The digital transformation has brought with it a new customer and consumer, characterized by being much more demanding and demanding digitized, personalized and agile services. This context has created in companies the need to automate their processes and this is when artificial intelligence comes into play. Although AI is currently only used by 11.8% of Spanish companies with more than ten employees, according to the latest Ontsi report, more and more companies are deciding to take the plunge and, in fact, in 2022 this percentage it was 3.5 points higher than the previous year. The irruption of this new technology, among many other benefits, allows companies to offer better services adapted to the new consumer, improve their efficiency in decision-making, increase their productivity and save on costs.
The consultancy atSistemas has gathered some of the barriers that companies are encountering when implementing this technology:
– Lack of knowledge. One of the main barriers that companies have to overcome to implement solutions based on artificial intelligence is the lack of knowledge and experience in the field. Being a highly specialized field and due to its high level of sophistication, it is not easy for companies to acquire the necessary talent to carry out demanding projects. In fact, as the latest study by the Industrial Association for the Promotion of the Data Economy and AI (IndesIA) points out, the lack of qualified professionals in Spanish companies will leave more than 6,500 job offers in data unfilled. and artificial intelligence in 2023.
– Confidence in your decisions. Systems based on artificial intelligence feed on data that is used for learning, training algorithms to build models that solve certain tasks. If the starting data is biased, the systems can generate unbalanced decisions in racial or gender terms, or present unfair inequalities and preferences. Also, as algorithms become more complex, transparency decreases and it can be difficult or even impossible to understand how decisions are made. Preserving the “explainability” of the models is key to maintaining confidence in decisions and allowing more responsible and safe use of AI systems.
– Privacy & Security. Although in 2021 the European Commission already presented a draft of a regulation on the use and development of artificial intelligence, it is currently still pending approval by the European Parliament and Council. However, the use of AI is already associated with the obligation to comply with the laws for the protection of confidential and sensitive data of both clients and employees of the company itself. Thus, the creation and subsequent maintenance of solutions based on artificial intelligence requires collecting a large amount of data that is used to design and evolve their models, so companies must respect that these data protection standards and regulations are complied with in their projects in two different ways: on the one hand, in the data used for the construction and evolution of the models themselves and, on the other hand, in the data used by the models when they are in a real productive environment, since the AI system it works as a super user that has almost unlimited access to a huge volume of data for treatment and decision making.
– Data availability. Most AI-based systems rely on vast amounts of data for their construction and maintenance. If data availability is limited, the patterns and relationships that allow systems to make accurate decisions cannot be found. Therefore, companies depend on the availability of said data, that it is of good quality and that it is stored correctly so that it does not suffer damage and that it continues to be useful, but also that it is possible to extract useful information from it. For this, it is important to know what the data is going to be needed for, how it is going to be exploited and related to each other, so that the information they offer improves the efficiency and competitiveness of companies.
– Necessary infrastructure. Not only the availability and quality of the data is crucial for the performance of the AI systems, but also the necessary infrastructure for its storage and processing. The construction of intelligent systems depends to a large extent on a powerful infrastructure that is capable of processing large volumes of data and, thanks to the advances in the fields of big data and dedicated computing hardware, it is possible to overcome the access barrier that makes a few years had the companies. Increasing cloud adoption lowers the cost required for both storage and processing, and more vendors are offering pre-built cloud-based AI products and solutions. In this way, companies have access to its benefits and can make use of it without having the necessary infrastructure on their own servers and without worrying excessively about the security and vulnerabilities of said infrastructure.
