Artificial intelligence negotiation algorithms: Pioneering artificial intelligence negotiation algorithms for business

Objective: The article aims to demonstrate AI’s role in supporting negotiation preparations, especially in defending the starting position. Research Design & Methods: In the article, we applied a descriptive analysis, with a prior review of literature sources, comparison, and deduction. We based the development of the artificial intelligence negotiation algorithms (AINA) on a heuristic-synthetic method. Findings: We propose an algorithm for defending the starting position that not only structures the negotiation process but also provides practical semantic tools to effectively defend the offer and build long-term relationships with customers. Implications & Recommendations: The AINA algorithm not only offers an effective tool for present negotiators but also provides the foundation for further identification and development of advanced negotiation algorithms. The considerations presented aimed at providing business practitioners with insights into the integration of AI into negotiation strategies and starting a dialogue on the unification of such algorithms in future AI models that will be capable of conducting complex negotiations. Contribution & Value Added: The presented algorithm for defending the starting negotiation position, which combines the F-A-B technique (Feature-Advantage-Benefit) with the straight line persuasion (SLP) model, represents a novel conceptualisation of defensive logic in negotiations. It focuses on resisting premature concessions while maintaining constructive dialogue. This synthesis constitutes a significant added value and an attempt to address an existing research gap.