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AI can help diplomats prepare for negotiations by finding information, drafting material and exploring possible scenarios. That may create an advantage in speed or analysis, but the available evidence does not show that AI systems have independently negotiated agreements, changed national positions or measurably shifted international public opinion. The “diplomatic weapon” is best understood as a potential source of state capability and influence—not an autonomous actor.
How can AI change diplomatic work?
AI may affect diplomacy through three distinct channels: analysis that informs a negotiating position, communication that shapes how a position is expressed, and diplomacy over the rules governing AI itself. These channels have different evidence behind them. A model can produce an analysis or a draft; governments and their officials remain responsible for deciding what to believe, say and commit to.
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Analysis and negotiation preparation
A 2022 study by Stiftung Wissenschaft und Politik, conducted as a pilot with Germany’s Federal Foreign Office, examined whether AI could predict state behavior in United Nations General Assembly voting. The authors concluded that AI could become an important tool for preparing and conducting negotiations, including by generating scenarios and forecasts.
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesThat is evidence of a research pilot and a proposed use, not proof that AI secured an agreement or caused a country to change its vote. For a diplomat, a forecast is useful only insofar as its assumptions, data and uncertainty can be examined. It should inform judgment, not stand in for it.
#1 Best Overall
Drafting, search and public communication
Generative AI can assist with tasks such as drafting, information retrieval, summaries, reports, conversational support, public-engagement material and policy documents. These capabilities could help a foreign ministry prepare briefings or adapt communications, but broad government-use statistics do not establish how often diplomatic services use them or whether they improve diplomatic outcomes.
The OECD’s 2025 report, Governing with Artificial Intelligence, analyzes 200 government AI use cases across 11 functions. Its examples establish a wider public-sector context for AI use, not a measured record of diplomatic performance.
Negotiations over AI rules
AI is also a subject of diplomacy. The G7 Hiroshima Process took stock of generative AI’s opportunities and challenges, while the UN Advisory Body on AI proposed steps for international cooperation and global governance. Here, governments and institutions are negotiating policy about AI; that is different from an AI system acting as a negotiator.
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What does the evidence say about AI’s diplomatic advantage?
The strongest case for an advantage is practical rather than proven: an organization that can retrieve and synthesize information quickly, test scenarios and produce drafts may be better prepared. These are plausible mechanisms for influence. The sources available here do not provide a measured causal estimate showing that models changed negotiation outcomes, state perceptions or international public opinion.
Rank #3
| Channel | What AI may contribute | What the evidence establishes | Key question for officials |
|---|---|---|---|
| Analytical assistance | Scenario generation, prediction, retrieval and summarization | The 2022 SWP pilot examined predicting UN General Assembly voting behavior and identified forecasts and scenarios as possible support for negotiation preparation. | Can staff validate the data, assumptions and uncertainty behind an output? |
| Communication assistance | Drafting or adapting policy and public-engagement content | OECD sources document these as government-wide AI use categories, not diplomacy-specific results. | Are claims accurate, culturally appropriate, traceable and reviewed by a responsible person? |
| Governance diplomacy | Shared principles, coordination and institutional arrangements | The G7 Hiroshima Process and UN governance initiatives show that AI itself is on the international policy agenda. | Are the rules inclusive, workable across jurisdictions and accessible to states with different capacities? |
These are useful comparison questions, not a ranking from a comparative trial. The European Parliament’s 2021 study, Artificial Intelligence diplomacy: Artificial Intelligence governance as a new external policy tool, offers a longer-running strategic frame: AI governance can be part of external policy, and AI may affect global politics and the balance of power. Because it predates the current wave of generative AI, it should not be treated as evidence about today’s large language models.
How widespread are relevant government uses?
The OECD’s Digital Government Outlook 2026 reports generative-AI use across 36 countries. The figures describe government-wide activity; the report figures cited here do not give a foreign-ministry subset or establish a diplomatic-services denominator.
Rank #4
- 20 of 36 countries (56%) reported generative-AI support for public servants, including drafting assistance, search and knowledge retrieval, and conversational support.
- 15 of 36 countries (42%) reported automated reports or summaries to inform decision-making.
- 15 of 36 countries (42%) reported citizen-engagement content, such as consultation replies and newsletters.
- 13 of 36 countries (36%) reported generative-AI assistance with policy-document creation.
These counts indicate that relevant capabilities are appearing across government. They do not show how many diplomatic teams use them, how frequently they do so, or whether use has altered negotiations. The OECD’s separate 2023 G7 report is also time-bound: it was a questionnaire-based stocktake reflecting trends identified in the first half of 2023, not a current global census.
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It could influence perceptions through the material officials use to assess a counterpart, the language in statements and briefings, or the scale and speed of public-facing content. But a model generating a message is not evidence that audiences were persuaded, that trust changed, or that another government revised its position. The cited sources do not quantify such effects.
Best Value
In practice, perception depends on more than the wording of a draft: who is speaking, whether the statement is credible, how it is translated and interpreted, and what audiences already believe. If AI-generated analysis or communications are used, officials should be able to check their origins and correct errors. They should also consider whether a model’s language or training data misrepresents cultural context or systematically favors some perspectives.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What safeguards belong in diplomatic use?
The OECD’s 2025 framework organizes trustworthy AI in government around three pillars: “enablers, guardrails and engagement.” It is a general public-sector framework, not a diplomatic trial. Applied to foreign-policy work, it suggests practical controls for protecting sensitive information and keeping responsibility with people and institutions.
Enablers: make reliable use possible
- Set clear governance and procurement rules, with named officials responsible for approving use cases.
- Use appropriate data, infrastructure and staff skills; ensure users understand what a model can and cannot establish.
- Assess whether unequal access to computing resources, data and expertise could widen differences in states’ ability to prepare and negotiate.
Guardrails: control risk and responsibility
- Do not put confidential negotiation material into a system unless its security and data-handling terms have been approved for that information.
- Check factual claims against authoritative sources, record the provenance of consequential outputs and make uncertainty visible.
- Test for errors, bias and weaknesses across languages and cultural contexts; use human review before outputs inform policy or are sent externally.
- Keep officials accountable for national positions, commitments and public statements. A model’s recommendation does not constitute policy authority.
Engagement: include affected people and partners
- Consider how public servants and citizens can raise concerns about AI-supported government services and communications.
- Coordinate across borders where shared risks or incompatible rules could affect cooperation.
- Make participation meaningful for countries with different technical and institutional capacities, not only those with the greatest resources.
Why is AI governance becoming a diplomatic issue?
International forums are trying to shape how AI is governed, including how countries cooperate and what institutions or shared principles are needed. The UN Advisory Body on AI’s September 2024 final report followed consultations involving more than 2,000 participants across all regions, more than 50 consultation sessions, and over 250 written submissions from more than 150 organizations and 100 individuals. Those figures describe the report’s consultation process, not public consensus on any particular proposal.
The UN’s Independent International Scientific Panel on AI was created by General Assembly resolution A/RES/79/325 on 26 August 2025. Announcing the panel, Secretary-General António Guterres said: “In a world where AI is racing ahead, this Panel will provide what’s been missing – rigorous, independent scientific insight.” Such initiatives show that international cooperation over AI is an active policy concern; they do not demonstrate that AI systems themselves exercise diplomatic authority.
What should readers conclude?
AI can support diplomatic preparation and communication, and governments are negotiating the rules around the technology. That gives states potential tools for analysis and influence, but the evidence cited here stops short of showing that AI has independently conducted diplomacy or produced measurable changes in negotiations or perceptions. The consequential questions are how reliable the inputs are, whether outputs can be scrutinized, who has access to the capabilities, and who remains accountable for decisions.
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