According to many experts, the implementation of artificial intelligence in Russian enterprises would proceed much faster if it were not for objective difficulties.
Over 50% of companies consider artificial intelligence technologies to be the most promising, according to the latest data.
First of all, enterprise managers are interested in data analytics. In addition, they are interested in human resource management, quality control, customer service, sales and marketing.
If we talk about use specifically in the agricultural sector, then machine vision technology is very promising, which allows you to see what is happening in the fields right now, and it is AI that evaluates what is happening in the camera, which allows you not to waste human resources.
Digital analytical models are also used to calculate the structure of crop areas, digital twins of fields are used. And this is not all, because there are dozens of AI technologies that have great potential for implementation in agriculture.
However, today there are several problems at once that prevent the implementation of AI technologies in the activities of companies.
— Lack of specialists who could successfully carry out digitalization.
The personnel issue as a whole remains one of the most acute in Russia today, while the implementation of artificial intelligence requires special knowledge and skills that only a few possess. P
The appearance of a large number of qualified personnel on the labor market could accelerate the digitalization process many times over.
“Both business and the government have already recognized this problem, and now there is a discussion on how to solve it in the best possible way.
Individual companies that can afford investments in this area are working independently to resolve the situation. For example, the Steppe agroholding is very actively recruiting specialists, offering competitive working conditions and interesting tasks,” says Andrey Neduzhko, CEO of the Steppe agroholding.
— Lack of mature domestic solutions. Many managers would be happy to implement AI technologies, but they believe that the products offered by developer companies are still quite “raw” and are not capable of bringing real benefits.
Sales of software products to new buyers in the agro-industrial complex are also held back by the fact that most often sellers cannot provide relevant cases that would allow us to see what tasks specific companies have managed to solve and what results they have achieved.
But there is hope that such cases will appear as the market develops.
