The ongoing transformation of global energy systems—accelerated by climate concerns, geopolitical shifts, and technological breakthroughs—demands an equally adaptive approach to diplomacy. Amid this flux, artificial intelligence (AI), particularly generative models, is emerging not as a supporting act, but as a potentially game-changing force. Energy diplomacy, traditionally shaped by statecraft and strategy, is beginning to feel the quiet push of data, models, and algorithms. The rise of generative AI may very well rewrite how negotiations unfold, how energy transitions are understood, and how the global energy map is drawn.
Energy diplomacy, as Michael T. Klare pointed out in The Race for What’s Left, has always been a complex terrain where political ambition and resource security intertwine. Historically, diplomatic efforts revolved around securing fossil fuel access or navigating pipeline politics. However, with the global push toward renewables, the language of diplomacy is changing. Now it’s about securing critical minerals, harmonizing green tech policies, and managing the vulnerabilities of a distributed energy infrastructure. In this shifting context, generative AI offers capabilities that traditional diplomatic tools can’t match—especially when it comes to synthesizing massive datasets, simulating negotiation scenarios, or crafting tailored policy briefs within seconds.
Consider the example of policy forecasting. In The Grid, Gretchen Bakke explores how outdated infrastructure is colliding with new demands for decentralized energy. Generative models can assist policymakers by building scenario-based narratives, each grounded in a unique blend of technical and geopolitical variables. These narratives aren’t just numbers and charts; they can be written as hypothetical memos, diplomatic cables, or even press briefings—making them instantly accessible to decision-makers under pressure. This doesn’t replace strategic thinking, but it makes it more nimble, more responsive to real-time complexity.
And it’s not just government agencies that stand to benefit. Multilateral platforms like the International Energy Agency (IEA) or OPEC+, which often struggle to align vastly different national interests, could use AI-generated simulations to predict negotiation bottlenecks or possible compromises before talks even begin. Daniel Yergin’s The New Map captures the ever-evolving geopolitical contours shaped by energy shifts. AI can help visualize those contours—not as static maps but as dynamic, evolving conversations among actors with competing interests.
This isn’t to say AI models are flawless prophets. Far from it. As Kate Crawford argues in Atlas of AI, the infrastructure of AI is neither neutral nor immaterial. Generative models reflect the assumptions baked into their training data. In energy diplomacy, where national narratives and historical grievances run deep, context matters. An AI model trained solely on Western perspectives might misread or oversimplify the stakes in, say, a China-Africa energy deal or a Middle Eastern hydrogen alliance. But here’s the twist: if trained carefully—on multilateral treaties, non-Western news media, indigenous energy governance practices—these models could reflect a fuller picture, one that acknowledges the diversity of interests on the global energy stage.
Moreover, energy diplomacy doesn’t unfold in neat press releases or formal negotiations. Much of it lives in grey areas—think soft power initiatives, joint research partnerships, or even academic exchanges. In The Geopolitics of Renewable Energy, Daniel Scholten highlights how soft influence will matter more as countries compete to set the rules around green technologies. Generative AI can assist here too, drafting cultural exchange proposals, simulating public diplomacy campaigns, or generating localized communication strategies for stakeholder engagement. These outputs don’t need to be perfect—they just need to be good enough to start conversations, seed ideas, or prepare diplomats before they step into the room.
One might be tempted to ask: why now? What’s changed to make AI suddenly relevant to energy diplomacy? A few things, actually. First, the energy transition is no longer a slow, marginal process. As Vaclav Smil notes in Energy and Civilization, societies do not change energy systems overnight—but the pressure to accelerate this shift is unlike anything seen before. With timelines collapsing, there’s little room for trial and error. Generative models can compress what used to be multi-week research into minutes, offering a degree of foresight that’s increasingly essential.
Second, the diplomatic toolkit is expanding. In Artificial Intelligence and International Politics, Valentin Schatz and Nikolas Glover explain how AI technologies are pushing the boundaries of what counts as “diplomatic labor.” Today, diplomats are expected to engage not just with their counterparts, but with tech companies, climate scientists, and energy entrepreneurs. Generative AI can help bridge these disparate worlds by translating technical documents into lay terms or by simulating conversations across different stakeholder groups. Think of it as a multilingual, multidisciplinary assistant that doesn’t get tired or overwhelmed by jargon.
But the real value may lie in storytelling. As Rob Nixon argues in Slow Violence and the Environmentalism of the Poor, many of the most pressing energy conflicts are invisible—playing out over decades, often in the Global South, far from media attention. AI-generated narratives can shine a light on these long-term injustices. Whether it’s a simulated report on the impact of lithium mining in Bolivia or a fictionalized news article from a post-oil Gulf state in 2035, generative models can make abstract futures feel concrete. They can reframe debates not by adding noise, but by helping actors see what’s at stake in ways that data tables alone cannot capture.
Of course, there’s a risk of manipulation. In Weapons of Math Destruction, Cathy O’Neil warns about the seductive power of algorithms that appear objective but perpetuate bias. In diplomacy, the stakes are too high to blindly trust machines. The challenge, then, is to treat generative models not as oracles but as tools—extensions of human judgment, not replacements for it. This balance requires what Shoshana Zuboff, in The Age of Surveillance Capitalism, calls epistemic vigilance. Those who deploy these models must understand not just what they do, but how they do it—and what they leave out.
There’s also the issue of access. In Technological Sovereignty, Silvia Rivera Cusicanqui writes about the unequal distribution of tech resources and knowledge. If only a few powerful countries or corporations control the most advanced AI tools, the diplomacy they enable may reinforce existing hierarchies rather than dismantle them. To avoid this, energy diplomacy in the age of AI must also be about building technological commons—open-source models, transparent data repositories, and collaborative AI governance structures.
Still, the possibilities are hard to ignore. In Powering the Future, Robert Laughlin envisions a world where energy abundance reshapes geopolitics in unexpected ways. Generative AI could help us anticipate those surprises—not perfectly, but better than we can alone. Whether it’s mapping new supply chains for rare earth elements or sketching out what a post-carbon alliance between South Asia and the Middle East might look like, these tools can stretch the diplomatic imagination.
That’s the key: imagination. Energy diplomacy has always been about reading the world differently—about spotting patterns others miss or proposing deals others think impossible. AI, when used thoughtfully, can sharpen that vision. It can speed up analysis, widen perspectives, and help stakeholders communicate in new ways. But it can’t replace judgment, values, or the messy business of trust-building. As Adam Tooze reflects in Crashed, crisis moments are often when institutions learn—or fail to. The current energy transition is a kind of slow-motion crisis, unfolding unevenly but urgently. Generative AI won’t save us from it, but it might help us navigate it a little more wisely.
In the end, the question isn’t whether AI will shape the future of energy diplomacy—it already is. The question is who gets to shape the AI, and to what end. That’s a diplomatic challenge in its own right, and one that needs more than just data. It needs political courage, ethical reflection, and yes, the occasional algorithm that knows how to write a decent memo.
