Managing Negotiations in the Age of AI
Artificial Intelligence is already transforming the way organisations do business: streamlining processes, analysing complex datasets, and unlocking competitive advantage. As its capabilities grow, there’s a growing belief that AI may also upend a critical interpersonal activity in business: negotiation.
Some see AI as a disruptive force that could one day replace negotiators altogether. Others dismiss it as a limited tool, incapable of matching human insight . The reality lies in between. AI will not be taking the lead in high-stakes negotiations any time soon, but it is already changing how negotiations are prepared, analysed, and supported. The future will belong to negotiators who can harness AI’s analytical power while bringing distinctly human skills, such as listening for nuance, trust-building, and adaptive judgment to the table.
Moving Beyond the Hype
AI’s value in negotiation is clear when the task involves recognising patterns in large, well-structured datasets. For example, with access to tens of thousands of past customer service transcripts and outcome data, AI can be trained to function as a competent service agent. Similarly, if provided with enough examples of near-identical, repetitive transactions—think perhaps of car sales—it could perform reasonably well in that negotiation context.
But commercial negotiations are rarely uniform. They are dynamic, shaped by unique personalities, shifting interests, and complex organisational politics. The vast and varied data required to train AI for every kind of negotiation simply doesn’t exist—and won’t for some time. Even if every meeting on Microsoft Teams, Zoom, or Webex were recorded and analysed, the sheer diversity and unpredictability of real-world negotiations would still leave huge gaps.
More importantly, the human side of negotiation—reading the room, sensing hesitation, building rapport, knowing when to push and when to pause—isn’t easily codified into data. Strategic deals, high-value partnerships, and dispute resolutions require not just an understanding of what happened in the past, but insight into why certain approaches work in specific contexts.
That said, there are five main areas where AI is already being trialled and used:
AI as a Negotiation Advisor
AI in Negotiation Preparation
AI for Coaching and Feedback
AI as a Negotiation Observer
AI as a Negotiator
1. AI as a Negotiation Advisor
One of AI’s earliest applications in this space has been ingesting the vast body of negotiation literature: books, case studies, and online content to act as an on-demand advisor. A negotiator can ask it about strategies, tactics, or alternative approaches and receive an immediate answer.
However, there are two major limitations:
Knowledge without judgment
AI is only as knowledgeable as the material it’s trained on. Not everything on the internet is good advice. AI can tell you about every tactic in the book, but it cannot reliably judge which tactic is best in your specific circumstances. A move that delivers a tactical win in one context might cause damage in another. Without situational judgment, knowledge without context can mislead.
Answering rather than questioning
When you ask AI a question, it tells you want you want to know, not what you need to know. Ask an expert negotiator and they will first ask more questions, probing your assumptions, reframing the problem, or exploring hidden variables. AI can only do this when prompted carefully, and even then, it’s following your lead rather than applying independent curiosity. AI is also easily guided. It may reverse its advice when challenged and, providing you ask the right question, will give you the answer you are looking for.
In other words, AI is a powerful reference tool, but it is not close to being a strategic advisor.
2. AI-Assisted Negotiation Preparation
Where AI truly shines is in preparation. Effective negotiation begins long before anyone sits down at the table. AI systems can provide negotiators with powerful insights that would be difficult to gather manually, such as:
Historical negotiation outcomes
Opponent or counterparty behaviour patterns
Industry benchmarks and pricing trends
Legal, financial, and compliance risks
Macroeconomic and market conditions
These insights can help negotiators anticipate likely sticking points, identify trade-offs, and enter discussions with greater confidence and clarity.
However, data alone doesn’t determine the best path forward. Negotiators still need to weigh competing priorities, decide on walk-away points, shape the framing of the conversation, consider long-term relationship impacts and many other factors
AI can produce vital insights to inform these choices, but it can’t make them. Human expertise and judgment will remain essential for effective preparation and strategy.
3. AI for Coaching and Feedback
Preparation is not just analytical—it is also about building skill. Experienced negotiators often use simulations, wargames, and “red-blue” team exercises to rehearse strategies and test responses to pressure.
AI-driven coaching tools, such as those in development at MIT Sloan and INSEAD, have been developed to give constructive feedback by:
Flagging emotionally charged language
Suggesting alternative phrasing or framing
Identifying strong and weak questioning techniques
Highlighting potential risk points in the dialogue
Offering tactical suggestions for exploration
Such feedback can accelerate some aspects of skill development, particularly for less experienced negotiators, but unless these tactical and verbal insights are paired with strategic insight, key skills remain unaddressed. Context is key. Knowing what to do is one thing; understanding why it matters and when to apply it is another. This is exactly why the way Negotiation Partners teach negotiation skills is so powerful and why coaching by expert negotiators remains essential.
4. AI as a Negotiation Observer
AI coaching tools have also been used as a silent partner during negotiations: listening in, analysing exchanges in real time, and offering tactical prompts. Post-negotiation, AI could produce detailed breakdowns of turning points, sentiment shifts, and potential missed opportunities.
Whilst appealing in theory, AI faces two challenges in the observer role:
Lack of insight and strategic judgment
In complex negotiations, every context is different. Cultural factors or language differences will have an impact. ‘Yes’ and ‘No’ don't always mean ‘Yes’ and ‘No’. The right move in one situation may be disastrous in another.
The chilling effect
Effective negotiations thrive on trust and candour. So often in challenging negotiations, the breakthrough did not come at the table, but during informal conversations over coffee or during breaks.
The mere knowledge that an AI is recording, transcribing, and analysing a negotiation can make participants cautious and have a chilling effect on the free-flowing exchange of information and ideas. This is particularly relevant to AI tools that are currently being trained to flag “inappropriate offers”, “probity violations” and “unethical conduct”.
Introducing a powerful AI tool, especially where its action is potentially punitive will have negative repercussions for the negotiation.
If an AI observer must be involved, ensure it is an agreed third-party tool and that both sides have independent access to its output. For complex, sensitive deals, a skilled human observer on your team remains the better choice.
5. AI as a Negotiator
Autonomous AI negotiators are already in use in certain transactional settings, such as procurement platforms and customer service systems. These environments share two traits: abundant historical data and predictable, rules-based interactions.
Complex, strategic negotiations are neither predictable nor reliably rational. Preferences are non-linear and may shift mid-discussion. Relationships matter. Emotions influence decisions. Trust, rapport, and long-term considerations are key.
AI also raises legal and ethical concerns. Sensitive information disclosed to an AI may be stored indefinitely and disclosed, leveraged or exploited in ways not anticipated by either party.
AI agents also have an Achilles heel. Having developed a preferred pattern, this can be analysed and exploited. One example is an AI procurement agent that drives for three ‘best and final offers’ (BAFO) and if the last is not acceptable, will continue negotiating until the other side restates the same offer three times, after which it will accept. Good to know.
As long as trust, expertise, adaptability and emotional nuance matter, AI will struggle to lead in high-stakes, bespoke negotiations.
Why Human-Centred Skills Still Matter
Despite AI’s advances, several human skills remain irreplaceable:
i. Building trust
Trust is the currency of long-term deals. AI can calculate optimal terms, but it cannot deliver personal integrity, the willingness of both parties to take a risk, to share information or the ability to inspire confidence during uncertain times.
ii. Asking the right questions
AI responds to the questions it is given. Skilled negotiators know how to probe gently, follow cues, and surface unexpected opportunities. They will recognise what the other side has not said and seek to reveal hidden truths, deeper interests, and unspoken concerns that need to be addressed.
iii. Managing emotional dynamics
Internal negotiations over budgets, resources, and timelines often involve colleagues with shared histories. External negotiations can be equally fraught, involving stakeholders with long memories. AI may support planning, but it cannot read the room, manage emotions or navigate political sensitivities.
iv. Creative problem-solving
Negotiation isn’t just about compromise and finding a middle ground: it’s about creating value. The best deals often involve unconventional trade-offs that create value for both sides. AI can identify patterns, but humans are better at reframing problems to discover hidden solutions. It’s not immediately obvious to AI why one side might agree to waive local shipping costs in return for a warm introduction to a major client of the other.
v. Valuing relationships over short-term wins
AI may be able to help optimise contract terms, but strategic negotiation is about more than a ‘win’: it’s about building sustainable partnerships. Power ebbs and flows. Buyers who had abused their leverage before COVID-19 found themselves disadvantaged when suppliers had the upper hand. Many suppliers were more accommodating and responsive to buyers who had built strong, respectful relationships.
The Hybrid Future: AI-Informed Negotiators
The most likely and most productive future is one where AI is assisting negotiators, not replacing them:
AI provides: data analysis, risk modelling, predictive insights, pattern recognition, and administrative efficiency.
Experienced Negotiators provide: strategic judgment, creativity, stakeholder management, emotional intelligence, and a breadth of cultural and sector- and deal-specific expertise that is beyond what can be read in a book.
Negotiators, assisted by AI, can build on the strengths of both and be both analytically empowered and emotionally intelligent.
To prepare for this future, organisations should:
Train negotiators in both AI literacy and strategic thinking,
Develop clear ethical frameworks for AI use in negotiations,
Encourage learning and skills development in their negotiators, and
Avoid over-reliance on AI-generated insights without expert validation.
Conclusion: Balancing Power in the AI Era
AI is not replacing negotiators—it is redefining the skills they will need to excel. Those who rely solely on intuition will be outmanoeuvred by data-driven rivals. Those who follow algorithms blindly will misjudge the human factors that make or break deals.
The most effective negotiators will be those who balance analytical precision with empathy and careful listening, creativity, and foresight. They will understand that negotiation is not simply a sequence of tactics, but a coherent strategy aimed at sustainable outcomes.
In the age of AI, negotiation is both art and science. The winners will be those who master both—and who use AI not as a crutch, but as a catalyst for better, smarter, and more human-centred agreements.
Written by Dr Matt Lohmeyer and Mark Spatz