Rushing or Dragging?
Continuing the Yakutsk notes: how does the Russian Arctic develop its AI?
NORTHERN SUSTAINABLE DEVELOPMENT FORUM 2026Series · 2 posts
- A Flipped Map, Wildfire Math, and Regional Ties
- Rushing or Dragging?
One of the thematic directions of the Northern Sustainable Development Forum in Yakutsk was the development of artificial intelligence. However, the current tempo of development seems a bit off, or rather, syncopated.
Generally, we understand that by now some of the main use cases for AI are agentic development, orchestration, and running smaller models on autonomous infrastructure. For the Arctic, this is not a fashion statement. Agents can take over whole chains of work, not just single documents, and small models can run locally—at a remote clinic, a mine, or a weather station—where the internet connection is weak or absent. Does the Russian Arctic implement these innovations, and if so, how?
The Plenary Session: Combating Red Tape and the Mundane
The plenary session brought together the head of Yakutia, Aisen Nikolaev; Ambassador Anton Vasiliev; Irina Gekht, governor of the Nenets Autonomous Okrug and chair of the Northern Forum; Sakhamin Afanasyev, deputy chair of the Federation Council Committee on Federal Structure, Regional Policy, Local Self-Government, and Northern Affairs; Sergey Karaganov, academic supervisor of the Siberization of Russia: Turn to the East 2.0 project; Anatoly Semenov, deputy chair of the government of Yakutia; Vladimir Vasiliev, executive director of the Northern Forum; and Anatoly Nikolaev, rector of the North-Eastern Federal University.
The moderator questioned each and every one of them about AI. Curiously, the participants mostly hope that AI will take care of the mundane tasks, leaving more time for the tough ones.
Irina Gekht said that they use AI for bureaucratic purposes: to draft documents and transcribe meetings. Other participants also noted that this is one of the biggest prospects for AI, as it will free up time for the purpose of agreements, not the paperwork.
A poll was also running for the session’s audience. Most answers confirmed the obvious: people—Arctic experts—generally use Russian AI chatbots or foreign models like ChatGPT, Perplexity, Gemini, and Claude. And the uses stop there: working with documents and the like.
Despite the good efforts, one would estimate a certain drag here, a year or so behind the pace of AI development. David Heinemeier Hansson, the creator of Ruby on Rails, dates the turning point precisely: “On November 24th, 2025, we got the ‘Kodak Brownie’ of our era. We got Opus 4.5.” Since then, agents have been writing, testing, and fixing software with little human direction; his company, 37signals, has stopped writing code by hand altogether. Drafting documents and transcribing meetings belong to the era before that turning point. Nobody at the session even mentioned the newer trends.
As for applications in education and medicine, everyone said they have a lot of potential, but the work seems a bit undirected and scattered. There aren’t many projects to show for it right now. Aisen Nikolaev did point to some: AI is already being introduced in the republic’s medical organizations, including the oncology center, though in what way remains unclear. The more distinctive project is linguistic. The artificial intelligence laboratory at the North-Eastern Federal University is developing technology that can interact with users in the Yakut language, which would expand its presence in the digital space.
Climate Action
The tech-savvy climate section, Climate Regulation in Russia 2026: New Rules of the Game for the Arctic, which I covered earlier, showed more empirical results: a decrease in fires in Siberia. This seems to be one of the most profitable investment prospects for the Republic of Sakha (Yakutia). The biggest prospect of all—autonomous, full-cycle Arctic settlements, where AI runs the buildings, energy, and supply—is a nice dream to have, but even here it was not addressed directly. You hear “AI will help with this” and “it will allow us to do that,” but one does not feel the real contours of it all.
Smoke-detecting AI on cameras lets the republic catch wildfires very quickly and act on them, and thus earn invaluable carbon units, which in turn pay for more AI and cameras. This is a very nice cycle to have.
Rushing and Dragging at Once
So, are we rushing or dragging? In the end, AI development in the Russian Arctic is a bit of both—syncopated, with the accents falling where one would not expect them: on paperwork and wildfires rather than on medicine and education. Officials successfully use AI to tackle red tape—some nice news to hear—but everything else remains in a bit of a fog, with no clear direction.
The forum, like other Arctic events, is still feeling out the path. The talk rushes ahead: everyone wants AI in education and medicine. But before it can be applied there, someone has to find a good use for it, and that work has barely begun. Meanwhile, what AI could already do for the humanities and political studies of the Arctic, such as analyzing empirical data, remains mostly untouched. Beyond the paperwork, implementation is dragging.
Wildfires are the exception. There, the technology already works, and it might improve climate action in the region immensely.
