AI is supercharging war. Could it also help broker peace?

Can we measure what is in our hearts and minds, and could it help us end wars any sooner? These are the questions that consume entrepreneur Shawn Guttman, a Canadian émigré who recently gave up his yearslong teaching position in Israel to accelerate a path to peace—using an algorithm.

Living some 75 miles north of Tel Aviv, Guttman is no stranger to the uncertainties of conflict. Over the past few months, miscalculated drone strikes and imprecise missile targets—some intended for larger cities—have occasionally landed dangerously close to his town, sending him to bomb shelters more than once.

“When something big happens, we can point to it and say, ‘Right, that happened because five years ago we did A, B, and C, and look at its effect,’” he says over Google Meet from his office, following a recent trip to the shelter. Behind him, souvenirs from the 1979 Egypt-Israel and 1994 Israel-Jordan peace treaties are visible. “I’m tired of that perspective.”

The startup he cofounded, Didi, is taking a different approach. Its aim is to analyze data across news outlets, political discourse, and social media to identify opportune moments to broker peace. Inspired by political scientist I. William Zartman’s “ripeness” theory, the algorithm—called the Ripeness Index—is designed to tell negotiators, organizers, diplomats, and nongovernmental organizations (NGOs) exactly when conditions are “ripe” to initiate peace negotiations, build coalitions, or launch grassroots campaigns.

During ongoing U.S.-led negotiations over the war in Gaza, both Israel and Hamas have entrenched themselves in opposing bargaining positions. Meanwhile, Israel’s traditional allies, including the U.S., have expressed growing frustration over the war and the dire humanitarian conditions in the enclave, where the threat of famine looms.

In Israel, Didi’s data is already informing grassroots organizations as they strategize which media outlets to target and how to time public actions, such as protests, in coordination with coalition partners. Guttman and his collaborators hope that eventually negotiators will use the model’s insights to help broker lasting peace.

Guttman’s project is part of a rising wave of so-called PeaceTech—a movement using technology to make negotiations more inclusive and data-driven. This includes AI from Hala Systems, which uses satellite imagery and data fusion to monitor ceasefires in Yemen and Ukraine. Another AI startup, Remesh, has been active across the Middle East, helping organizations of all sizes canvas key stakeholders. Its algorithm clusters similar opinions, giving policymakers and mediators a clearer view of public sentiment and division.

A range of NGOs and academic researchers have also developed digital tools for peacebuilding. The nonprofit Computational Democracy Project created Pol.is, an open-source platform that enables citizens to crowdsource outcomes to public debates. Meanwhile, the Futures Lab at the Center for Strategic and International Studies built a peace agreement simulator, complete with a chart to track how well each stakeholder’s needs are met.

Guttman knows it’s an uphill battle. In addition to the ethical and privacy concerns of using AI to interpret public sentiment, PeaceTech also faces financial hurdles. These companies must find ways to sustain themselves amid shrinking public funding and a transatlantic surge in defense spending, which has pulled resources away from peacebuilding initiatives.

Still, Guttman and his investors remain undeterred. One way to view the opportunity for PeaceTech is by looking at the economic toll of war. In its Global Peace Index 2024, the Institute for Economics and Peace’s Vision of Humanity platform estimated that economic disruption due to violence and the fear of violence cost the world $19.1 trillion in 2023, or about 13 percent of global GDP. Guttman sees plenty of commercial potential in times of peace as well.

“Can we make billions of dollars,” Guttman asks, “and save the world—and create peace?” 

The Ripeness Index

Every evening, Didi’s bots scrape the websites of 60 Israeli and 30 Palestinian media outlets, digesting keywords into its Ripeness Index model. The index, a colorful radar chart resembling a digital version of the vintage puzzle game Simon, aims to distill the complex dynamics of Israeli-Palestinian social unrest into simple categories. These categories indicate when the time may be right to push for peace through grassroots messaging and diplomatic activity.

If the center of the index is red, it signals that conditions are not yet ripe for negotiations. In such cases, messaging efforts should focus on shifting the surrounding red sections of the model to yellow. Yellow indicates that both sides are beginning to recognize that the costs of continuing the conflict outweigh the benefits.

In early May, Guttman and his cofounder, Keren Winter-Dinur, a doctoral student in conflict resolution, worked with a team of developers to put the system through its biggest test to date. The occasion was the annual People’s Peace Summit in Jerusalem. This year’s summit was organized by the It’s Time coalition—a network of dozens of grassroots organizations seeking solutions to the Israeli-Palestinian conflict—and brought together 15,000 attendees from peace-focused groups on both sides of the border.

Many of the summit’s events are “talking about, ‘Hey, Israelis, learn about and understand what Palestinians are going through,’” Guttman says. “See the other.” The “ripeness” theory of negotiation, first introduced by Zartman in 1989, proposes that conflicts become ripe for resolution when two conditions are met. The first is the experience of a “mutually hurting stalemate,” where both sides are suffering and see no viable, unilateral path to a satisfactory outcome. The second is that both parties perceive a “way out” of the conflict. At this moment of “ripeness,” the door to negotiation opens.

More recently, as big datasets around conflict resolution have become more easily available, researchers have tried to quantitatively validate Zartman’s theory on past diplomatic negotiations. Still, quantitative studies around ripeness theory remain limited. 

When they launched Didi in 2022, Guttman and Winter-Dinur began by testing their Ripeness Index model on a different conflict: the Troubles in Northern Ireland in the years leading up to the 1998 Good Friday Agreement. After scraping a decade’s worth of speeches from the U.K. Parliament, the team found that support for negotiated peace increased on both sides just before key political partnerships formed, while support for continuing armed struggle diminished.

Then October 7th happened. Guttman and Winter-Dinur knew they needed to pivot to Israel’s war. They began localizing their training database in Hebrew and Arabic and started scraping regional news. Their dataset now extends back to September 26, 2023.

“I said, ‘Let’s jump into the deep waters and see how we do,’” Guttman recalls.

As it scans the news media, the bot tracks specific terms associated with each section of the Ripeness Index, such as confident in winning or willingness to compromise. At the bottom of the dashboard, graphs plot the frequency of flagged keywords in Israeli and Arabic news outlets over time, aligned with the model’s criteria. For the It’s Time coalition, the model also tracks mentions of affiliated organizations, such as the pro-peace group Women Wage Peace and a recent Israeli-Palestinian memorial gathering.

Guttman believes grassroots organizations should be using this data every day to spread pro-peace messaging to the public, alongside documentation of wartime atrocities, and to challenge the belief that military victory is necessary. “We should be moving as fast as the news cycle moves,” he says.

One promising signal came in January, at the start of a two-month ceasefire between Israel and Hamas, when Guttman and his team observed a surge in Israeli sentiment toward compromise.

“According to the theory, that moment of ripeness was what gave the Israeli political echelon the legitimacy and the support to say, ‘Okay, we’re going to have a ceasefire, we’re going to give humanitarian aid, we’re going to exchange Palestinian prisoners for Israeli hostages,’” Guttman says.

But that sentiment declined soon after and dropped sharply in March. That same month, citing stalled ceasefire negotiations, Israel resumed its ground war in Gaza. Guttman interprets the public shift as a response to the perceived failure of political efforts to secure the return of Israeli hostages.

Then, in the week leading up to the People’s Peace Summit in early May, the model determined that both Israeli and Palestinian publics saw a potential “way out” of the war. Still, the moment was not yet ripe for negotiations. On the left side of the index, the “confident in winning” and “impossibility of winning” sections had yet to shift into the green zone.

Alongside the insights Didi gathers from the news media, the It’s Time coalition also has been collecting data from social media platforms, including Facebook and X. Social media sentiment analysis is on Didi’s road map as well, but Guttman and Winter-Dinur caution against using it as a source of ground truth. 

Guttman and his team are still learning the limitations of their own data, too. Manual validation is important because the AI still misclassifies news articles. And Guttman admits that the model’s capabilities in Arabic are not yet as good as they are in Hebrew, a problem future datasets will address, he says. 

What could go wrong?

The company’s mix of AI and big data will also need to win over skeptics in the world of diplomacy. One concern is that relying on historical data to make predictions and inform decision-making could lead to a repetition of past mistakes.

“Most of the time, any kind of prediction work, machine-enabled or human-enabled, is going wrong,” says Martin Wählisch, associate professor of transformative technologies, innovation, and global affairs at the University of Birmingham. 

The representativeness of data is a major challenge for PeaceTech, says Wählisch, who founded his own startup in the space, Office for Dreams, which combines digital tools with creative strategies to facilitate decision-making. “The currency is the data inflow,” he says.

Last month, Wählisch joined an interdisciplinary group of technologists, researchers, and peacebuilders at the Stockholm Forum on Peace and Development to define a vision for AI use in large-scale deliberation processes. One system, built at Google’s DeepMind, uses large language models to assist with the mediation process itself. In experiments with more than 5,000 participants in the U.K., researchers found the system, named after the German social theorist Jürgen Habermas, outperformed untrained human mediators, with 56% of participants preferring AI-generated statements over human ones. The tool also increased group agreement by about 8 percentage points and incorporated minority views. However, the researchers noted, “AI-assisted deliberation is not without its risks. . . . Steps must be taken to ensure users are representative of the target population and are prepared to contribute in good faith.”

Still, many of these efforts are swimming upstream at a moment when defense startups are seeing increased focus and funding amid surging military budgets. According to Bloomberg, private investors have already spent around $790 million on defense this year. Compare that figure to the investing trend in the past two decades, when private equity spending on defense reached $1 billion in only five of those years.  

Private investment in PeaceTech is still nascent. Peacebuilding startups have traditionally been supported by government grants and donors, but these are harder to find now. The U.S. Agency for International Development’s Development Innovation Ventures, for instance, typically funded startups like Didi, until it was shuttered by the Trump administration. 

Didi’s angel investor, B Ventures Group, exclusively funds tech firms with peacebuilding applications. Other PeaceTech investors include Peaceinvest, which focuses on local, pro-peace projects, and Kluz Ventures, which runs the annual Kluz Prize for PeaceTech. Two years ago, Didi won a Kluz Prize, which came with a $20,000 cash award recognizing the company’s achievements in machine learning. 

“Peacebuilding has traditionally been seen as the domain of nonprofits and governments, not a space for venture capital,” Brian Abrams, founder and managing partner of B Ventures Group, wrote in a March essay. “At the same time, this type of opportunity has been associated with impact investing and lower returns, a trade-off many venture investors are unwilling to make. But PeaceTech challenges those assumptions, offering a model that prioritizes both profit and purpose.”

Pursuing profits means presenting PeaceTech as useful outside of conflict zones too, the way defense firms typically diversify their business with the sale of dual-use technologies. Palantir, for instance—known for the AI-powered data tools it sells to military and immigration authorities—also works for Fortune 500 companies and develops tools for humanitarian purposes. After its software was used to facilitate Ukrainian refugee assistance, the company was awarded a special distinction by the Kluz Prize for PeaceTech in 2023, the same year Didi won its award. 

“We need to expand the current dual-use framing of technology—civilian and military—to a triple-use paradigm that includes peace as a third pillar,” Artur Kluz, founder and CEO of Kluz Ventures, and Stefaan Verhulst, a research professor at New York University, wrote in a recent Fast Company op-ed. “This would mean structuring investments in a way that not only supports battlefield advantage and economic competitiveness, but also actively contributes to conflict prevention, mediation, and resolution.”

Abrams sees many commercial opportunities in Didi’s tool: Imagine a private equity firm using the Ripeness Index to time its mergers and acquisitions perfectly, or a public relations firm tuning its crisis management messaging just right. Recent estimates gauge the market size for public opinion and election polling at $8.93 billion in 2025. 

In any scenario, developers and entrepreneurs must be mindful about the use of personal data, says Abrams. “PeaceTech begins, I think, with Hippocratic guardrails. First, do no harm. Make sure the technology is contributing toward peace and not in any way being used for anything counterproductive,” he says. 

That concern is heightened by