Ai and ml in retail are important when a company has a lot of data and needs to simplify working with it or earn more with it. This scenario is relevant, for example, for marketing, IT and banking.
What is AI, ML and what are they for business
AI (artificial intelligence) is artificial intelligence. That is, the machine performs tasks that only a person could handle before. AI systems are capable of launching a thought process: they reason, look for meaning, generalize, learn from their mistakes and draw conclusions.
A slightly narrower concept is ML (machine learning) – machine learning. This is one of the methods of artificial intelligence, and it is just responsible for transferring the necessary “knowledge” to the AI system.
With the help of artificial intelligence of the company:
- create personalized offers, images, videos, texts;
- build communication with potential and real customers (chat bots are the same AI);
- select personal products and interest from banks and bank cards;
- show suitable vacancies on Headhunter;
- develop mobile applications;
- recognize speech and create voice assistants.
In ordinary life, people encounter Al and ML without noticing it. For example, you read about the new iPhone model on your work laptop, and already on the way home on Instagram you are constantly being offered advertisements in the spirit of “new iPhone in installments”.
One more example. You urgently need to fill the site with text, and you turn to a content agency in the hope that your task will be quickly taken up. There are no free copywriters, but the agency uses artificial intelligence technologies – and you immediately get ready-made texts for the site.
Now AI and ML are most widely used in six areas:
- Analytics, project management and decision making.
- Natural speech processing.
- Personalization of marketing and service.
- Internet of things and digital twins.
- Autonomous devices (for example, robotic vacuum cleaners).
- AI-development (for example, the development of business solutions without the involvement of consultants).
Why not all companies use data
To use artificial intelligence and machine learning in a company, you need to collect customer data. All this amount of information is called Big Data – a database that companies receive from external and internal sources: reports, data from the support service and sales department, analytics systems and the actions of the customers themselves.
The simplest example is polls in chatbots or via email. The client answers questions, his answers are transferred to the database, after which you can connect AI and ML to work and create a personal offer for him.
Conventionally, all companies can be divided into 3 groups:
- We have nothing: do not use data because they do not understand or do not see the point in it. As a rule, they have a large shortage of specialists, very expensive cloud or boxed solutions, and a complex process of introducing new technologies. Getting started with data here is the hardest and longest.
- We have data: they are just starting to use data in their work, collecting analytics to understand how their business works. They, as in the first group, may have expensive cloud or boxed solutions, a constant shortage of personnel, and an outdated set of technologies.
- Data-Driven Company: well built data-driven processes. They already know how to collect and apply data in business. It is in such companies that new technologies quickly take root and develop.
Enterprise application development services you will also find in the list of our services.
