Artificial intelligence (AI) has arrived to revolutionize the world, being a technology that, although it has been with us for decades, is experiencing a current boom that has led it to undergo a great evolution, with diverse applications in countless areas. Its economic potential is indisputable, but in this era of energy efficiency and cost optimization and savings, the operating cost of its infrastructure must be kept in mind.
This technology allows us to improve and accelerate different processes, driving the advancement of society through increasingly advanced applications. However, all this has a cost, and each “prompt” that is generated and each response from these platforms costs a lot of money.
All of their applications have a high energy cost that can grow over time as AI becomes increasingly sophisticated. Furthermore, beyond this, everything that surrounds the world of artificial intelligence means having to face other important financial outlays related to the technology itself, at the hardware and software level, and in the human workforce itself.
The need to have high computational power for all the tasks inherent in the development and operation of AI also highlights the need to have increasingly powerful and efficient processors, which are also increasingly scarce, therefore the growing boom in AI development also collaterally makes the entire manufacturing and supply chain of semiconductors, graphics cards and specialized hardware more expensive.
On the other hand, it has obvious costs derived from the very existence of data, since, in order to be trained, this technology requires data that it will later use to reach operational conclusions, and all of this implies a series of preparation costs.
Before talking in greater depth about the different types of AI costs, it is worth keeping in mind that, although these are high as a whole, this does not mean that they are not worth the investment, since, as we have seen in In recent months, this technology can help us automate a large number of tasks, which can lead to interesting profitability in the medium-long term. Additionally, as technology evolves, it is expected to become more efficient and economical.
Types of AI costs
The costs of artificial intelligence arise in various areas, starting with those related to data recovery and cleaning, as it is important to obtain and purify the information so that it is of quality, and continuing with the hardware, software and infrastructure, since that it is necessary to have powerful hardware that allows training AI models, to which we must add the energy costs and the maintenance of these systems.
The budget must also consider personnel expenses, as data scientists, machine learning engineers or AI researchers are necessary, as well as those related to the training of personnel to master this technology. It also involves costs in cloud services, which are used by many companies for their artificial intelligence models, and research and development expenses, which are necessary to investigate new techniques, algorithms and applications.
In addition to adding the additional costs derived from legal and ethical compliance with the technology, especially when some type of infringement occurs, we must take into account all those that are directly related to training, such as its high energy demand.
