AWS is entering the South Korean enterprise artificial intelligence (AI) agent market with its new product, 'Amazon Quick,' which connects corporate data and work applications. As generative AI evolves into 'agentic AI' capable of performing actual tasks, AWS has expanded its business intelligence (BI) and enterprise data utilization technologies into work-related AI over the past decade.
On August 12, AWS Korea held a press conference in Gangnam, Seoul, to introduce the key features of the AI assistant Amazon Quick and its applications both domestically and internationally.
Amazon Quick is an AI assistant that integrates over 40 work applications, including Slack, Salesforce, and Google Workspace, along with local files, calendars, and emails. It can analyze data scattered across various platforms and generate reports or automate repetitive tasks using natural language commands. A key feature is its ability to understand the relationships between work data, continuously leveraging the user's work context.
Park Hye-young, Chief Solutions Architect at AWS Korea, noted, "AI agents have progressed from merely answering questions or recommending information to making judgments and taking actions themselves." She explained that the use of AI in businesses is expanding from supporting individual tasks like searching and document creation to executing and automating entire workflows.
Park emphasized the need for AI tools that can operate across multiple applications. She pointed out that even companies that have adopted generative AI still require employees to navigate various apps for actual work processes. While AI can search for information and draft documents, follow-up tasks like sending emails or scheduling appointments still require manual handling within each application.
According to research, office workers spend about 40 hours a month switching between different work applications. "AI can provide answers, but sending emails, scheduling, and recording in internal systems still require accessing each app individually," she said.
AWS has validated the effectiveness of Amazon Quick in workplace applications over six months with 200,000 Amazon employees, resulting in over 300,000 automated tasks. The time taken to create reports, which previously required about three hours for data collection, formatting, drafting, and feedback incorporation, has been reduced to around five minutes through natural language commands.
The foundation of Amazon Quick is built on AWS's accumulated expertise in enterprise data analysis and utilization over the past decade. AWS began analyzing structured data through its BI service, 'Amazon QuickSight,' in 2015. As corporate needs expanded to include unstructured data like documents and emails, it broadened its scope with 'Amazon Q Business.'
Recently, as the use of generative AI has expanded beyond information retrieval and analysis to actual task execution and automation, these functions have been integrated into Amazon Quick. AWS highlighted its unique capability to combine its accumulated enterprise data processing capabilities with connectivity that is not dependent on specific work applications, allowing for expansion from individual to organizational task automation.
In South Korea, AWS has already secured adoption cases. According to AWS, Black Yak is utilizing Amazon Quick for natural language-based data analysis in its existing BI operations, while Megazone Cloud has implemented it for automating repetitive tasks and data analysis.
Park stated, "Amazon Quick is a service designed for all employees, not just developers, and is structured to be usable at both individual and organizational levels."
* This article has been translated by AI.
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