Artificial Intelligence (AI) is directly related to Data Science – the science of data aimed at extracting business value from an array of information. This value may include, for example, increased forecasting capabilities, knowledge of patterns, and informed decision-making. In a narrower sense, AI is algorithms and methodologies for information processing. Artificial intelligence operates on huge arrays, analyzes incoming data, and develops adaptive solutions based on them.

Artificial intelligence is used in various fields, including marketing and business. According to PwC, artificial intelligence will boost gross domestic product (GDP) in individual countries by 26% and boost the global economy by nearly $16 trillion. In this article, we will look at how modern digital technologies are used in the market, what a “smart” algorithm can do, what results it produces, and why the use of AI software consulting services gives companies an advantage over their competitors.

In the realm of business, artificial intelligence plays a pivotal role, offering tools like the DragGAN AI editing tool to enhance efficiency and creativity. This tool simplifies image manipulation with its intuitive drag-and-drop interface, enabling businesses to create compelling visuals effortlessly.

Incorporating such advanced AI tools can significantly streamline operations and drive innovation, giving companies a competitive edge in the market.



The enterprise AI solutions can quickly take a business to a fundamentally new level; this is one of its key functions and tasks. Here are a few problems that can be solved using machine learning algorithms:

  1. Prompt response. In some areas of business, a fundamental condition for success is to quickly analyze incoming data and respond to it instantly – for example, in stock exchange operations. Unlike conventional algorithms, which are not able to independently adapt to new conditions and data without prior training, artificial intelligence provides this opportunity. Leveraging custom AI development services can significantly enhance this capability, offering tailored solutions that perfectly fit specific operational needs and industry requirements.
  2. Development of a marketing strategy based on the provided data and established goals. Artificial intelligence helps in the work of a marketer: it not only analyzes the experience of previous sales, but also uses forecasting to “predict” future ones, and takes into account the behavior of competitors and the general situation in the market.
  3. Human factor. Even the most professional and experienced employee has a bad day and bad decisions. Artificial intelligence does not, it has functions instead of emotions, and technology and information replace changeable moods.
  4. Fighting fraud. In addition to analyzing user behavior and spotting questionable transactions, self-learning neural networks are used to develop algorithms that stop financial losses. As a consequence, the system becomes less susceptible, which is essential for gaining the confidence of users.
  5. Increased profits. The use of machine learning in the pricing system alone can provide a 5% increase in revenue, and with an integrated approach, the company’s revenue can increase several times.

Areas of application of artificial intelligence

  • Banking (forecasting, chatbots in mobile banking apps, risk management).
  • Information security (anti-fraud technology, information for building a shared database, and analysis of historical dangers and prevention of future ones).
  • Industry (managing manufacturing processes, optimizing them, diagnosing equipment, tracking malfunctions, taking preventative action, automation).
  • Trade (procurement management, customization of loyalty programs, in-depth analytics, study of purchase behavior, and the efficacy of marketing campaigns).
  • Medicine (documentation, diagnostics).

This is only a small part of the capabilities of AI. Of course, solving all of the above problems is also possible for humans, but it will require much more time and resources. The development of a self-learning system also requires investment at the first stage, but in the future its assistance in processing large amounts of data is invaluable.

Certain business segments have transformed with the advent of artificial intelligence, for example:

Chatbots. Machine learning algorithms replace call centers and help perform such tasks as providing customer assistance and information around the clock, on holidays and weekends. A “smart” program learns from its own mistakes and over time surpasses a live operator’s incompetence. Result: a significant increase in customer loyalty, creating a positive image of the company.

Data management. AI collects, systematizes, analyzes, and stores company information, makes forecasts based on it, and/or monitors the condition of equipment.

Automation. A self-learning algorithm takes over regular routine tasks and frees up human resources to solve more creative problems. For example, the program can fully automate the booking of hotels and conference rooms, sending out invitations to meetings, purchasing air tickets, and planning routes. In this way, the entire administrative sphere can be transferred to artificial intelligence. Automation existed before, but its scope was limited.

Forecasting. Humans are not entirely unbiased and objective, in contrast to artificial intelligence. Furthermore, processing a large quantity of data is necessary to provide a trustworthy prediction, and the computer executes this task admirably.

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The use of artificial intelligence is gradually becoming a necessity in all business sectors. The only question is who will be the first to introduce modern technologies and get quick results, and who will catch up at the very end in order to at least just stay on the market? According to McKinsey research, Data Science has a significant impact on marketing and sales, and market analysts strongly recommend implementing artificial intelligence today.

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