Survey: 65% of Companies See Gap Between Management's AI Requests and Infrastructure Readiness

K2 NeuroTech surveyed 100 corporate companies and found that 65% see a notable gap between top management's AI expectations and actual capabilities. 56% assess their data landscapes as partially or not ready for new regulations, and 52% say current IT infrastructure requires major modernization or hasn't been evaluated for AI loads. 28% have not conducted load planning for AI scenarios, and 45% gauge AI management effectiveness qualitatively or by feel. According to Vyacheslav Degtyarev, head of product solution development at K2 NeuroTech, up to 70% of AI experiments never reach stable industrial operation due to lagging infrastructure. Companies are addressing deficits with hybrid models: 62% are oriented toward hybrid architecture, 31% already use hybrid for AI training and inference, and 31% consider it strategically optimal. 21% say insufficient capacity is the main limitation. On cybersecurity, 79% of employees use public AI services at work, but only 29% have implemented real controls and security policies. 38% of corporations have internal AI development teams, but in 75% of cases these processes do not fully comply with MLSecOps standards. Alexander Lysenko, leading expert in development security and AI at K2 Cybersecurity, stated that AI is now a business continuity component, and 25% of companies consider AI security among their top-5 priorities.