Technique

Chain-of-Thought Reasoning

Chain-of-thought (CoT) reasoning is a prompting technique that guides AI to solve problems step-by-step, dramatically improving accuracy on complex reasoning tasks.

What Is Chain-of-Thought Reasoning?

Chain-of-thought (CoT) reasoning is a prompt engineering technique where the AI is instructed to work through problems step by step — showing its reasoning process before reaching a conclusion. Research shows CoT can improve accuracy by 20-40% on complex reasoning tasks compared to direct answers.

How Is Chain-of-Thought Used in Business AI?

CoT is essential in agentic AI systems that make multi-step decisions — analyzing customer requests, evaluating options, and selecting actions. It also enables transparent decision-making: the AI explains its reasoning, which supports explainability requirements and allows humans to verify AI logic before acting on recommendations.

chain-of-thoughtCoTAI reasoningstep-by-step AI

Related Terms

Prompt Engineering

Prompt engineering is the practice of designing and optimizing the instructions given to AI models to elicit accurate, relevant, and useful responses for specific tasks.

Agentic AI

Agentic AI refers to autonomous AI systems that can plan, execute, and learn from multi-step tasks without human intervention at each step — managing complete business workflows independently.

Explainable AI (XAI)

Explainable AI refers to techniques that make AI decision-making processes transparent and understandable to humans, enabling trust, debugging, and regulatory compliance.

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