The expert assessed the implementation of artificial intelligence in Russian business

Russian business has passed only about 30% of the way to the mass implementation of artificial intelligence.

TTechnically, many companies are already ready, but mentally, they are not yet. This is how the deputy head of T1 AI (T1 IT holding) Sergei Karpovich assessed the level of AI maturity at the Data Fusion conference.

He noted that in order for AI to become a massive and effective tool, and not a showcase technology, businesses need to simultaneously advance in three directions. The first track is technological: built architecture, structured data and knowledge base. The second is the team’s readiness to work with new tools: we are talking not only about IT and Data Science specialists, but also about “line” management who are starting to use AI in applied tasks. The third vector is the reassembly of business processes, without which it is impossible to achieve a tangible effect from AI.

According to the expert, the market remains highly differentiated. Large banks, telecoms and oil and gas companies have already completed digital transformation or are at its final stage, have prepared a platform for the implementation of AI and are actively integrating machine learning into operational processes. It is much more difficult for small and medium-sized businesses that do not have a ready infrastructure and do not have a culture of working with data to enter the AI ​​agenda.

Speaking of barriers, Sergey Karpovich emphasized that the often mentioned shortage of computing power and lack of personnel are in some cases overestimated.

“If management understands that the company has no future without AI, resources are most often found: there are already LLM models that can be calculated on a single video card and do not require exorbitant budgets. And training specialists with the availability of modern tools is a solvable task,” said expert.

Much more seriously his According to him, challenges related to trust in AI and information security: in critical processes, errors can have sensitive consequences.

On the home stretch to wider adoption of AI, businesses will have to build multi-layered security systems and reconsider the principles of cyber protection in an environment where artificial intelligence becomes part of the core infrastructure of companies.