Recently, the business has been generating a colossal information flow, which is increasing literally before our eyes. Conventional means can no longer cope with the processing of such a volume of data, therefore, not only new capacities for storing accumulated data but also completely different analysis and processing technologies become necessary.
One of the technologies that can cope with the increased volume of data can be artificial intelligence. Its main advantage is the speed and quality of information processing: what a person can spend an hour, a day, a month, or even a year on, AI can do in just a few seconds.
Process Automation
One of the most common applications of AI in business is the automation of processes. Dasha.AI offers a solution for enterprise performing collection and analysis of large amounts of data flowing from various departments of the company.
Marketing is becoming more and more personal, and artificial intelligence helps to analyze a large amount of data, taking over the routine work of processing information and finding the best solutions for building communication with the user. With the help of AI, shortcomings in the work of both individual employees and entire departments are revealed, various options for solving problems are analyzed, and the degree of efficiency of the company as a whole is assessed.
AI algorithms are also used for automatic processing and verification of primary documentation:
- invoices;
- acts;
- details and descriptions of nomenclatures.
Virtual Assistants
They play a special role in automating business processes. Now they are in great demand in areas that are interested in automating customer services to reduce costs:
- telecom;
- finance;
- retail.
These industries have always been IT trendsetters in business. They have been implementing chatbots in all text channels for a long time. And today, they are starting to massively develop voice assistants for processing incoming calls, outgoing calls, and even sales (which seemed impossible before).
AI-based virtual assistants can independently communicate with customers via email, instant messengers, and phone, collect feedback, perform money transfers, and other simple operations.
Such systems can be used not only on websites but also in call centers, where they perform many completely different tasks. So, it can provide omnichannel service — when the interaction of the operator with the client goes through various channels — social networks, applications, email. In this case, AI aggregates information, analyzes, and presents it in a form convenient for the employee.
In addition, based on a deep analysis of the available information about interactions with customers, the AI platform can make fairly accurate predictions about future consumer trends, identify patterns of customer behavior, and predict their requests. It is possible to target offers and improve products and services based on implicit feedback from customers, provide customer service 24 hours a day, predict the behavior of potential buyers, and much more.
Data Analysis
Artificial intelligence is also involved in the field of data analysis. The high speed of their processing, the possibility of structuring, and the ability to work with big data make it ideal for such work.
The goal of most projects using intelligent information processing is to improve customer experience, increase business efficiency and transparency. Companies are constantly looking for new growth points, adjusting development priorities, and quickly responding to market changes. To do this, they use the entire stack of technologies aimed at working with data and business processes.
AI algorithms are also used in predictive analytics, in other words, forecasting. This is especially in demand in sales, where they assess the demand potential for a particular product, then analyze the behavior of the buyer and, as a result, issue recommendations on how to increase the check.
Recruitment and HR Management
Already, AI algorithms speed up the process of processing resumes by 94%. This usually happens in three main ways:
- competence;
- education;
- experience.
In addition, AI can select not by one database, as a person does, but by several at once. Automated and identified gaps in the knowledge and skills of candidates. AI deals with employee skill assessment and training.
Also, artificial intelligence allows the company to determine the correspondence between the psychological portrait of the ideal employees and the candidate, the ability to work in a team, and also take into account hidden factors that affect the further effectiveness of a person in a team, such as remoteness from home to work or the candidate’s interests outside of work.
AI can monitor employee performance. Some programs analyze the work of employees at the computer. This includes monitoring email, studying the web pages that the employee visits, and documents created by him. All collected information is sent to the server, where the AI system analyzes everything and identifies gaps in the work.
Efficient Marketing
Whereas previously, businesses had to wait for the user to find the right product or service in the browser, now the right information almost finds the user on its own. Therefore, over time, artificial intelligence has become a part of marketing: it can not only help develop a marketing strategy but also take over part of the implementation. Thanks to technology, it has become easier than ever to segment customers by demographics and interests, which allows you to target ads and give consumers what they need and want.
Already, AI has shown itself so well that businesses are ready to invest in its study and implementation. The main trend in the development of AI in business shortly will be the use of cloud technologies. Only with their help, it will be possible to overcome the main barriers that prevent AI from fully working in business — the lack of available high-performance computing resources for working with AI algorithms, the weak distribution of machine learning models, and the acute shortage of relevant specialists — data engineers, analysts, and so on.
