In recent years, thanks to advances in information technology, machine learning has become extremely popular in business. Businesses around the world are using this field of artificial intelligence to analyze large data sets to gain valuable insights into their customers, markets and competitors. Machine learning algorithms are used in a wide variety of fields, allowing companies to increase productivity, among other things. In our article, we will present some examples of how this technology is being used.
How is artificial intelligence developing?
According to the definition, artificial intelligence (AI) is a field of computer science that deals with the creation of computer systems capable of performing tasks that would normally require human intelligence. As a result, the technology is developing in several basic fields:
- Machine learning – one of the most important branches of artificial intelligence, which allows computer systems to learn from data.
- Natural language processing – the field that deals with the understanding and generation of natural language by computers. Includes speech recognition, machine translation or text generation, among others.
- Robotics – an area focusing on the construction of autonomous machines and systems that are able to perform increasingly complex tasks, such as moving autonomously through space, identifying objects or interacting with humans.
- Data analytics – a field that allows real-time processing and analysis of data to make business decisions faster and more effective.
- Ethics and privacy – the development of artificial intelligence also raises ethical challenges, so various types of tools and technologies are being developed to protect the privacy of user data.
What does the term machine learning mean?
As we mentioned above, machine learning is a field of AI that deals with creating algorithms and models that can learn from data and automatically improve their performance. In other words, it’s about computers and information systems being able to detect patterns in data and make decisions based on them, instead of relying on rigid programming rules.
The process of machine learning involves providing an algorithm with a large amount of training data from which it can learn to recognize specific patterns. With successive such lessons, the artificial intelligence gradually improves its performance, adapting to new information and situations.
Practical application of artificial intelligence in business
The rapid development of machine learning is taking artificial intelligence to a whole new level. As it increasingly mimics behaviors similar to human manifestations of intelligence (as defined by McCarthy), it is becoming very useful in business. Examples of its applications include:
- Personalizing offers and advertising – intelligent programs are able to collect and analyze data about customers, then tailoring store offers and advertising messages to them.
- Demand and demand forecasting – based on historical data, such as sales or consumer trends, intelligent programs automatically predict future customer needs and adjust production or orders accordingly.
- Optimizing logistics processes – self-learning machines use collected data on product availability, delivery times or weather forecasts to create logistics models for companies in any industry.
- Credit risk analysis – based on guidelines such as customers’ credit history or income, AI programs can infer whether they are solvent, deciding de facto whether they can be granted credit.
- Customer service automation – science allows for the training of chatbots or voice assistants, processing user inquiries and providing answers based on the information they have.
These are just a few examples of the use of artificial intelligence in business. However, it is worth noting that it is evolving exceptionally fast, penetrating even into the field of art. Huge popularity today, for example, is enjoyed by intelligent generators of images or videos available online. AI-composed musical pieces and AI-written scripts are also creating a furore.
Properly programmed algorithms, thanks to deep learning methods, are increasingly able to cope with the complexity of human language, which allows them to perform advanced tasks, solve interesting problems and achieve further goals – not only business ones.