Do you know what an AI algorithm is? They are capable of recognizing patterns in data and enabling computational systems to learn from them! Understand how your company can benefit!
According to McKinsey, organizations that implemented marketing personalization algorithms experienced a 20% increase in sales. According to Deloitte, the results of advertising campaigns improved by up to 30% when using algorithms for planning, monitoring, and correcting processes during execution.
For McKinsey, the use of artificial intelligence algorithms helped reduce churn rates by up to 25% and increase revenue from customer bases by 20%.
Investments in artificial intelligence are reaching increasingly higher levels, and there is an explanation for this: the ability of the company to accelerate its operations, analyses, and base decisions.
Is your company on the list of those that have already begun the movement of adopting and using AI intelligently? In today’s article, we explain what an AI algorithm is, what their role is in strategic decision-making, and how your company can achieve results never seen before through this technology. Follow along!
What is an AI algorithm and its importance?
AI algorithms are sequences of commands that a computer uses to perform a task. These codes are designed to follow a logical order, identify patterns in data, and learn from them to make decisions or take specific actions, which can also be known as machine learning.
The importance of algorithms lies in their ability to process and analyze massive volumes of data and identify trends that would be difficult to detect manually. Not only that, but they also train systems and machines to automate complex and repetitive tasks.
Practical applications of AI algorithms in different sectors
Due to their ability to process large volumes of data and identify complex patterns, artificial intelligence algorithms have been applied in different business areas.
In agriculture, for example, they are being used to improve efficiency and productivity in the field through agricultural robotics, crop monitoring, and predictive analysis. Additionally, they are facilitating property management, providing relevant insights to farmers based on images.
In the automotive sector, algorithms are being applied from production to infotainment delivery. Process optimization on the assembly line, precise identification of faults and defects, mass analysis in asset management, and manufacturing of more logical and automated automobiles. These are just a few of the applications.
In logistics and retail, algorithms are transforming how companies serve their customers by delivering specific product recommendations, personalized offers, and targeted content. Moreover, they are also contributing to demand forecasting, inventory management, and greater transparency in supply chains.
In the healthcare sector, AI algorithms are able to identify patterns that aid in medical diagnoses and the creation of innovative treatment methods. AI-powered robots and surgical systems are also being applied inside operating rooms to assist surgeons in critical procedures.
The financial sector is also benefiting from the application of artificial intelligence algorithms. They are playing a role in detecting fraud and suspicious account activities and also assisting in delivering more personalized and agile banking services through the use of virtual assistants.
According to a report published by Goldman Sachs, investments in artificial intelligence are expected to reach $200 billion by 2025, globally. Due to the rise of corporate AI, Gartner predicts that AI will be responsible for 20% of the global workforce and 40% of all economic productivity by 2028.
The role of data management in the efficient use of AI algorithms
For AI algorithms to learn and identify patterns from data, they need to be fed with as much information as possible.
It is important to understand, however, that the amount of data is not the only determining factor for the company to achieve efficient use of artificial intelligence algorithms. The data used in training needs to be of high quality, accessible, secure, and compliant with major regulations.
Therefore, the primary concern of companies needs to be optimizing the management of their own data. Steps such as collection, storage, maintenance, and processing need to be performed correctly and with maximum agility. Not only that, the company needs to have talented individuals capable of analyzing data to generate useful insights.
From the processes of collection, storage, maintenance, and processing, data can have machine learning applied to it. But just as data management is important, managing ML models is also necessary to:
- Ensure that training data is of high quality;
- Protect models and the data used to train them;
- Ensure that models have clear and transparent explainability;
- Ensure that models are developed and used in accordance with ethical, legal, and regulatory standards.
How to ensure decision-making with the right tools
The need and importance of implementing a data-driven culture have motivated many software vendors to develop robust solutions to manage data and simplify analyses.
These solutions are decisive within corporate environments that want to benefit from information or train machines and systems through artificial intelligence to perform repetitive tasks.
A study developed by McKinsey shows that the way data is analyzed and processed will change by 2025. The support of artificial intelligence will become a key factor for the efficient use of data, prompting teams to become less operational and more strategic.
Engineering, knowing that the fusion of data and AI drives business growth, has developed a solution focused on transforming raw data into intelligent decisions: DHuO Data!
With DHuO Data, companies can collect data, prepare it for analysis, create machine learning models, and achieve powerful insights from the data. The future belongs to companies that innovate today. Elevate your decision-making potential with artificial intelligence and get ahead.