Alexey Kuzovkin on innovative technologies in IT: application of machine learning and artificial intelligence in business

Alexey Viktorovich Kuzovkin is an IT entrepreneur, ex-Chairman of the Board of Directors of Armada Group. Alexey Viktorovich has tremendous experience in managing innovative and IT projects.

Artificial intelligence at its current stage is developing at an incredible pace. Every day more and more demonstrations of phenomenal technical achievements in the field of machine learning appear online. Its main feature is that the machine, or, to put it simply, AI, learns completely autonomously thanks to theoretical knowledge and even practical experience in performing specific tasks. For the sake of full understanding, it is worth clarifying that the definitions of machine learning, also called ML (Machine learning) and AI (Artificial Intelligence), do differ in some individual details. However, in the context of this review, this difference is too insignificant, so these terms can be used as synonyms, and we will not go too deep into the distinction between ML and AI.

The principle of machine learning is not much different from that of human learning, except that the machine learns hundreds, if not thousands, of times faster, not to mention the amount of work it is capable of realising in the shortest possible time. Of course, such advanced technology could in no way bypass the business sphere. Even now, many entrepreneurs use innovative IT developments to run their own business. Let us consider a few of the main areas in which information technology is used.

Creative sphere

This includes logo creation, slogan creation, product design and generally anything directly related to creative artwork. There are already a huge number of neural networks in the public domain, capable of creating thematic images even by textual request. A case when the studio of the famous Russian designer Artemy Lebedev actually sold AI works to clients is quite indicative. Of course, the developments of artificial intelligence were taken as a basis, and later small details were finalised by professional artists in order to give the final result a marketable appearance. Most likely, the demand for the use of neural network logos will only increase in the future.

What is ‘hyper-automisation’ and how will it affect business processes

This trend covers a fairly wide range of businesses. In brief, it is a concept through which companies are adopting advanced technologies to optimally automate multiple workflows. More specifically, hyper-automation refers to robotic process automation (RPA), low-cost coding application development platforms (LCAP), and artificial intelligence along with machine learning. According to research by Gartner, an international organisation specialising in the study of modern information technology, hyper-automation processes are the leading strategic technology in the 2020s.

Why is there such interest in this area? It’s simple – cheapness and speed. The classic implementation of IT has already simplified the work of enterprises in many ways, eliminating a huge number of now unnecessary processes and automating many procedures. A banal example: now there is no need to calculate the figures in the accounting report on your own or on a calculator, because it is enough just to enter them into Excel, 1C and other programmes, after which they will automatically carry out a significant part of lengthy calculations. This is just to give you an example.

On the other hand, even this kind of revolution still does not remove the need to manually carry out a large number of operations that can be easily automated with RPA. Companies around the world are expected to reduce so-called “operating costs” by more than 30% in 2024 due to the hyper-automation of many processes.

More specifically, ML and AI technologies will be able to greatly simplify the next set of tasks while minimising the associated costs:

1. Forecasting. On the basis of huge data arrays from open access, AI is sometimes as capable as an experienced analyst of determining trends in the development of the global economic market or a particular industry of an enterprise. Thus, the introduction of high technologies can significantly help in making the most important management decisions, making them more accurate and, most importantly, prompt.
2. logistics. Building the most efficient logistical paths for product delivery to the customer, cash flow, queue management and so on – all these are more than manageable tasks for advanced artificial intelligence.
3. Working with clients. Some online resources already offer the function of not just analysing a wide client base, but a real automated SMS mailing or even conducting full-fledged calls. So far, obviously, all this is only in the first stages of development, but at this rate, in a few years, instead of call centre employees, people may well start to be called by “neural networks”.

Why the problem of “job cuts” is a myth

Finally, let’s talk about the coming “crisis” that many workers are complaining about – the crowding out of people from the labour market. This problem is especially acute when it comes to programmers: say, the same ChatGPT is now able to write a full-fledged programme for free, so why do we need programmers on a permanent basis with huge salaries?

However, such alarmists do not take into account one rather important point: as old professions disappear, new ones always appear. Obviously, with the development of machine learning technologies, many existing professions will gradually begin to lose their relevance, but new ones are bound to emerge in their place. Not to mention that at the current stage, AI cannot fully replace an expert. No matter how accurate its conclusions, no matter how rationally it analyses information, it cannot take into account all possible nuances.

The banal “human factor” is commonly seen as the reason for the slowdown of progress and the main argument in favour of why artificial intelligence will now take over all jobs. In reality, however, this is very far from reality, at least in the near future. It’s not just about creative professions, because a robot will never replace a real experienced analyst, with a wealth of experience and the capacity for out-of-the-box thinking beyond the limits set by technical limitations. Employers favour “machines” because of lower costs and optimal speed, but the end result should not be forgotten.

As a result, we can say that ML and AI have incredible potential for full integration into the business sphere in all its manifestations. Despite this, it simply does not make sense to speculate on the absolute replacement of all human specialists, considering AI as a “competitor”. Artificial intelligence is primarily a tool for realising certain tasks. Yes, many of them will be automated, simplified, minimised, but even then, people capable of coping with this advanced tool will be needed.