The warning from a Russian Academy of Sciences academician about the dangers of pursuing "bright flashes" of artificial intelligence reflects a fundamental shift in national-level perception of the technology. We are witnessing a complete transition from the phase of technological euphoria to the stage of pragmatic integration. In 2026, when generative models have already become part of infrastructure, it is critically important to recognize that blind implementation of neural networks without strategic vision leads not to progress, but to fragmentation of the digital landscape and loss of resources.
Hype-driven demand for AI tools often masks the absence of deep expertise. Without understanding architectural limitations and ethical risks, "quick wins" transform into long-term security and stability problems for corporate systems. The academician emphasizes the necessity of systematic activity: this means evaluating the real contribution of algorithms to economic competitiveness, not merely demonstrating capabilities. For the professional community, this signals that the era of experiments for experiments' sake is ending, giving way to demands for proven effectiveness.
The key conclusion becomes prioritizing qualitative transformation of processes over quantitative accumulation of tools. Russians need to focus on creating their own competencies, understanding the pros and cons of neural networks in the context of national tasks. Only such an approach will avoid technological dependency and ensure sustainable development, where AI serves not as an end in itself, but as an effective instrument for achieving specific economic and social indicators. Ignoring systematicity threatens the formation of "digital junk," which will hinder innovations instead of accelerating them.