AI in Negotiation: How Providing Context Beats Generic Prompts
Artificial Intelligence is transforming negotiations, but not all AI usage is equally effective. Professor Yadvinder Rana, a CABL trainer and Professor of Cross-Cultural Negotiation at the Catholic University of Milan, has spent years researching how AI intersects with negotiation practice. In his work, he identifies four stages of AI adoption in negotiation, ranging from basic interaction with AI tools to fully integrated, organization-wide systems.
Most professionals today are still at the first stage. They open a general-purpose large language model, such as ChatGPT, Microsoft Copilot, Google Cloud Gemini, or Claude, type prompts, and receive generic answers. These outputs can seem helpful, but the AI has no understanding of the specifics of the deal. It doesn’t know your margins, internal approval processes, historical concessions, or your counterpart’s behavior. At this stage, AI acts as a polished question-and-answer tool, impressive in appearance but detached from actionable strategy.
The Real Game-Changer: Context Over Prompts
The second stage, however, is where the real transformation happens. Here, AI stops being a generic assistant and becomes a context-aware partner. Professionals provide the AI with structured information, such as past deals, strategic objectives, internal priorities, risk thresholds, and meeting transcripts, allowing it to reason within the actual negotiation. This enables AI to simulate trade-offs, stress-test proposals, identify hidden value opportunities, and highlight inconsistencies.
The power of Stage Two is simple but profound: it shifts the focus from asking smarter questions to feeding the AI the right context. This makes AI a strategic preparation engine, amplifying human insight instead of just generating generic suggestions.
Why Context is a Strategic Skill
Providing meaningful context is not a technical exercise, it’s a strategic one. Negotiators must clarify what truly matters in the deal, define their limits, and articulate acceptable trade-offs. By structuring information for the AI, they improve both its outputs and their own strategic thinking.
Reliability is also crucial. In high-stakes negotiations, AI outputs must be consistent and trustworthy. Stage Two emphasizes structured workflows to ensure that insights are both relevant and dependable, creating real competitive advantage.
The Competitive Divide
The future of negotiation will favor those who understand the value of context, not those who simply rely on clever prompts. Professionals who remain at the first stage may gain incremental insights, but those who embrace Stage Two, designing context-driven AI workflows, will gain a compounding advantage.
In the upcoming video, Professor Rana will explain all four stages of AI maturity, showing how negotiators can progress from basic interaction to fully integrated, high-performance AI systems.
For now, the key insight is clear: in negotiation, AI does not reward better prompts, it rewards better context.