Project “AID” is implemented within the framework of the National Recovery and Resilience Plan 2021–2026 and is financed by European Union funds through the NextGenerationEU instrument.
The “AId” project explores how artificial intelligence (AI) is fundamentally changing consumers’ decision-making processes and what the key implications of these changes are for market dynamics and company strategies. In today’s deeply digitalized era, AI-driven systems—from sophisticated recommendation algorithms and personalized marketing campaigns to intelligent virtual assistants and dynamic pricing—have become an unavoidable, ubiquitous part of the consumer experience. These tools not only change how consumers discover information, evaluate alternatives, and make final purchase decisions, but also reshape their expectations and ways of interacting with brands across a wide range of industries.
Through a multidisciplinary research approach, the “AId” project will provide scientifically grounded insights into the psychological and behavioral aspects of AI’s impact on consumers and markets. Based on these insights, practical frameworks and recommendations will be developed for companies, helping them redefine their business models and strategies, and specify the key managerial competencies necessary to lead companies in AI-shaped markets—thereby directly contributing to stronger competitiveness, innovation, and responsible business conduct in an increasingly complex era of artificial intelligence.
The main goal of the project is to identify the impact of artificial intelligence on market dynamics. Specifically, the project includes three key objectives:
To analyze in detail and understand how AI influences consumers’ cognitive processes, preferences, and behavior—considering the role of AI as complementary support in consumer decision-making processes, and as a substitute for the consumer in decision-making.
To identify how companies should adapt their business models, marketing strategies, brand management, and customer relationship management in order to operate successfully and ethically in this new, AI-shaped market environment.
To define the key knowledge, skills, and competencies that managers must possess for effective company management and decision-making in the context of market changes resulting from the pervasive presence of AI; and to develop innovative educational resources.
To develop scientific infrastructure (databases and domain knowledge), scientific productivity (six papers submitted for publication), and young researchers (doctoral students) within the Faculty of Economics and Business – Zagreb.
In addition, the project’s indirect objectives are:
Structuring knowledge and mapping the areas of AI’s impact on market dynamics and company strategies.
Developing a framework for understanding the role of AI in market dynamics and company strategies.
Conducting research.
Developing guidelines and recommendations.
Raising awareness among the public and professionals about the implications of AI for consumers, companies, and the system.
Integrating a research team focused on studying AI’s impact on market dynamics and company strategies.
The current state of research (State of the Art) in artificial intelligence (AI) points to its transformative potential across various domains, with particular emphasis on marketing and consumer decision-making processes. The proposed project “The Impact of Artificial Intelligence on Decision-Making: Implications for Market Dynamics and Company Strategies (AId)” aims to make a significant contribution to the further development of knowledge in this dynamic field by addressing the key challenges and opportunities that AI brings.
The concept of artificial intelligence, defined as early as 1956 at the “Dartmouth Conference,” anticipated a future in which machines learn, form concepts, and solve problems previously reserved exclusively for humans (Hildebrand, 2019, p. 11). Contemporary definitions, such as that of Haenlein and Kaplan (2019, p. 5), describe AI as the “ability of a system to correctly interpret external data, learn from such data, and use those learnings to achieve specific goals and tasks through flexible adaptation.” Viewed as a system, AI uses data as inputs processed through machine learning, deep learning, and neural networks (Wisetri et al., 2021) to generate outputs—information crucial for decision-making or as input for other information systems (Paschen, Pitt, and Kietzmann, 2020).
In the context of marketing, artificial intelligence is defined as “the development of artificial agents that, based on information they have about consumers, competitors, and the given company, propose and/or carry out marketing activities that achieve the best marketing results” (Overgoor et al., 2019, p. 157). Academic research in this area, as noted by Thakur and Kushwaha (2023), dates back to works by Klingman et al. (1990) and Rodenrys (1990). The initial focus was on identifying barriers, later shifting toward applications in marketing activities, the evolution of data mining, market segmentation, predicting customer lifetime value, and more recently to trends such as robotics, voice-controlled AI, advanced analytics, and big data in marketing.
Current research on human–AI synergy, according to Bao, Gong, and Yang (2023), can be grouped into three main streams:
Collaboration in task solving, where AI takes on the role of facilitator, evaluator, expert advisor, or guide.
The impact of AI on user experience and perception.
Improving the design, settings, and governance of AI systems to ensure quality and trust.
Given that marketing relies heavily on data analytics, AI offers significant assistance in analyzing and visually presenting strategic campaign options (Huang and Rust, 2017), especially with unstructured data such as text, images, sound, and video (Liu, Singh, and Srinivasan, 2016). Its application brings benefits in segmentation, targeting, and positioning, enabling better satisfaction of the needs of different consumer groups by understanding their preferences (Lei and Moon, 2015). Personalization—highlighting consumer differences by adapting products to their preferences (Suprenant and Solomon, 1987)—is significantly simplified through the use of big data (Lakshmipriyanka et al., 2023). Examples such as Amazon and Netflix, which invest effort in personalizing the entire user experience (Kumar et al., 2019), illustrate a drive to deliver greater value. Netflix, for instance, uses AI to recommend movies based on users’ viewing histories and those of other users, as well as contextual information such as time of day or device (Kathayat, 2019). However, it is important to note that neglecting uniqueness can have a negative effect, as consumers may feel treated “like a number” (Longoni, Bonezzi, and Morewedge, 2019). In such a world, personalization—beyond improving user experience—also leads to higher conversions, engagement, content relevance, and overall advertising effectiveness (Efendioglu, 2023). Additional benefits for consumers include lower costs, a variety of service channels, innovation, and opportunities for creativity by shifting repetitive tasks to AI (Mustak et al., 2021).
Online communication with consumers via chatbots is one of the frequent applications of AI, enabling companies to be continuously available and interact with clients (Lakshmipriyanka et al., 2023), in a way that can be significantly more effective than less experienced sales representatives, depending on whether the AI system self-identifies as artificial (Luo, Tong, Fang, and Qu, 2019). Tools such as Siri, Cortana, or Bixby further simplify everyday tasks (Masnita et al., 2024), and ChatGPT (OpenAI, 2022) stands out for its ability to conduct complex interactions and generate content.
Despite this progress, the field of AI’s influence on consumer decision-making and market dynamics requires further research. Key aspects such as trust in AI systems, consumer autonomy, and ethical implications need greater focus in scientific work. Trust—defined in this context as “the extent to which a user is confident in and willing to act on the recommendations, actions, and decisions of an AI decision-support system” (Ashoori and Weisz, 2019, p. 2)—is important for understanding how trust in humans versus AI affects decision-making (Lee and See, 2004). The literature has considered the role of task characteristics (Castelo, Bos, and Lehmann, 2019), the transparency and reliability of AI models (Ashoori and Weisz, 2019), consumer AI literacy (Tully, Longoni, and Appel, 2025), and potential losses of control, privacy, or human contact (Ameen et al., 2021). To fully assess AI’s potential role in decision-making processes, it is necessary to view AI not only as a substitute for humans, but also as a complement (Van Oost and Reed, 2010).
The decision-making process—reducing multiple alternatives to one (Dreher and Tremblay, 2009)—is one in which AI can have influence at different stages (BaniHani, Alawadi, and Elmrayyan, 2024), throughout the entire decision funnel (Syam and Sharma, 2018).
Regarding their decisions, the level of AI use can vary (Dellaert et al., 2020), up to AI taking over the consumer’s entire decision (Steffel and Williams, 2018), often to avoid responsibility. AI has the potential to undermine autonomy, a key element of consumer choice (Wertenbroch et al., 2020), which is particularly pronounced when recommendations are not aligned with consumer preferences (Gonçalves et al., 2024). Theoretically, there is an optimal level of autonomy for AI algorithms, but it depends on context and individual characteristics (Fan and Liu, 2022).
In light of the above, and given that people often overestimate the benefits of making decisions independently while neglecting the costs (André et al., 2018), this project focuses on understanding the complex changes in how market logic functions when AI takes over certain phases of decision-making, depending on the characteristics of the decision, the brand, the industry, and the consumer. The consumer in this context changes significantly: they are more informed, more demanding, more sophisticated, and their needs are shaped differently (Klaus and Zaichkowsky, 2020). Interaction with AI can also lead to consumer alienation—for example due to errors in automated support or poor adaptation to specific consumer groups (Puntoni et al., 2020). Therefore, companies should focus not only on the human–AI relationship, but also on facilitating human–human relationships (Epp and Velagaleti, 2014), where AI serves as an interface to encourage social connectedness (Farooq and Grudin, 2016).
The proposed “AId” project directly responds to these needs for advancing knowledge. The project objectives are aimed at:
Understanding the impact of AI on consumers and the logic of how markets function: By exploring how AI affects consumer decision-making processes, the project focuses on understanding the key principles behind changing market logic (i.e., assumptions of market dynamics).
Understanding changes on the company side: Insights into changing assumptions of market dynamics will support understanding the key needs for adapting company strategies through ethically sound competitive brand strategies in AI-era markets.
Understanding key knowledge for managing markets: Given that after many years of focusing on understanding consumer decision-making processes and the factors influencing them (Kesić, 2006), these processes are changing due to AI integration, the project focuses on understanding the key knowledge and skills managers need to successfully manage markets in the AI era.
By investigating the complex interaction between artificial intelligence, consumer decision-making processes, and market strategies, the “AId” project will provide valuable insights that go beyond the current state of knowledge. By generating new knowledge about optimal models of human–AI collaboration, identifying factors that influence trust and acceptance of AI, and examining ethical aspects and impacts on consumer autonomy, the project will make a significant contribution to the academic community, policymakers, and business practice. In doing so, it will not only advance scientific understanding, but also create foundations for more responsible and effective development and application of artificial intelligence for the benefit of consumers and society as a whole.
In conclusion, the “AId” project is timely and relevant research with the potential to significantly contribute to understanding the complex relationship between artificial intelligence, human decision-making, and economic transformation. Its methodological breadth, clear purpose, strong justification, and innovative approach make it important for the development of science in the field.