Artificial intelligence, especially machine learning in companies, will become the most influential technology to transform industries and areas that are already in the focus of digitization from scratch. With the proliferation of the Internet, the growing online presence and connected devices that generate a huge flood of digital information, companies are increasingly relying on algorithms to solve otherwise far-reaching problems with good guarantees of a solution. Data is the accelerator for our information society. Therefore, new technologies and machine learning techniques are the key to dealing with the new wealth of information in complex contexts.
Machine Learning - what is that?
But what is machine learning? Machine Learning as a branch of Artificial Intelligence (AI) uses algorithms and models that allow computers to perform tasks without explicit instructions. As a result, statements can be made based on human learning abilities, which help the system to automatically improve through this experience and provide accurate output based on new information. Put simply, Machine Learning finds answers to business-related problems. It is a data analysis process that uses algorithms to learn iteratively from existing data and help computers find hidden insights without being programmed to do so.
Machine learning can help companies to make data-driven decisions that result in savings and increased revenue. In addition, machine learning algorithms help eliminate risk and fraud, ensure secure processes and improve customer satisfaction. Surveys show that there are use cases for machine learning across all industries and all levels of companies. Artificial intelligence, and machine learning in particular, will not only have a significant impact on society over the next few years, but also and above all on the company’s own business areas.
Use cases of Machine Learning in companies
Machine Learning can be used to follow and understand customer conversations in the context of a product. It can even apply the algorithm to predict the functionality and features customers expect. In addition, a company can use machine learning to build better relationships with its customers. The machine learning algorithm can easily identify customer requests and send them to the appropriate team. It will accelerate the process of solving customers’ problems and provide them with quick answers.
When creating digital services, companies can use machine learning to enable customers to find products or information faster. A specific algorithm helps to ensure that customers receive relevant and high-quality information in a timely manner. In addition, the new technology helps customers to select products according to their needs and preferences.
Learning algorithms can be used in the financial industry to develop automated trading strategies. They can be used to identify patterns and make trading decisions based on data. The other potential applications are the creation of credit scoring mechanisms by searching for patterns of external, internal and economic factors that influence the financial performance of companies. These techniques can also be used to provide relevant automated investment advice to clients.
The speed with which Machine Learning identifies relevant data enables companies to take appropriate action at the right time. For example, Machine Learning optimises the best follow-up offer for a company’s customers. This enables the customer to see the right offer at the right time without an employee having to spend time on individual support or preparing offers. Machine Learning enables companies to analyse and interpret data on past behaviour or results. Based on the new and different data, better predictions about customer behavior can therefore be made.
Attacks on IT networks usually occur in real time without prior warning. To enable companies to maintain network security, any suspicious network behavior must be proactively identified before the intrusion leads to a full-scale security attack, data loss and outages. Machine learning algorithms help monitor network behavior for anomalies in real time so that proactive measures are automatically executed.
How companies implement Machine Learning
With the introduction of their cloud machine learning platforms by Google, Amazon and Microsoft Azure, the topic of artificial intelligence has gained in importance in recent years. There are various approaches to introducing machine learning in companies. The cost of data storage has fallen so dramatically that companies can access large amounts of data, hide the patterns of profitable business knowledge and use machine learning technologies to uncover them. Some organizations use cloud-based tools and third-party systems, while others use applications with built-in machine learning capabilities. Many algorithms and frameworks are accessible through open source channels. These pre-existing resources enable organizations to leverage machine learning without having to invest in the necessary infrastructure up front. The technology is already mature and companies can take advantage of the benefits.
These benefits can be applied to a wide range of use cases, especially when data is the focus of the service offering. The technology is rapidly replacing manual operations in the enterprise market segment, and both small and medium and large enterprises are well positioned to take advantage of machine learning solutions.