---
title: "AI in Russia: Hype vs. Reality. Why 91% of Companies Are Not Ready to Implement Neural Networks"
description: "Russian business in 2026 turned out to be unprepared for the mass implementation of AI: the readiness index is only 38 out of 100. The main problems: 91% of companies lack the capacity to train neural networks, and 79% lack personnel. 📉🤖"
date: 2026-07-31T21:00:09.000Z
lang: en
url: https://xab.info/en/posts/ai-in-russia-hype-vs-reality-why-91-of-companies-are-not-ready-to-implement-neural-networks
tags: [orionsoft, artificial-intelligence, russian-business, gpu-shortage, digital-transformation]
publisher: "XAB.info"
---

# AI in Russia: Hype vs. Reality. Why 91% of Companies Are Not Ready to Implement Neural Networks

![AI specialist in server room: illustrating the gap between hype and reality of neural network adoption in Russia](https://xab.info/media/2026/07/31/ii-v-rossii-azhiotazh-protiv-realnosti-pochemu-91- kompaniy-ne-gotovy-k-vnedreniyu/ii-v-rossii-azhiotazh-protiv-realnosti-pochemu-91- kompaniy-ne-gotovy-k-vnedreniyu-1.webp)

Russian businesses are facing a paradox: high interest in artificial intelligence (AI) technologies is not backed by technical readiness for their implementation. Analysts at OrionSoft, summarizing the first half of 2026, recorded a critical gap between company ambitions and the actual state of their infrastructure.

The AI infrastructure readiness index for domestic organizations amounted to only 38 points out of 100. This figure indicates that most enterprises are still at the initial stage of creating the necessary conditions for working with neural networks.

### Crisis of Resources and Personnel

The study, which involved representatives of 100 Russian organizations (mostly large businesses), identified two key problems hindering digital transformation. The most acute issue is the personnel gap: 79% of the surveyed companies admitted that they are experiencing a severe shortage of artificial intelligence specialists.

However, the lack of people is only half the problem. A much more serious barrier turned out to be the lack of "hardware." According to the survey, 91% of participants do not have servers with graphics processing units (GPUs). Without this equipment, it is impossible to train modern models or fully launch them on an industrial scale.

### How Companies Are Adapting to Limitations

Despite the low readiness index and resource shortages, business does not stop. Companies continue to implement AI, trying to adapt to current conditions:

    - 28% of organizations are already implementing one or two pilot projects.

    - Another 21% of companies have reached the level of more than two launched initiatives.

    - About a third of respondents are still at the planning stage for launches.

Thus, although the mass transition to AI in Russia is being delayed due to infrastructure problems, the segment of companies already implementing technologies continues to form, operating under strict constraints.