Business moves from the use of universal sheabots to the construction of the concept of human teamwork and AI – Human-Agent Teams, where specialized AI-agents become full participants in operational processes. At the same time the main barThe riot for the effectiveness of artificial intelligence in companies is the disorder in corporate data and attempts to use universal models instead of deeply integrated tools. Oleg Shcherbatenko, the founder and CEO of IT-Enterprise, talks about how to build an effective partnership between man and AI.

According to the top manager, the availability of skills of a person with AI is finally transformed from an additional advantage to the basic demand of employers.  

‘In the coming years, the competitive unit will be not just a separate specialist, but a specialist with his own AI-competence. AI-agent is not a replacement for an employee, but an additional production capacity. A person formulates a task, controls quality and makes decisions, and the agent takes over the operational routine., – emphasizes Oleg Shcherbatenko, founder and CEO of IT-Enterprise. 

Transformations are confirmed by international research data. So according to the data PwC Global AI Jobs Barometer 2026, the number of vacancies that require specialized AI skills is growing almost 8 times faster than the market as a whole. And the average allowance to the salary for possession of AI-tools reached 62%. At the same time, according to Work Trend Index 2026, 66% of AI users have received more time for high-value tasks, and 58% perform tasks that were inaccessible to them a year ago (among advanced users – 80%). World Economic Forum (Future of Jobs Report 2025) calls AI and Big Data the fastest growing skills by 2030, and 86% of employers expect business transformations under the influence of these technologies.  

On the example of some developments AI-assistant factories IT-ENTERPRISE Oleg Shcherbatenko names practical scenarios for the use of AI-agents in business and highlights several key areas where the teamwork of man and Agent gives the highest result: 

1. HR and recruitment: AI-agents automatically process more than 100 types of documents (summaries, passports, diplomas, certificates) and enter data into the relevant ERP-system registers, accelerating the processing of applications almost to the online regime. 
2. Service Engineering: Manual Assistant Analyzes technical manuals and regulations of repair work, helps to form technological maps, assesses the condition of equipment and warns of the risks of stops. 
3. Procurement and jurisprudence: AI assistants analyze the tender documents, assess the probability of victory and prepare primary proposals. 
4. Production and energy management: AI agents monitor the operation of equipment around the clock, predict failures and optimize resource consumption. 

However, CEO IT-Enterprise emphasizes that universal public models (like Chatgpt) have a broad general outlook, but do not know the specifics of a particular company. To obtain a measurable business effect, a transition to the ERP + SHI architecture is needed, where specialized agents work with closed corporate knowledge bases, regulations and internal documentation 24/7.  

Oleg Shcherbatenko also warns: AI will not correct the lack of structure. If the information is scattered over Excel tables and local folders, the quality of AI will be low. The effectiveness of the agent directly depends on the quality of the information context provided by the company. 

As previously reported, IT-Enterprise, Gipanis manufacturing enterprise and Astar Sustainable Development Agency, EDIH Clotex Hub combined expertise within the European project Wasabi to Implement an AI assistant Directly in the production process of making shoes. The solution should help the footwear and light industry enterprises reduce production waste, control technological parameters and increase energy efficiency.