Artificial Intelligence (AI) is revolutionizing the way companies operate and set their course worldwide. 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 risks, and improve their results. The application of this technology across multiple areas not only improves the efficiency and effectiveness of operations but also strengthens governance by providing a more accurate and real-time view of the company's status, enabling a quick response to potential issues.
Meanwhile, taking AI from theory and putting it into practice, combined with other methods and technologies to enhance efficiency, requires strategy and knowledge. When we talk about optimization in the operational area, there are countless processes and two clear paths: the first is pure and simple automation, through Robotic Process Automation (RPA) tools – technology that uses software robots to automate repetitive and manual tasks performed by humans in business systems.
The other approach deals with identifying the processes and whether the best practices are truly being adopted. All this mapping and questioning within a market benchmark is very important, and in this action, AI can assist considerably by predictively indicating which steps are optimized and which ones 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 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). Add to that real-time analyses around fraud, risk management, and sentiment analysis.
Nothing beats practical examples to illustrate what we are dealing with here. In the industry, AI can positively impact the operation of all machinery by analyzing sensor data and indicating preventive maintenance, preventing activity stoppages. For banks and insurance companies, behavioral patterns can assist in identifying fraud in financial and claim requests.
Furthermore, AI can contribute significantly to the automation of client 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 a company's process is, the less the impact of operational deficiency. This is because automation is capable of catching the error and reprocessing, which would be an ideal scenario. If the amount of rework is not significant or the time spent on it is small, we have an acceptable deficiency; however, it is important to assess the maturity level of each organization.
In the same vein, it is worth emphasizing that AI or technology do not have the power to question and criticize. The machine learns what it is taught, but there are situations involving bias or ethics alongside algorithms, and it is in these cases that the human factor becomes essential. There must always be someone capable of observing, redirecting, and providing feedback to the technology tools, so ongoing training and capacity building cannot be minimized.
From the factory floor to IT departments, operational efficiency with AI and machine learning, to name just two possible technologies, is essential in a highly competitive environment with increasingly demanding customers for personalized deliveries. With better decision-making, increased efficiency, and optimized costs, we have a complete ecosystem close to the highest returns sought by any and all businesses. But, to achieve this result, understanding the processes, measuring, automating, and having structured governance in place are essential.
