What is artificial intelligence?
Artificial intelligence (AI), also known by its English name, Artificial Intelligence (AI), is a technology that tries to perform tasks and make business decisions automatically and autonomously, learning continuously.
Artificial intelligence uses Big Data to obtain the data necessary to operate. With business intelligence (BI), you analyze that data, and the AI will use those statistics to make decisions. For example, in a company that manufactures machines, sensors in the plant indicate the temperatures at which parts are being made. If a sensor detects that one of the machines that make the parts shows a temperature higher than the recommended one, an artificial intelligence system can stop the production process and alert a technician to investigate what the problem is. This process is quite common in Industry 4.0 companies since the system uses all the data to make the right decisions.
Attention: companies use different databases to collect Big Data data. Choosing a good database is essential for good data storage and security. In the ERP Guide, there is an in-depth comparison of the different databases on the market.
What does machine learning have to do with artificial intelligence?
Machine learning (ML, or machine learning in Spanish) is the technology that makes artificial intelligence learn continuously. The system receives an input, and a human reacts, and, thus, the next time the system gets that input, it will know how to act without having to go to the human.
Today, this system can become even more advanced. ML uses deep learning (DL, or deep learning in Spanish) to learn without human help. Deep learning technology uses a series of examples and a series of rules to learn to solve problems autonomously. For example, a chatbot can use deep learning to solve users’ questions or concerns. You can also know what the most popular topics are. In this way, proposals may come out to the user as soon as they open the chat, together with choosing the option to select another topic and recommend the content related to their query.
How is artificial intelligence used in companies?
Artificial intelligence within different types of companies can be very varied. Today many programs include an AI module to optimize business processes. Some of the most common uses within artificial intelligence are discussed below:
How is image recognition (computer vision) used?
Computer vision is the recognition of objects through pictures. In some food companies, a robot controls the apples that pass through a conveyor belt. The robot uses artificial intelligence to review the apples, categorizing them. So mandalas that are perfect on one side are sold in greengrocers, and those bruised elsewhere to be reviewed. Depending on the characteristics and quality of the bruised apples, they are processed to make products such as compote or apple pudding or used for animal feed.
Another use of this type of AI is facial recognition. Some companies use this technology to grant access to the headquarters and the different rooms to authorized persons, thus generating control of the time they have been. With this use, it is necessary to ensure that the system complies with the data protection regulations to avoid problems.
Language technology understands the message
Language technology (or Language Technology, LT) is still relatively new. LT consists of understanding natural language both in oral and written format. One of the uses of this technology is voice recognition for identity and access management. For example, when a person asks Siri something or says “Hey Google,” the corresponding mobile assistant is activated only with the device owner.
However, that is not the only use of natural language recognition. For example, when an email is received, the language technology system can study the content of the message to recognize the nature of the message ( Digital mailroom ). In this way, even if the matter does not put “complaint” or the content itself, the system finds out that it is because it says something like “I’m not happy” or “I’m disappointed.” Thus, it can classify the different received emails, redirect them to the appropriate person and register it within the document manager in the complaints section.
Robotic process automation (RPA) to save time from repetitive tasks
Robotic process automation ( RPA ) automates repetitive tasks. RPA is software programmed to do tasks (almost always) without the need for a human. For example, an HR system can automate the entire onboarding process for your employees. At the moment in which a person is selected for a vacant position, the system is put into operation so that they follow all the corresponding steps, such as: registering with social security; sending the documents for the protection of occupational hazards to the new employee; dump the recruiting system data in an employee file in the HR system; and provide you with all the necessary accesses to carry out your activity (email account, access to the software, possible initial training course, etc.).
The most common use for RPA is to automate accounting processes. For example, robotic automation of account reconciliation processes. While an employee can take about 2 hours to perform this task, this system takes 2-3 minutes. The RPA can work sequentially for 24 hours. It can be filled with processes that are done one after another until the 24 hours of work are filled.
Using AI in customer relationship management
A customer relationship management (CRM) system serves to store and track customer data centrally. Artificial intelligence recognizes trends and behavior patterns of target customers. In this way, artificial intelligence can incorporate data into the CRM and help segment it as stipulated by the company (location, gender, age, purchase history, …). In addition, in some cases, email marketing is being automated. Personalized emails can be sent automatically using artificial intelligence since the artificial intelligence system will feed on the CRM data and enter it in the email.
For example, a company wants to launch a marketing campaign for customers between 25 and 30 years old who have bought in the last six months. Then, the AI system will obtain all the email addresses of the people with that profile and will send them one by one an email in which they put: their name (to be more personal), the details of the offer, when they acquired something for the last time (1, 2, 3, 4, 5 or 6 months ago). Being personalized for the client, the email will have better reception. Another advantage is that doing the system rather than the employee saves a great deal of time.
Another example of AI with CRM is that of an online clothing store. When a customer has looked at and bought certain products, the system shows him related products. In this way, the customer is tempted to buy products that have a great potential to interest the customer and, thus, increase the average purchase ticket and sales.
Did you know? The cost of acquiring a new customer is higher than building loyalty from existing customers. In the CRM Guide, there are tips to achieve customer loyalty with the help of a CRM system.
Production prediction to set prices
Artificial intelligence systems feed on data and are capable of making production predictions. In the agricultural sector, it is widespread to use AI to know the number of products of each type that will be produced in advance. For example, if there was a drought or an insect infestation, this data will be recognized by the AI system. In this way, for example, it is known that an insufficient quantity of tomatoes will be produced compared to the previous year. Due to the shortage of tomatoes, this will cause the price of tomatoes to rise in the prior year. On the other hand, if there is an overproduction of tomatoes one year, the cost of tomatoes will drop considerably.
Recognition of fraudulent transactions with AI
Companies dedicated to the financial world invest in security technologies, such as Blockchain or AI. In the case of artificial intelligence, banks use this technology to identify and respond to patterns efficiently and quickly in the face of emerging fraud trends. For example, when a user makes an online purchase with a card, the investment must undergo a series of validations before being approved. The user’s account has developed a profile with their behavior patterns. In this way, to evaluate whether the transaction should be approved, the bank will check a series of details. These details are: that the store is related to the type of stores the user would go to; the device from which you pay is usually linked to your account; and other verifications of IP addresses and email and telephone.
Modules specialized in artificial intelligence VS included in the software
Artificial intelligence can be integrated into software systems of different fields or as specialized independent software. If it is integrated into a system, it is usually already entirely configured to do a specific type of task. However, when it comes to standalone and specialized software, you have to configure it to do the required job. This second type offers more flexibility and possibilities but requires an expert team behind it.
Many large software companies develop AI in both forms, both embedded within their enterprise software and as separate systems. Some of these organizations are IBM, SAP, Microsoft, and Oracle. The cost of AI within enterprise software is usually included in the total price of the software, while the price of a standalone program will be significantly higher. For example, SAP goes from € 1 per month per unit of capacity (infrastructure resource, both computing, and storage) with a minimum contract of 3 months. IBM offers a free version of Watson, a standard one that costs $ 99 per month, and a versioned enterprise for $ 6,000 a month. Microsoft offers its pay-as-you-go Artificial Intelligence. Oracle has a different rate depending on the type of AI required, with prices starting at € 0.89 per capacity unit or € 89.981 per user per month.