Artificial Intelligence (AI) is revolutionizing the way companies operate and define their directions around the world. Its ability to process large volumes of data quickly and identify complex patterns makes it a powerful tool for detecting operational and governance deficiencies, making organizations more efficient, competitive and resilient.
By leveraging AI capabilities, companies can make smarter decisions, reduce risk and improve their bottom line.The application of this technology in multiple areas not only improves efficiency and effectiveness of operations, but also strengthens governance by providing a more accurate, real-time view of the state of the enterprise, enabling a rapid response to potential problems.
However, taking AI from theory and putting it into practice, associated with other methods and technologies in favor of efficiency, demands strategy and knowledge. When we talk about optimization in the operational area, there are numerous processes and two clear paths: the first is that of pure and simple automation, through Robotic Process Automation tools (RPA, in the acronym in English) & technology that uses software robots to automate repetitive and manual tasks, performed by humans in business systems.
The other way is about identifying processes and if best practices are actually being adopted. All this mapping and questioning within a market benchmark is very important, and in this action AI can help considerably, pointing in a predictive way which steps are optimized and which are those that do not generate adequate value, comparing with companies in the same sector, preventing failures and suggesting improvements around bottlenecks and workflows.
The positive impact to combat operational deficiencies with AI also involves automating repetitive tasks (AI frees up professionals to focus on activities that require more creativity and analysis) and reducing errors (task automation reduces the possibility of human errors, increasing process accuracy).
In industry, AI can positively impact the functioning of the entire machinery, analyzing sensor data and indicating preventive maintenance, avoiding the stoppage of activities.For banks and insurers, behavior patterns can help in identifying fraud in financial and indemnity requests.
In addition, AI can contribute significantly to the automation of customer projects, standardizing interpretations according to established parameters, bringing more personalized results, with greater efficiency, cost reduction and satisfaction.
We can conclude, in this way, that the more automated the process of a company, the smaller the impact of operational deficiency. This is because automation is able to catch the error and reprocess, in what would be an ideal scenario. If the volume of rework is not considerable or the time for this is small, we have a deficiency even acceptable, but it is important to assess the degree of maturity of each organization.
In this same sense, it is worth mentioning that AI or technology does not have the power to question and criticize. The machine learns what it is taught, but there are situations that involve bias or ethics with the algorithms, and that is where the human factor imposes itself as fundamental. It is necessary to always have someone able to look, redirect and give feedback to the technology tools, so constant training and training can not be minimized.
From the factory floor to the IT sectors, operational efficiency with AI and machine learning, to name just two possible technologies, is essential in an environment of strong competition and increasingly demanding customers for personalized deliveries. With better decision making, more efficiency and optimized costs, we have an ecosystem that is intact and close to the highest returns desired by any business. But to achieve this result, understanding the processes, measuring, automating and having a structured governance present is essential.