Enterprise AI Analysis
A Bibliometric and Visualization Analysis of Generative AI Research in China
This study analyzes 1094 GenAI-related articles from the CNKI database to identify research hotspots and trends in China. Key areas include Large Language Models, diverse application fields (education, media, medicine, finance, law, digital government, metaverse), and critical challenges such as intellectual property, data security, and AI hallucination.
Executive Impact: Key Metrics at a Glance
This study analyzes 1094 GenAI-related articles from the CNKI database to identify research hotspots and trends in China. Key areas include Large Language Models, diverse application fields (education, media, medicine, finance, law, digital government, metaverse), and critical challenges such as intellectual property, data security, and AI hallucination.
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
LLMs form the technological backbone of GenAI, with rapid advancements and applications across various domains, from information management to finance and legal research.
GenAI is being applied across numerous sectors in China, with education, press & media, library science, medicine, finance, law, digital government, and the metaverse identified as key areas of interest.
Research highlights significant challenges including intellectual property, data security, ethical risks, AI hallucination, and the duty of care for GenAI service providers.
Enterprise Process Flow
| Application Field | Opportunities | Challenges |
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| Education |
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| Press & Media |
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| Library Science |
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Impact of ChatGPT on Information Management
ChatGPT, a prime example of an LLM, has profoundly impacted information resource management. Key areas include supporting algorithms, information resource construction, organization, retrieval, governance, content security, and human-computer interaction and collaboration. This showcases the widespread influence of LLMs.
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Your AI Implementation Roadmap
A strategic phased approach for integrating AI into your enterprise, ensuring maximum impact and smooth transition.
Phase 1: Discovery & Strategy
Initial assessment of current systems, identifying AI opportunities, and defining strategic objectives.
Phase 2: Data Preparation & Model Training
Collecting, cleaning, and preparing enterprise data; training or fine-tuning AI models.
Phase 3: Integration & Pilot Deployment
Integrating AI solutions with existing infrastructure; conducting pilot tests and gathering feedback.
Phase 4: Scaling & Optimization
Full-scale deployment across the organization; continuous monitoring, performance optimization, and updates.
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