According to the survey, 44% of companies use artificial intelligence
Posted: Mon Jan 20, 2025 8:00 am
his result was shown by the State of DevOps Russia 2024 study, which was conducted by the Express 42 team with the strategic support of Deckhouse together with Yandex Cloud, HeadHunter, Avito Tech, T-Bank, JUG Ru Group and OTUS. It was conducted in the form of a survey, in which more than 4,000 IT specialists from Russian companies took part.
(AI) in software development and testing. AI tools are most actively used to automate code testing, identify data anomalies, manage system configurations and incidents. 47% of respondents noted the positive impact of AI on the efficiency of processes related to software development and testing.
Dmitry Svalov, Technical south korea whatsapp resource Director of BSS LLC, believes that this result is justified and even somewhat understated: "This assessment seems quite justified, given the current trends in the industry. AI tools are being actively implemented to automate routine tasks and improve the efficiency of software development and operation. It is worth noting that the actual percentage of AI use, primarily in testing, may be even higher, since employees often use AI on their own initiative to solve work tasks, which is not always reflected in official studies."
David Martirosov, CEO of Basis LLC, sees a trend that AI will be able not only to refine and check, but also to write software code, albeit simple at first: "In the future, the role of such assistants will grow, and they will be able to fully compete with developers. Similar trends exist in the operation of existing information systems, where IT specialists perform a clear set of functions, some of which can already be taken over by AI. In the future, we will see similar trends in other areas - for example, in industry, where AI can and is already taking control of production quality, etc. The limiting factor is the difficulty of access to specialized equipment for working with neural networks and AI. At the same time, it is important how the issue of access to specialized equipment for working with AI will be resolved: so far, Western countries are leading in this area, but Chinese partners are already offering similar products. There is hope that Russia will also not stand aside and will present domestic hardware solutions, which will give a significant boost to the country's digitalization."
Head of the .NET department at ICL Services Ibrahim Gabidullin compared the use of AI for DevOps tasks to delegating tasks from experienced to junior employees: "As practice shows, some tasks are simplified and accelerated, but at the same time time is spent on reviewing what the AI has done. For example, this can be compared to when a manager assigns a task to a Junior employee, and a Senior employee checks and edits this task after the Junior. In general, this approach saves about 30% of the Senior employee's time. Part of DevOps tasks is the development of scripts, and this is where all kinds of GPT neural networks come to the rescue."
(AI) in software development and testing. AI tools are most actively used to automate code testing, identify data anomalies, manage system configurations and incidents. 47% of respondents noted the positive impact of AI on the efficiency of processes related to software development and testing.
Dmitry Svalov, Technical south korea whatsapp resource Director of BSS LLC, believes that this result is justified and even somewhat understated: "This assessment seems quite justified, given the current trends in the industry. AI tools are being actively implemented to automate routine tasks and improve the efficiency of software development and operation. It is worth noting that the actual percentage of AI use, primarily in testing, may be even higher, since employees often use AI on their own initiative to solve work tasks, which is not always reflected in official studies."
David Martirosov, CEO of Basis LLC, sees a trend that AI will be able not only to refine and check, but also to write software code, albeit simple at first: "In the future, the role of such assistants will grow, and they will be able to fully compete with developers. Similar trends exist in the operation of existing information systems, where IT specialists perform a clear set of functions, some of which can already be taken over by AI. In the future, we will see similar trends in other areas - for example, in industry, where AI can and is already taking control of production quality, etc. The limiting factor is the difficulty of access to specialized equipment for working with neural networks and AI. At the same time, it is important how the issue of access to specialized equipment for working with AI will be resolved: so far, Western countries are leading in this area, but Chinese partners are already offering similar products. There is hope that Russia will also not stand aside and will present domestic hardware solutions, which will give a significant boost to the country's digitalization."
Head of the .NET department at ICL Services Ibrahim Gabidullin compared the use of AI for DevOps tasks to delegating tasks from experienced to junior employees: "As practice shows, some tasks are simplified and accelerated, but at the same time time is spent on reviewing what the AI has done. For example, this can be compared to when a manager assigns a task to a Junior employee, and a Senior employee checks and edits this task after the Junior. In general, this approach saves about 30% of the Senior employee's time. Part of DevOps tasks is the development of scripts, and this is where all kinds of GPT neural networks come to the rescue."