It is natural to associate AI with risk in wartime. AI can be misused, and we don't pretend otherwise. But there is a quieter side to the story. Peace-builders, humanitarian agencies and researchers already use AI tools to see trouble coming, to help people understand each other, to widen who is heard in peace talks, and to check what is true. This page covers only tools that have actually been used, with their limits stated plainly.

The most important point first: AI does not make peace. People do. At its best, AI helps them see a little further, hear a few more voices, and waste less time on falsehoods.

1. Seeing risk earlier: conflict forecasting

What it is. Conflict forecasting uses statistics and machine learning (software that learns patterns from past data) to estimate where violence is more likely in the coming months. The aim is not to predict the future with certainty. It is to give humanitarian agencies and governments time to prepare.

A real example: VIEWS. The Violence & Impacts Early-Warning System, co-hosted by Uppsala University and the Peace Research Institute Oslo (PRIO), publishes open-source forecasts of armed conflict from 1 to 36 months ahead, updated every month. Its June 2026 release includes detailed, map-based forecasts for Africa and the Middle East. Its funders include UN ESCWA, the UN's economic and social commission for Western Asia, through a joint ViEWS-ESCWA project, as well as the UK Foreign, Commonwealth & Development Office and UNHCR. In April 2026 it began collaborating with the UN Food and Agriculture Organization on "anticipatory action", which means acting before a crisis peaks, not after (VIEWS).

Its limits. Forecasts are probabilities, not certainties. They depend on the quality of the data behind them, and they can be wrong. They also raise a responsibility question: an early warning is only useful if someone acts on it.

2. Understanding each other: translation

What it is. Machine translation lets people read and speak across languages. In a region with Arabic, Persian, Kurdish, Turkish, Hebrew and many dialects, this matters for aid workers, journalists, negotiators and ordinary families.

A real example: No Language Left Behind. Meta's NLLB-200 model, published in Nature in June 2024, translates across 200 languages, including many "low-resource" languages that previous tools served poorly. The researchers report an average improvement of 44% on a standard quality measure compared with earlier systems. They released their models and data free for non-commercial use (Nature, 5 Jun 2024). Their own conclusion is modest: the model is "one piece of a massive puzzle", and education, internet access and digital literacy still matter.

The Gulf's contribution. Arabic-first models such as Fanar (Qatar), ALLaM (Saudi Arabia) and Jais (UAE) are designed to understand Arabic and its dialects better than general-purpose tools. Fanar's builders, for example, describe dialect-aware speech recognition. Better Arabic language technology is not a peace tool in itself. But misunderstanding is often where tension starts, and better translation removes one source of it.

Its limits. Machine translation still makes mistakes, especially with dialect, idiom and emotionally loaded language. In sensitive negotiations, human interpreters remain essential.

3. Hearing more voices: AI-assisted dialogue

What it is. Peace talks usually involve a small number of people in a room. AI-assisted dialogue tools let a mediator hold a structured, real-time conversation with hundreds or thousands of people at once. The software groups similar answers together and shows where people agree.

Real examples: Yemen and Libya.

  • In June 2020, the Office of the UN Special Envoy for Yemen, with the UN Department of Political and Peacebuilding Affairs, held a digital dialogue with more than 500 Yemenis. The tool allows one person to converse with up to 1,000 people in real time. The UN described it as the first use of this technology in an active UN mediation process. The then Special Envoy, Martin Griffiths, acknowledged its limits, including that not everyone could take part (OSESGY, Aug 2020).
  • The UN Support Mission in Libya held similar digital dialogues with up to 1,000 Libyans at a time in 2020–21 (ReliefWeb).

Why it matters. Women, young people and displaced communities are often absent from formal negotiations. These tools cannot give them a seat at the table, but they can make sure their views reach it.

Its limits. People need connectivity and a safe way to take part. Online samples are never fully representative. And a mediator has to decide what to do with what they hear.

4. Checking what is true: verification

What it is. In any conflict, false images and videos spread quickly, and AI now makes convincing fakes easier to produce. The International AI Safety Report 2026 lists scams, deepfakes and manipulation among the main current harms of AI (executive summary). Verification tools are part of the answer.

A real example: Content Credentials (C2PA). The Coalition for Content Provenance and Authenticity publishes an open standard that attaches a tamper-evident record to a photo, video or document. The record shows where the file came from, how it was edited, and whether AI was used to make it. If the file or its record is altered, the change can be detected (C2PA explainer). The standard's own authors are careful about what it can and cannot do. It "is not a cure-all for misinformation". It does not judge whether content is true, only whether its history is intact. It works alongside fact-checking and media literacy, and it depends on wide adoption.

Its limits. Most content online carries no credentials yet, and bad actors can strip metadata. Verification tools help careful people. They do not replace care.

5. The Gulf's possible role

The Gulf states bring several things to this work:

  • A record of convening. Oman hosted the first round of indirect US–Iran talks in Muscat in April 2025 (Reuters; search-verified). Qatar and others have also played mediation roles.
  • Arabic language technology, which can improve translation and dialogue tools for the region.
  • Compute and research capacity, which could support regional early-warning, humanitarian data and verification work.
  • Stated principles. The UAE's AI Charter (2024) includes "peaceful coexistence" among its 12 principles (UAE Government portal).

These are possibilities, not achievements. We will report on them only as they are carried out.

The honest counterweight

AI also has military uses, and the same technologies that forecast risk or verify images can be turned to surveillance or targeting. The 2026 war in the region is a reminder that digital infrastructure itself can come under attack (see Resilience in 2026). Acknowledging this is not pessimism. It is why peace-oriented uses deserve deliberate support and funding, rather than being left to chance.

What this means for you

  • Treat dramatic images from conflict zones with patience. Check the source and look for verification.
  • If you work in aid, media or policy, open tools such as VIEWS forecasts and Content Credentials are available now.
  • Support efforts that widen who is heard. Technology that helps more people speak is one of the most hopeful uses of AI.