Svojim ubrzanim razvojem, veštačka inteligencija (VI) postala je značajan faktor koji utiče na savremeno poslovanje, sa važnim implikacijama u različitim organizacionim domenima. Mapiranjem literature o uticaju VI na moderno poslovanje, ovaj rad nastoji da identifikuje relevantne studije i klasifikuje ih prema ključnim oblastima primene, uključujući poslovnu efikasnost i inovacije, korisničko iskustvo, analizu podataka i donošenje odluka, kao i pitanja vezana za etiku, bezbednost i rizike primene VI. Studija se zasniva na sistematskom pristupu pregledu postojeće literature, uz primenu etabliranih metodologija scoping pregleda radi identifikacije i odabira relevantnih studija i istraživanja. Istaknuta su određena ograničenja i praznine u postojećem korpusu istraživanja, koja mogu poslužiti kao osnova i polazna tačka za dalja istraživanja. Na kraju, rad iznosi niz zaključaka i predlaže moguće pravce budućih istraživanja.

Introduction

The development of information and communication technologies has influenced all aspects of contemporary society (Stanković, Čerović, & Panić, 2023). Very often, companies that were pioneers in adopting innovative technologies over the past twenty years have experienced significant growth and business development. AI is one of the latest advances in this field and a key factor in modern business transformation. According to a PwC report, by 2030 AI could add up to 15.7 trillion US dollars to the global economy (PwC, 2020). However, some authors point out that for a broader application of AI, certain prerequisites must be fulfilled: Natural Language Processing (NLP) for communication in natural language; identification and storage of new knowledge; Automated Reasoning for creating answers and drawing conclusions based on stored information; and Machine Learning (ML) for adapting to new circumstances, as well as for discovering and extrapolating patterns (Russell & Norvig, 2016; Huang & Rust, 2018).

Selection Strategy and Source Validation

Using the PRISMA-SCR framework, five levels of selection were applied to the identified studies and articles on the given topic. At the first level, the selection focused on the title of the article. Once this criterion was met, the process continued to the second level, which involved the review of keywords.

Figure 1. PRISMA-SCR FLOW Diagram for literature selection

At the third level, the author evaluated the abstracts of the articles that had satisfied the previous criteria. If the article met the requirements at this stage, a full-text review was conducted at the fourth level. Finally, at the fifth level, the conclusions and limitations of the reviewed studies were analyzed.

This review included a total of 24 articles that satisfied all requirements after applying the above criteria. The authors independently developed a matrix for mapping the selected studies. This matrix included the following key data points: names of authors, year of publication, type of article, research area, and key conclusions. Organizing the studies in this way facilitated comparison and the synthesis of results. The articles that remained after the selection of the available literature were thoroughly analyzed and included in the developed matrix for the purpose of synthesizing the results.

We considered a broad spectrum of academic sources important in gathering the literature for this study on the impact of AI on contemporary business (Savić et al., 2025a). The reviewed literature on the impact of AI on contemporary business is considered relevant and provides valid research supported by credible data.

However, it's crucial to stress that we observed several potential limitations. Since AI is still a relatively new phenomenon in the business environment, the lack of empirical data may affect the completeness of the analysis of its impact (Perifanis & Kitsios, 2023). In addition, the rapid technological progress in the field of AI may lead to the quick obsolescence of data and information in certain studies (Savić et al., 2025b).

Given that AI is part of a complex economic and financial system, its influence may be affected by different factors such as geopolitical events, regulatory changes, technological development, and market demands (Bharadiya, 2023; Janković & Golubović, 2025). These factors are difficult to predict and may significantly shape research outcomes.

Despite these limitations, it is important to stress that the existing literature still provides valuable insights. To gain a more comprehensive understanding of this topic, future research should aim to address these limitations and include broader perspectives to create a more complete picture of the impact of AI on contemporary business (Kitsios & Kamariotou, 2021; Sira, 2022).

Integration of Key Findings

The synthesis of this research followed several key steps in the preparation of the study. This included a comprehensive review of all collected sources and the recording of key findings, research methods, and identified limitations. Notes were then grouped according to relevant themes and subthemes related to the impact of AI on contemporary business. The main topics emerging from the reviewed sources were analyzed and compared to identify similarities and differences. A critical assessment of the quality of evidence in each source also considered the limitations mentioned in the reviewed studies, as well as those recognized by the author, considering the applied methodology and sample size. The final findings were synthesized to provide answers to the research questions concerning the impact of AI on contemporary business.

The main topics addressed in the articles include the application of AI in modern business and its effects on processes, performance, and innovation, with particular attention to reliability, transparency, and data availability. We also examined how AI transforms business models, optimizes decision-making, and enhances business efficiency. In addition, the article contains the authors’ predictions about the future application of AI in this context.

Relevant evidence and data on the impact of AI on contemporary business were grouped into several categories, including the use of AI in different industries, its influence on strategic decision-making, and its role in creating competitive advantages for companies.

As illustrated in the flow diagram for literature selection (Figure 1), the search initially identified 122 studies and articles. By applying the established selection process through five levels—title, keywords, abstract, relevance of the topic, and conclusions—the number of relevant studies was narrowed down to 23, which were analyzed in detail and synthesized in this review.

Special attention was given to literature that provided insights into the direct or indirect impact of AI on business processes, value creation, and ethical principles of AI application. The reputation of the authors was assessed based on citation counts, while the reputation of scientific articles was evaluated using impact factors obtained from the academic databases included in the search. Selected sources had to meet criteria of reliability and validity, considering the applied methodology, sample size, instrument validity, and other factors influencing the quality of data.

The authors carefully assessed the credibility and reliability of the selected sources to ensure that the review’s objectives were achieved. The methodological approach to this critical evaluation included a systematic review of relevant studies and articles in the fields of information and digital technologies, artificial intelligence, economics, and business. To assess methodological quality and identify potential limitations, the CRAAP test (University of the West of Scotland, 2022) was used. Applying the CRAAP criteria (Currency, Relevance, Authority, Accuracy, and Purpose) ensured the relevance and reliability of the information and findings from the selected sources. This provided adequate information and a high level of reliability in addressing the objectives and purpose of the review. Nevertheless, it should be noted that certain limitations exist in the selected sources, which were transparently acknowledged with the aim of creating a comprehensive overview of the results obtained.

Review of Primary Sources of Evidence

The results of the individual sources of evidence were synthesized in the table provided in Appendix 1 of this article. Based on the analysis of the available literature that met the relevance criteria, it can be concluded that AI has become a significant factor in contemporary business. Organizations that aim to ensure further development and growth must inevitably focus on the implementation of AI solutions into their business processes. On the other hand, the use of AI in company operations generates an increase in productivity, which creates conditions for sustainable economic development and enables the formation of competitive advantages (Maslak et al., 2021).

The analysis also indicates that the field of AI application in business is still in its early stages. Although there is notable interest from both the academic community and business practice, there is a clear need for further research and deeper segmentation of studies across different business domains and processes.

The impact of AI on contemporary business is undeniably significant. Its advantages, such as the rapid and precise processing of large volumes of data, process automation, and improvements in efficiency, make it an indispensable resource for many companies.

Table 1. Synthesis of Research Results

Organizations that successfully implement AI into their operations have the opportunity to generate substantial innovations through new business models and processes, thereby creating the potential to transform the global competitive landscape (Lee, Suh, Roy, & Baucus, 2019).

However, this progress also raises numerous questions and concerns. One of the main issues relates to data privacy and security. AI requires access to large datasets, which may lead to potential misuse or data breaches. Moreover, as with all new technologies, the application of AI in business has certain limitations, including insufficient awareness among decision-makers about the potential benefits of implementation, low levels of IT competencies, underdeveloped IT infrastructure, and the need to design customized solutions for each business organization (Grünbichler, 2023; Žikić et al. 2022).

Conclusion

Artificial intelligence, as one of the modern digital technologies, is becoming an important factor in the development of business organizations and has a strong influence on contemporary business. The impact of AI can be considered from several aspects: business efficiency and business strategy, interaction with users, support to business analytics and decision-making, as well as ethical and social issues. The use of AI in business brings clear advantages, such as faster data processing, automation of processes, and better efficiency, but at the same time it creates risks. Because of that, each company has the challenge to find its own way to implement AI and to manage the risks that come with it.

This review shows that AI is not only a new trend but also a strategic resource for companies that want to stay competitive in the long term. Further development of information and communication technologies, the regulatory environment, and the fast changes on the global market suggest that AI will in the future become one of the tools without which companies cannot operate. According to Gonzalez-Tejero et al. (2023), the cooperation between academia, business organizations, and regulators should be used to develop principles that will help sustainable use of AI technologies and their introduction into business practice.

This article also points out several limitations. One limitation is the lack of access to some articles and the relatively narrow literature search, which means that some relevant works may have been left out. Another limitation is that only literature about company operations was used, while technical and technological aspects of AI were not included. In addition, the choice of sources could have been affected by the authors’ bias. This means that some relevant articles might have been excluded from the final review because of subjective judgment during the selection process.

Since this is a relatively new topic and technology is changing very fast, many authors agree that current research does not cover all aspects of the problem. Some studies are based on a small number of sources, while others rely on assumptions that can easily change over time. Because AI develops quickly, research in this field also needs to be updated often and followed continuously.

AI is both an opportunity and a challenge. It can have an impact on developing new business models, better efficiency, and innovation, but at the same time, the potential risk that this technology carries requires responsible use, ethical standards, and careful regulation.