February 2025
    • January 2025
    • December 2024
    • November 2024
    • October 2024
    • September 2024
    • August 2024
    • July 2024
    • June 2024
    • May 2024
    • April 2024
    • March 2024
    • February 2024
    • January 2024
    • December 2023
    • November 2023
    • October 2023
    • September 2023
    • August 2023
    • July 2023
    • June 2023
    • May 2023
    • April 2023
    • March 2023
    • February 2023
    • January 2023
    • December 2022
    • November 2022
    • October 2022
    • September 2022
    • August 2022
    • July 2022
    • June 2022
    • May 2022
    • April 2022
    • March 2022
    • February 2022
    • January 2022
    • December 2021
    • November 2021
    • October 2021
    • September 2021
    • August 2021
    • July 2021
    • June 2021
    • May 2021
    • April 2021
    • March 2021
    • February 2021
    • January 2021
    • December 2020
    • November 2020
    • October 2020
    • September 2020
    • August 2020
    • July 2020
    • June 2020
    • May 2020
    • April 2020
    • January 2020
    • December 2019
    • November 2019
    • October 2019
    • September 2019
    • August 2019
    • July 2019
    • June 2019
    • May 2019
    • April 2019
    • March 2019
    • February 2019
    • January 2019
    • December 2018
    • November 2018
    • October 2018
    • September 2018
    • August 2018
    • July 2018
    • June 2018
    • May 2018
    • April 2018
    • March 2018
    • February 2018
    • January 2018
    • December 2017
    • November 2017
    • October 2017
    • September 2017
    • August 2017
    • July 2017
    • June 2017
    • May 2017
    • April 2017
    • March 2017
    • February 2017
    • January 2017
    Categories
    • News
    Meta
    • Log in
    • Entries feed
    • Comments feed
    • WordPress.org
    Tiatra LLC.

    Tiatra, LLC, based in the Washington, DC metropolitan area, proudly serves federal government agencies, organizations that work with the government and other commercial businesses and organizations. Tiatra specializes in a broad range of information technology (IT) development and management services incorporating solid engineering, attention to client needs, and meeting or exceeding any security parameters required. Our small yet innovative company is structured with a full complement of the necessary technical experts, working with hands-on management, to provide a high level of service and competitive pricing for your systems and engineering requirements.

    Find us on:

    FacebookTwitterLinkedin

    Submitclear

    Tiatra, LLC
    Copyright 2016. All rights reserved.