Artificial Intelligence and Machine Learning, already used by 3 out of 10 Spanish companies for data management

Artificial Intelligence and Machine Learning continue to gain relevance in data management.Especially in the context of digital transformation, where more and more companies are aware of the value that these technologies bring. Since they allow you to boost efficiency and improve decision making, analyzing large volumes of information quickly and accurately.

In fact, it is estimated that approximately 36% of companies have already adopted Artificial Intelligence and Machine Learning, making them indispensable tools to process, analyze and obtain valuable knowledge. Which reflects the recognition of the importance of making the most of data to obtain competitive advantages.

The revolution of Artificial Intelligence and Machine Learning in the business world

This is according to an IDC report, which confirms that 60% of Spanish companies have a strategic plan for data management. Since it is a valuable asset for business growth and decision-making. Not to mention that more than half of this percentage implemented AI and ML technologies to streamline these processes.

A crucial measure to face the growing amount of data. Those that are generated from infrastructures rooted in digital processes, being crucial to have AI and ML applications. These two efficient solutions allow processing massive volumes of information. Without them, managing this overwhelming amount of data would be a considerable challenge.

Innovative Artificial Intelligence and Machine Learning solutions

It is precisely in this context, in which the EMPHASIS project arises, which has the participation of teams such as SEGULA Technologies. Its main objective is to implement Artificial Intelligence and Machine Learning technologies to “extract, understand and structure” data automatically. This is done through advanced algorithms that make the most of existing information.

Basically, efficiently manage processes that range from obtaining information, its classification and final treatment. This throughAI and Machine Learning technologies that allow this data to be transformed into useful information. Something that would affect both the company and commerce in general, making the most of potential patterns, trends and opportunities.

Addressing business incidents organically through AI and Machine Learning

Not to mention that EMPHASIS would be putting a high priority on security of the data. To achieve this, they implemented anonymized processing techniques, with the aim of increasing the degree of confidentiality of the documentation. So that the companies involved can provide peace of mind to both customers and employees, protecting privacy during processing.

In addition, the use of Artificial Intelligence and Machine Learning is proposed to automatically address a wide variety of problems. Since these technologies allow the early detection and resolution of business incidents. These range from technical problems, disruptions in supply chains and errors in computer systems. Likewise, minimizing downtime and improving customer satisfaction.

The promotion of Artificial Intelligence and Machine Learning within the business world

All this together translates into a much friendlier data management system for the user. At the same time, it has functionalities aimed at guaranteeing the confidentiality, security and analytical efficiency of the information. As revealed by Jorge Martínez, R&I Manager of SEGULA Technologies, who explains that it becomes an ecosystem with a friendlier and improved experience.

“The EMPHASIS project is completely innovative, as it provides multiple layers of management over technical support tools, without being limited to a specific ERP. “This makes it possible to address deficiencies in the existing software that customers use, filling gaps and improving its functionality in a personalized way.”

This shows why More and more companies decide to use Artificial Intelligence and Machine Learning to optimize your processes. Thus, they can be applied in a wide variety of areas, from supply chain management to the analysis of historical product data and even prediction of weather patterns. Hence, they become indispensable tools to improve efficiency and decision-making in various sectors.