Module I·Article III·~2 min read
Large Language Models: ChatGPT and Its Application in Business
Digital Transformation and AI
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What are LLMs
Large Language Models (LLM) are large neural networks trained on enormous volumes of text. GPT-4 (OpenAI), Claude (Anthropic), Gemini (Google), Llama (Meta) are the main models in the market.
Capabilities of LLMs: text generation (at the human level); answering questions; analysis and summarization of documents; translation; code writing; creative thinking.
Why LLMs are a breakthrough: before LLMs, AI performed well with structured data (images, numbers). LLMs opened AI to unstructured text—80% of corporate information is unstructured.
Corporate Application of LLMs
Content generation: marketing texts, product descriptions, reports, template documents. McKinsey estimates: AI automates 20-40% of office tasks.
Document analytics: legal contracts (risk analysis in minutes instead of hours), financial statements (anomaly detection), client complaints (classification, summarization).
Developer assistant: GitHub Copilot (OpenAI+Microsoft)—AI completes code, writes tests. Study: +55% to developer productivity.
Client service: AI agents resolving up to 80% of standard requests without human intervention. Sierra (startup): agents for corporate client service.
RAG (Retrieval-Augmented Generation): LLM + search in the corporate knowledge base. Answer to the question "What are the terms of our contract with client X?"—AI searches documents and responds precisely.
Risks and Limitations in Business
Confidentiality: public LLMs (ChatGPT) are trained on user queries. Corporate data cannot be sent to public APIs without checking policies. Enterprise versions (ChatGPT Enterprise, Azure OpenAI) are safer.
Accuracy: LLMs are not always accurate, especially for recent events or specific facts. Human-in-the-loop is necessary for critical decisions.
Copyright: AI-generated content—legal status unclear in most jurisdictions.
Practical Assignment
Choose one routine task that you perform weekly (report writing, composing emails, data analysis). (1) Test ChatGPT/Claude for this task. (2) Rate the quality of the result (1-10). (3) How much time was saved? (4) What needs to be improved in the prompt for a better result?
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