1.1 Introduction
Artificial intelligence refers to the ability of computer-based systems to perform tasks that normally require human intelligence, such as learning, reasoning, problem-solving, pattern recognition, and decision making through the use of algorithms and large datasets (Russell & Norvig, 2021). In recent years, artificial intelligence has emerged as a transformative technological force that is redefining how businesses operate, compete, and create value across industries. Its growing relevance is particularly evident in entrepreneurship, where innovation, speed, adaptability, and efficient resource utilization are essential for survival and growth in highly dynamic markets.
Modern entrepreneurship is increasingly driven by digital technologies that enable firms to identify opportunities, respond to customer needs, and scale operations more effectively. Artificial intelligence plays a central role in this transformation by supporting data-driven decision making, automating routine processes, enhancing customer engagement, and improving risk management (Brynjolfsson & McAfee, 2017).
As a prelude to other parts of this study, this chapter will discuss the background upon which this study was initiated, the statement of problems that led to this study, the Aim and Objectives of the study. Others are significance of the study, scope of work, research hypothesis and questions, limitation of the study and definition of terms.
1.2 Background of Study
Historically, the adoption of artificial intelligence in modern entrepreneurship is closely linked to the broader evolution of computing technologies and the changing nature of business innovation. Artificial intelligence as a scientific and technological concept emerged in the mid-twentieth century, when early researchers sought to design machines capable of mimicking human intelligence through logical reasoning and symbolic processing. According to Russell and Norvig (2021), the initial phase of artificial intelligence development focused on rule-based systems and expert systems that were primarily applied in research institutions and large organizations due to high costs and limited computing power. During this period, entrepreneurial application of artificial intelligence was minimal, as the technology was largely inaccessible to small and emerging firms.
According to Russell and Norvig (2021), artificial intelligence involves the design of intelligent systems capable of performing tasks that ordinarily require human cognitive abilities, including learning, reasoning, and decision making. The integration of such intelligent systems into business operations has significantly altered how entrepreneurs identify opportunities, manage uncertainty, and create innovative solutions in competitive markets (Russell and Norvig, 2021). In the context of modern entrepreneurship, Brynjolfsson and McAfee (2017) reported that artificial intelligence has become a major driver of productivity, innovation, and scalability, particularly for firms operating in digital and technology-driven environments. They asserted that entrepreneurial firms increasingly rely on artificial intelligence to analyze large volumes of data, automate operational processes, and enhance customer engagement.
Globally, the adoption of artificial intelligence has been accelerated by advancements in computing power, data availability, and machine learning algorithms. The OECD (2019) stated that artificial intelligence is no longer confined to large multinational corporations but is increasingly accessible to small and medium-sized entrepreneurial ventures. This development has expanded the scope of entrepreneurship by lowering entry barriers and allowing innovative startups to compete effectively with established firms. However, the extent and effectiveness of artificial intelligence adoption vary significantly across regions, particularly between developed and developing economies.
Within emerging economies such as Nigeria, the rise of digital entrepreneurship has been closely linked to the expansion of the financial technology sector. PwC (2020) affirmed that Nigeria has become one of Africa's leading fintech hubs, driven by increasing digital adoption, a youthful population, and unmet financial inclusion needs. Fintech firms operate in a highly competitive and regulated environment, where efficiency, security, and customer trust are critical success factors. As a result, artificial intelligence is increasingly deployed for fraud detection, credit scoring, customer support automation, and personalized financial services.
Focusing on Opay Nigeria Limited, the company represents a modern entrepreneurial venture that leverages digital platforms to deliver payment and financial services to a wide customer base. Zhang, Li, and Chen (2021) contended that artificial intelligence adoption in entrepreneurial firms significantly influences innovation capability, operational performance, and competitive advantage, particularly in emerging markets. Despite these potential benefits, the adoption process is often constrained by challenges such as inadequate infrastructure, limited technical expertise, data privacy concerns, and regulatory uncertainties. McKinsey Global Institute (2018) stated that contextual factors such as institutional frameworks, market maturity, and human capital development play a critical role in shaping how artificial intelligence technologies are adopted and utilized by entrepreneurial firms. This study is set against the backdrop of the increasing reliance on artificial intelligence as a strategic tool for modern entrepreneurship and the need to understand how firms like Opay Nigeria Limited adopt and utilize artificial intelligence to enhance innovation, efficiency, and competitiveness within Nigeria's evolving digital economy.
1.3 Statement of Problems
Investigation revealed that the rapid diffusion of artificial intelligence in contemporary business environments is reshaping how entrepreneurial firms design products, interact with customers, manage risks, and achieve operational efficiency. In Nigeria's fast-growing fintech ecosystem, firms such as Opay Nigeria Limited operate in a highly competitive and technology-driven market where speed, accuracy, personalization, and trust are critical to survival.
A major problem confronting the adoption of artificial intelligence in modern entrepreneurship is the uneven level of organizational readiness in terms of infrastructure, technical expertise, and strategic alignment. In the context of Opay Nigeria Limited, artificial intelligence adoption is often influenced by challenges related to data quality, system integration, high implementation costs, and regulatory compliance within Nigeria's evolving digital and financial landscape.
Furthermore, the rapid pace of artificial intelligence development creates difficulties for entrepreneurs in keeping up with emerging tools and ensuring that employees possess the necessary skills to effectively utilize intelligent systems. It is against this backdrop that this study seeks to examine how artificial intelligence is adopted and integrated into modern entrepreneurial practices within Opay Nigeria Limited.
1.4 Aim and Objectives of Study
The aim of this study is to investigate the adoption of artificial intelligence in modern entrepreneurship and assess its impact on operational performance and innovation at Opay Nigeria Limited. The specific objectives of this study are:
- To examine the extent to which artificial intelligence is integrated into the operational processes of Opay Nigeria Limited.
- To identify the challenges associated with adopting artificial intelligence in modern entrepreneurship.
- To evaluate the effects of artificial intelligence adoption on innovation, decision making, and customer service in Opay Nigeria Limited.
- To recommend strategies for effective artificial intelligence adoption to enhance entrepreneurial performance.
1.5 Research Questions
The study came up with research questions so as to be able to ascertain the above stated objectives. The specific research questions for the study are stated below as follows:
- To what extent is artificial intelligence integrated into the operational processes of Opay Nigeria Limited?
- What are the major challenges faced by Opay Nigeria Limited in adopting artificial intelligence?
- How does artificial intelligence adoption affect innovation, decision making, and customer service at Opay Nigeria Limited?
- What strategies can be implemented to improve artificial intelligence adoption in modern entrepreneurial ventures?
1.6 Research Hypothesis
In order to pursue the objective of this study, the following generalized statements have been designed to guide and aids in obtaining the result for the experiment to be conducted. For this work, the null hypothesis will be represented with H0 while the alternative hypothesis will be represented with hypothesis H1.
Hypothesis One
- H0: Adoption of artificial intelligence has no significant effect on innovation, decision making, and operational performance in Opay Nigeria Limited.
- H1: Adoption of artificial intelligence significantly improves operational efficiency and decision-making in Opay Nigeria Limited.
Hypothesis One
- H0: Challenges such as inadequate technical skills and infrastructural constraints do not significantly affect the adoption of artificial intelligence in Opay Nigeria Limited.
- H1: Challenges such as inadequate technical skills and infrastructural constraints significantly affect the adoption of artificial intelligence in Opay Nigeria Limited.
1.7 Significance of Study
The outcome of this research will enable investors and financial stakeholders to make informed decisions regarding funding technology-driven ventures in the fintech sector. Also, the research will guide policymakers in developing regulations that support technology-driven entrepreneurship while ensuring data privacy and ethical practices.
Furthermore, the study will assist managers in designing strategies to optimize artificial intelligence adoption and improve decision-making processes.
Lastly, this research will serve as a reference for academic research, professional training, and practical innovation strategies within emerging digital economies.
1.8 Scope of Study
The scope of the research is focused on the adoption of artificial intelligence in modern entrepreneurship with a specific focus on Opay Nigeria Limited, Lagos State.
1.9 Limitations of the Study
During the course of this study, there were some problems encountered which stood as limitations to the research work. Some of the limitations include:
- Time Constraint: The time frame given to accomplish this project was very short due to school academic calendar and it was carried out under pressure which made the researcher not to implement some necessary features.
- Financial Constraint: Insufficient fund tends to impede the efficiency of the researcher in sourcing for the relevant materials, literature or information and in the process of data collection (internet, questionnaire and interview).
- Initial Cooperation Delay from Respondents: A particular limitation of this work came as a result of the respondent refusal to offer their cooperation at the initial time they were contacted. This contributed in making the success of this research study difficult.
1.10 Definition of Terms
Artificial Intelligence (AI):
Artificial intelligence is the ability of machines to perform tasks that typically require human intelligence, including learning, reasoning, and problem-solving (Russell & Norvig, 2021).
Entrepreneurship:
Entrepreneurship is the process of identifying, developing, and bringing a vision or business idea to life, often by taking calculated risks to achieve innovation and profitability (Hisrich et al., 2017).
Adoption:
Adoption refers to the process through which individuals or organizations accept, implement, and integrate new technologies or practices into their routine operations (Rogers, 2003).
Modern Entrepreneurship:
Modern entrepreneurship involves the use of contemporary technological, managerial, and innovative practices to establish and grow businesses in rapidly changing markets (Brynjolfsson & McAfee, 2017).
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