How AI Will Change Software Development: Software Leaders Should Know


Artificial intelligence technology, which has developed since the 60s of the last century, has finally reached its peak – almost all trends in the development of information technology are related in some way or a other. For example, IDC presented in October of last year a forecast for the IT industry for 2021. Let’s try to show that artificial intelligence affects almost every point of this forecast. So, these are the trends, according to IDC analysts, that will determine the development of IT in 2021.

The computer legacy of the pandemic

The forced migration of users to home devices and computers, as well as to the use of cloud services, will be felt even before 2023. CIOs will continue to seek opportunities to build resilient and distributed digital infrastructures. However, managing geographically dispersed devices, controlling the applications that run on them, and transferring data between office applications, end users, and cloud services require sophisticated monitoring, management, and orchestration mechanisms. They are difficult to deliver without AI powered applications.

Later, AI began to refer to a number of algorithms and software systems, a distinguishing feature of which is the performance of certain tasks in the same way that a person thinking of their solution would.

The main properties of AI are the understanding of language, learning and the ability to think and, above all, to act.

AI solutions development company is a complex of related technologies and processes, efficiently and quickly, for example:

  • natural language processing;
  • machine learning;
  • expert systems;
  • virtual agents (chat bots and virtual assistants);
  • recommendation systems.

Move to stand-alone IT operations

IDC’s analysis showed that by 2023, all IT and automation initiatives are expected to be based on cloud ecosystems as an underlying framework that improves asset management and over-time analytics capabilities. real. The systems are said to be autonomous because they make their own decisions, but most of them use cloud-trained neural networks based on the analysis of the data they collect. Modern artificial intelligence technology allows us to separate the complex computational task of analyzing a large amount of data from the rapid decision-making system. In other words, big data collected in cloud services is processed using artificial intelligence methods and as a result rather compact and fast neural networks are obtained. They are the ones who make decisions in autonomous systems. However, for companies to use such a system of separation of processing and decision-making, they need to integrate their data warehouses with analytics systems based on artificial intelligence and deep machine learning.

The importance of natural intelligence

Business automation and the widespread adoption of artificial intelligence will not be complete without investing in building IT or DevOps teams that continuously monitor neural network activity, identify their incorrect or undermined behavior. -optimal and recycle models. Moreover, it will not be so much the universal IT specialists who will be important as the professionals of specific sectors. Read more information on DataScience UA.


Margie D. Carlisle