In his day, scientist and researcher Arend Hintze established a formula for a machine, a robot, to have the ability to learn on its own, considering that it should follow the same learning process as a human. He based it on reactive machines, their reaction to unique events based on real-world perception. In limited memories with the ability to retain information for a limited period of time. In theory of mind, that is, the ability to imitate a human mental model that can understand emotions, thoughts, and interact directly with humans, and the ability to make decisions to the same extent as the human mind, but through machines, and in self-awareness, in a system capable of being conscious by itself.
Currently, AI is applied in numerous fields such as healthcare, education, marketing, businesses, and human resources. Let’s focus on the advantages and disadvantages of its application in the company.
Advantages and disadvantages of AI applied to the company
The implementation of AI in companies has not only increased machine and robot productivity but also increased worker productivity and the quality of their work. However, to properly incorporate AI into the company with the aim of obtaining proper data exploitation, all current processes of the company must first be analyzed, starting from the ground up, until data modeling and interpretable AI are achieved.
The study requires:
Knowing how to measure the current level of digitization of the company and studying all existing processes and repositories. Describing the information detailed in the current dashboard.
Optimizing the present with better prediction, automation, and process optimization. Integrating all existing data systems.
Changing the future by modeling the system and achieving interpretable AI, that is, data exploitation.
Process Automation: Its first objective is to implement solutions to reduce costs in order to increase customer service. Secondly, it increases productivity as the company’s technology grows, transforming productivity.
Empowers creative tasks: AI allows people to free themselves from routine and repetitive tasks, allowing them to spend more time on creative activities. It also helps prevent delays, fosters competitiveness, provides experience, harnesses human talent, stimulates communication, keeps the mind active, among others.
Provides accuracy: It has the ability to provide higher accuracy than humans in decision-making.
Reduction of human error: Thanks to the application of AI, failures caused by human limitations can be reduced. AI is used in some production chains to detect defects in parts that cannot be detected by human vision, using infrared sensors.
Reduction of employees’ time spent on data analysis: Since the system is automated, it allows for the analysis and utilization of production-derived data to be done quickly and in less time.
Predictive maintenance: It is the optimal way to perform machinery checks and maintenance. This is based on conditions and operating time to increase performance and lifecycle.
Improvements in production levels and decision-making: Having more structured information allows for more efficient and quick decision-making.
Optimization and Control of Production Processes: Through AI, more efficient and error-free processes are achieved to gain greater control over a company’s production line.
Increased Productivity: AI intervenes in both machinery productivity and workers’ productivity in the quality of their work. This is because they have access to more information, allowing them to have a more focused vision for making better decisions.
Disadvantages of AI in the company:
Cost and implementation time: The cost of implementing this type of technology is a significant factor. Most companies are not yet familiar with AI and lack sufficient internal skills. Implementing AI requires a detailed study and the involvement of qualified professionals.
Data availability: Data management is presented in isolation within the company. This means that the information is not integrated, with each application in the company having its own data and separate storage. Therefore, linking systems is vital for proper data exploitation.
Lack of trained professionals: To implement AI systems, companies need expert personnel who have a global understanding of the company’s business and can serve as a proper liaison and partner in the implementation and maintenance of the provided solution.
At Ebantic, we provide qualified functional and technical consulting services for the study and application of the data exploitation model in the company. We act from the tasks of digitization, integration, data modeling, and exploitation.