What is AI and why do businesses need it?

Artificial intelligence is overturning the conventional view of what can be achieved through technology. This breakthrough has changed the face of traditional industries and opened new perspectives for entrepreneurs.

In this article, we will analyze what AI is and how it is useful for business.

What is Artificial Intelligence?

Artificial Intelligence (AI) is a field of computer science concerned with creating systems and programs to perform tasks that normally require human intelligence like how to write a hit song.

These systems are capable of analyzing data and extracting information. Thereby enabling machines to learn from experience, adapt to new information, and perform tasks that require intelligence.

Artificial Intelligence and Business Processes

With AI, businesses have almost limitless access to new opportunities to expand operations and increase profits. Even a single algorithm can significantly improve performance, and an integrated approach is all the more likely to yield good results.

What the application of AI in business can bring to owners:

  • Routine administrative tasks, which we have already discussed above.
  • Increasing the productivity of specialists by optimizing work processes.
  • Technical and information support for clients.
  • Reducing the role of the human factor in decision-making.
  • Improving communication within companies, including overcoming the language barrier.
  • Control over financial transactions, detection of suspicious user activity.
  • Control over information security, observance of data confidentiality.
  • Development of marketing strategies.
  • Forecasting both in the short term and for the more distant future.

Artificial intelligence in business: examples


Enterprises that work with food products must monitor their shelf life and conduct timely write-offs. For example, in bakeries and bakeries the sell-by date is only one day, up to 30% of bakery products are written off every day.

The challenge: reduce losses, but not the assortment, as customers want a wide selection.

Solution: the use of artificial intelligence made it possible to predict demand for the next 3-4 days, with a prediction accuracy of 90%. All that was required was to analyze data from the CRM for the last two years and train the algorithm. Thanks to the forecast, the network was able to optimize the shop’s operation, reducing the amount of baked goods written off by up to 15% without losing assortment. The task was accomplished, and a positive “side effect” was a reduction in raw material consumption and an increase in margins.


Problem:  A loyalty system (loyalty cards) and special discounts during happy hours were introduced in the chain’s stores, but the effectiveness of these promotions was not measured in any way, and profits increased insignificantly.

Solution: self-learning program analyzed the purchase history of customers with a loyalty card and, using data for several years, selected the optimal system of incentives for each of them. If a customer was not interested in promotions and discounts, the artificial intelligence sent him other alerts, such as a description of the assortment or the dates of availability of his favorite products.

Shoppers who were interested in the “happy hours” promotion were informed by the computer about lucrative offers and when the next promotion would start. The store also used such a function of the program as sending personalized SMS.

Result: timely information increased customer loyalty, repeat customers increased by 80%, and both profit and margin increased. The task was completely solved.

Implementation of artificial intelligence

Utilizing AI requires a multi-step process. The entrepreneur’s first and primary task is to collect as much data as possible on sales over the previous several years; this kind of data set is known as a DataSet. Thankfully, the advent of online cash registers has made it possible for this data to be automatically recorded, requiring no human input from the user. The system synchronizes with it with only a few clicks. In many situations, organizing the information you currently have may enough, but in others, additional time and work will undoubtedly be required.

Money and effort will be needed to develop a self-learning algorithm, but the business sector will determine how much it costs. Retailers don’t have to start from scratch when developing a recommendation system; instead, they may use pre-made solutions. Increasing income is one of these systems’ purposes. After three months of usage, AI often pays for itself and starts to turn a profit because of large cost savings and higher sales.

The main steps in implementing AI:

  1. Collecting and digitizing information for analysis, inputting it into a data processing program.
  2. Creating an algorithm from scratch or refining it on the basis of a framework.
  3. Training and self-training of the algorithm.
  4. Creation of a new integrated marketing strategy of the enterprise and all business processes taking into account AI capabilities.

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Michael P
Los Angeles based finance writer covering everything from crypto to the markets.

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