Indrani Mahesh Jadhav
In an era where traditional multilateral institutions are increasingly paralyzed by bureaucracy, competing interests, and geopolitical polarization, mini-lateralism has emerged as a preferred diplomatic strategy. These smaller, more agile coalitions allow like-minded states to coordinate rapidly on current global issues. But what if the next evolutionary leap in diplomacy isn’t just smaller, but smarter? This article explores the provocative possibility that artificial intelligence (AI) could play a central role in mini-lateral forums, not just as a tool, but as a participant. One that may eventually replace traditional diplomats in specific contexts.[1] While this vision is speculative, it is grounded in real technological developments, from language models capable of negotiation to blockchain enforced compliance systems. What would diplomacy look like if algorithms were at the table?
The Rise of Minilateralism
Mini-lateralism refers to small-group diplomacy involving a limited number of states, often bound by shared interests, values, or regional stakes. Forums like the Quad (US, India, Japan, Australia), AUKUS, and the Visegrád Group exemplify this trend. These formats allow for faster coordination, reduced negotiation fatigue, and flexibility, basically qualities that align well with the demands of a rapidly changing global landscape.[2] These alliances often rely on backchannel negotiations, informal agreements, and elite diplomacy, all of which are time-intensive and prone to miscommunication. They provide a middle path, where like-minded states can pursue shared goals on climate, cyber, defense, or trade without waiting for laggards or spoilers. As the number of overlapping mini-lateral clubs grows, so does the complexity of the global system inviting calls for new tools to manage it.
However, even mini-laterals face familiar challenges such as decision-making inertia, strategic ambiguity and the delicate balance of national interests. This is where AI steps in, not merely as a support mechanism but potentially as a game-changer.
AI in Diplomacy: Present Capabilities
AI tools are already used in some diplomatic processes. Natural language processing (NLP) models help analyze treaties and diplomatic cables, data analytics support intelligence gathering and chatbots assist consular services. Predictive models can forecast political instability or simulate the outcomes of international agreements.[3] Multi-agent systems can model geopolitical scenarios, optimize negotiation outcomes, and evaluate strategic alignments in real time.
In the context of minilateralism, the advantages of AI are clear. Small coalitions often operate with minimal bureaucratic oversight, allowing for experimental governance methods. AI tools can automate the tedious work of policy alignment, detect inconsistencies in draft communiqués, and simulate likely reactions from third-party states. AI can also offer unbiased feedback on the strategic trade-offs of different negotiation paths, thereby enhancing the quality and speed of decision-making.
These functions, though auxiliary, show AI’s growing potential. What if we took it further? What if AI was assigned real-time negotiations between states to draft agreements, mediate disputes, or optimize cooperation on shared objectives?
Algorithmic Negotiation and the Mini-lateral Advantage
Unlike multilateral forums, where AI integration may be politically controversial or logistically overwhelming, mini-laterals offer a controlled sandbox. Their smaller size, trust-based structure, and task-specific focus make them ideal environments for experimenting with algorithmic diplomacy.
AI agents could model national preferences, simulate negotiation scenarios, and generate policy options based on predefined strategic priorities. Countries could input non-negotiable red lines, economic thresholds, or geopolitical goals into AI platforms, which would then generate a “negotiated” outcome instantly. Such systems could dramatically reduce the time spent in negotiation cycles while maintaining fairness and transparency through traceable data logs.[4]
Case Study: South Korea and the AI Action summit- Paris Declaration
Instead of months of back-and-forth diplomacy, an AI platform simulates various configurations of funding, intellectual property sharing, and market access in developing countries like South Korea.[5]
The AI Action Summit, held on February 10 and 11 2025, in Paris, marked a significant shift in global conversations about artificial intelligence. From cautious regulation to practical deployment. Co-hosted by French President Emmanuel Macron and Indian Prime Minister Narendra Modi, the summit gathered over 1,000 participants from more than 50 countries, including heads of state, tech leaders, academics, and civil society organizations. Unlike earlier summits focused primarily on AI safety and existential risk, Paris emphasized AI as a development tool, especially in public infrastructure, sustainability, education, and climate action.[6]
Benefits: Speed, Transparency, and Scenario Modelling
AI can digest vast datasets on trade, security, public opinion, and environmental impact far faster than human teams. It can model dozens of negotiation pathways simultaneously, presenting the most viable outcomes. With transparent algorithms and open-source audit trails, concerns about manipulation or bias can be partially mitigated.
Mini-laterals could lead the way by creating a “Diplomatic AI Charter,” which outlines ethical principles, transparency standards, and human override mechanisms for AI-driven negotiations. These charters could themselves be drafted with the help of AI, ensuring consistency, adaptability, and data-driven policy alignment.[7]
Furthermore, transparency dashboards, akin to blockchain explorers could be developed to track changes in draft agreements, explain AI recommendations, and log negotiation iterations[8]. These tools would increase accountability while preserving the agility that makes minilateralism attractive.
Moreover, AI could serve as a neutral third party in sensitive negotiations, reducing emotional friction or historical baggage that might cloud judgment among human negotiators.
Challenges and Ethical Concerns
While the benefits of algorithmic diplomacy are compelling, the challenges are profound. Who codes the AI? Whose values are embedded in the algorithms? An AI trained on Western liberal norms may not be accepted by states with different governance models. Moreover, algorithms lack emotional intelligence, cultural sensitivity, and the ability to build trust—hallmarks of effective diplomacy.
There is also the risk of opacity[9]. AI systems, particularly deep learning models, operate as black boxes. If a diplomatic decision emerges from an AI-generated recommendation, it may be difficult to trace the rationale, raising concerns about accountability and democratic oversight. And in the wrong hands, algorithmic diplomacy could be weaponized: imagine a scenario where an adversarial state floods the negotiation model with false data or subtly biases outcomes through manipulated training sets.
These questions highlight the need for strict ethical frameworks and international standards governing AI’s diplomatic use.
The Future: From Support Tool to Diplomatic Actor?
Looking ahead, AI may move from being a silent assistant to a visible actor in mini-lateral settings. Imagine a scenario where two countries ask an AI arbitrator to propose trade quotas or environmental targets based on real-time economic data. Or where a digital platform autonomously drafts a cyber-security protocol tailored to the unique tech ecosystems of three allied states.
In time, AI could even be trained to recognize and negotiate based on cultural cues, historical grievances, and soft-power concerns. Minilateralism, with its compact size and shared goals, provides the perfect testing ground for such futuristic tools.
Governance Before and After AI
A Diplomatic Inflection Point Before the rise of AI, governance in minilateralism relied heavily on human intuition, elite networking, and analog protocols. Outcomes were shaped in late-night conversations, slow-moving consensus-building, and diplomatic theater. Decision-making was deeply subject to historical memory and cultural intuition. Ambiguity often served as a tool of compromise, and delay was sometimes strategic.
After AI, governance becomes faster, more precise, and optimized for measurable outcomes. AI-driven analytics replace instinct with simulations, while real-time language processing enables instant treaty drafting. Disagreements are parsed not through persuasion, but probability curves.
AI and the Erosion of Multilateralism?
There is a deeper irony here, if minilateralism empowered by AI becomes the norm, it may further erode the legitimacy of multilateral institutions. Faster, more efficient mini-lateral pacts may make the slow, consensus-heavy models of the UN or WTO seem obsolete. This could lead to a tiered diplomatic ecosystem, where high-speed, high-tech mini-lateral clubs dictate global norms, leaving less digitally advanced states marginalized.[10]
Alternatively, mini-laterals could serve as innovation hubs, testing AI-driven diplomatic models that are later scaled up to multilateral forums. In this optimistic scenario, AI becomes a tool not of exclusion, but of revitalization.
Mini-lateralism and AI are both responses to the same global condition: the failure of bloated, rigid systems to deliver timely, effective solutions. Together, they may form a new diplomatic model,one that is agile, intelligent, and post-human in its logic. Yet, as we race toward this frontier, the essence of diplomacy, trust, empathy, and human judgment must not be lost. The goal should not be to replace diplomats but to reimagine diplomacy itself, using AI as an ally rather than a substitute. In the age of algorithmic alliances, the future of global cooperation may depend not just on what we agree upon, but on how we compute consensus.
The potential for AI to transform diplomacy is immense, particularly within the flexible, agile world of minilateralism. While full replacement of human diplomats is neither desirable nor imminent, hybrid models where AI augments and accelerates diplomatic processes are already within reach. The challenge lies in ensuring that this transformation is equitable, accountable, and normatively grounded.
Minilateralism, once seen as a pragmatic stopgap, may become the crucible in which algorithmic diplomacy is forged. If guided wisely, the role of diplomats will not be hindered but it will definitely give rise to a smarter and intelligent innovation.
[1] https://www.reddit.com/r/MachineLearning/comments/zfeh67/d_were_the_meta_ai_research_team_behind_cicero/
[2]https://visionias.in/current-affairs/monthly-magazine/2024-07-27/international-relations/rise-of-minilaterals
[3] https://www.xenonstack.com/blog/nlp-in-government
[4] https://www.ismworld.org/supply-management-news-and-reports/news-publications/inside-supply-management-magazine/blog/2024/2024-04/how-ai-is-transforming-negotiations/#:~:text=AI%20can%20analyze%20data%20and,a%20dynamic%20toolbox%20of%20possibilities.
[5] https://www.gsma.com/solutions-and-impact/connectivity-for-good/mobile-for-development/blog/ai-innovations-driving-climate-action-in-apac-insights-from-m360/#:~:text=AI%20helps%20gathering%2C%20completing%20and,and%20are%20looking%20for%20partnerships.
[6] https://en.wikipedia.org/wiki/AI_Action_Summit?
[7] https://economictimes.indiatimes.com/tech/artificial-intelligence/un-advisory-body-makes-seven-recommendations-for-governing-ai/articleshow/113481954.cms?from=mdr
[8] https://hellotars.com/blog/ai-for-good-governance-top-10-ways-how-ai-can-transform-government-operations
[9] https://www.ibm.com/think/insights/10-ai-dangers-and-risks-and-how-to-manage-them
[10] https://www.cigionline.org/publications/advancing-multi-stakeholderism-for-global-governance-of-the-internet-and-ai/#:~:text=There%20are%20growing%20tensions%20between,throughout%20the%20product%20life%20cycle.