Project – Artificial Intelligence and the Changing Nature of Workplace Decision-Making: A Study of Selected Employees in Guaranty Trust Holding Company Plc, Lagos

CHAPTER ONE

INTRODUCTION

1.1 Background to the Study

Artificial Intelligence (AI) has emerged as one of the most influential technological developments shaping contemporary organisations and the nature of work. Unlike earlier generations of workplace technologies that primarily focused on automating repetitive physical or administrative tasks, contemporary AI systems are increasingly capable of analysing large volumes of information, recognising patterns, generating recommendations, predicting outcomes, communicating through natural language and supporting complex organisational activities. Consequently, AI is no longer viewed solely as a technical tool operated by information technology specialists; it is increasingly becoming part of everyday managerial and employee activities, including planning, risk assessment, customer management, financial analysis, resource allocation and decision-making. The International Monetary Fund (IMF) observes that AI has the capacity to enhance productivity, improve predictions and strengthen decision-making, although its effects differ according to occupations, skills and institutional preparedness (Cazzaniga et al., 2024).

The growing importance of AI is associated with the broader digital transformation of organisations. Organisations increasingly operate in environments characterised by large volumes of digital data, rapid changes in customer expectations, intense competition and the need for faster and more evidence-based decisions. In such environments, traditional approaches to decision-making based exclusively on individual experience, intuition and manually processed information may be insufficient. AI provides organisations with the ability to process information at a speed and scale that exceeds ordinary human capacity. Machine-learning systems can identify patterns from historical data, predictive systems can estimate possible future outcomes, and generative AI applications can support employees in producing reports, summarising information, developing alternatives and communicating recommendations. Thus, the changing nature of AI is not simply about replacing human activities but about altering how employees obtain information, evaluate alternatives and arrive at decisions.

The workplace implications of AI are therefore broader than automation. The International Labour Organization (ILO) argues that generative AI is more likely to augment many occupations than completely eliminate them because AI can automate particular tasks while leaving other components of jobs dependent on human capabilities. The ILO further notes that AI can alter work intensity, autonomy and the quality of employment (Gmyrek, Berg, & Bescond, 2023). This perspective is particularly important for understanding workplace decision-making because employees may increasingly work in partnership with AI rather than simply being replaced by it. An employee may, for example, use an AI-generated analysis as an input into a decision while retaining responsibility for interpreting the information, considering organisational policies and exercising professional judgement.

Decision-making is a central function of organisational management. Every organisation makes decisions concerning customers, employees, finance, operations, marketing, risk, compliance and strategic development. The quality and timeliness of these decisions can influence organisational performance and competitiveness. Traditionally, organisational decisions have depended heavily on managerial experience, professional knowledge, organisational rules and information obtained from employees and established reporting systems. However, the increasing availability of big data and advanced analytics has changed the information environment within which decisions are made. AI systems can analyse structured and unstructured data and produce insights that may not be easily identified through conventional approaches.

The emergence of AI-supported decision-making has consequently introduced a new relationship between employees and technology. Employees may increasingly become interpreters, supervisors and evaluators of machine-generated information. Jarrahi (2018) argues that AI and human decision-makers can operate in a complementary relationship because humans possess contextual understanding, intuition, ethical judgement and the capacity to deal with ambiguity, while AI systems are particularly strong in computational analysis and the identification of patterns in large datasets. This human-AI relationship suggests that the changing nature of workplace decision-making should not be examined only in terms of whether AI makes decisions independently. It should also be examined in terms of how AI influences the information employees receive, the alternatives they consider, their confidence in decisions and the degree to which they depend on technological recommendations.

The development of AI is especially significant in the financial services industry. Financial institutions generate and process enormous quantities of data relating to customers, transactions, accounts, financial risks, market activities and regulatory requirements. Such an environment creates opportunities for AI applications in fraud detection, credit assessment, customer service, risk management, financial forecasting, compliance monitoring and operational optimisation. Arslanian and Fischer (2019) identify AI as one of the technologies reshaping financial services, with applications extending across different aspects of financial operations. The Central Bank of Nigeria has similarly recognised artificial intelligence, big data, cloud computing, hyper-automation and other emerging technologies as important developments influencing financial services (Usoro, 2022).

The Nigerian banking industry has experienced substantial technological transformation. Digital banking, electronic payments, mobile banking, automated service channels, data analytics and fintech innovations have changed how banks interact with customers and manage their operations. Samuel-Ogbu (2022) notes that technological development has significantly transformed Nigeria’s banking system by improving the speed, efficiency, security and convenience of financial services. The Nigerian banking industry has consequently become an important environment for the application and evaluation of emerging technologies.

The increasing relevance of AI in Nigeria is also reflected in national policy. Nigeria’s National Artificial Intelligence Strategy recognises AI as an important technology for socioeconomic development and provides a strategic framework for promoting AI research, adoption, innovation and responsible utilisation. The strategy highlights the need to develop appropriate infrastructure, human capacity and institutional arrangements for Nigeria to benefit from AI while managing associated risks. The establishment and activities of the National Centre for Artificial Intelligence and Robotics further demonstrate the country’s growing institutional interest in AI research, development and adoption.

The financial sector provides a particularly important setting for examining AI because many decisions within the sector involve financial consequences, customer interests, regulatory obligations and organisational risks. AI-assisted decisions concerning fraud alerts, customer segmentation, credit evaluation, transaction monitoring and service recommendations may affect both employees and customers. Although AI can improve speed and analytical capability, its recommendations may also contain errors or reflect limitations in the data used to train or operate the system. Consequently, employees must determine when to accept, question, modify or reject AI-generated recommendations. This introduces questions concerning employee trust, human oversight, transparency and accountability.

The issue of trust is particularly significant. Employees may accept AI recommendations because they perceive the system as more objective or analytically capable than human judgement. Conversely, employees may resist AI recommendations when they do not understand how the system arrived at a particular conclusion. Glikson and Woolley (2020), in their systematic review of trust in AI, demonstrate that trust is an important component of human-AI interaction and that factors such as system performance, transparency and the nature of the task influence people’s willingness to rely on AI. In workplace decision-making, inappropriate levels of trust may create problems. Excessive trust can result in automation bias, whereby employees accept machine recommendations without adequate scrutiny, whereas insufficient trust can prevent organisations from obtaining the full benefits of AI.

AI can also influence employee autonomy. Traditional workplace decision-making gives employees varying degrees of discretion to interpret information and determine appropriate actions. When AI systems provide recommendations or automatically prioritise tasks, employees’ discretion may change. In some circumstances, AI may empower employees by providing timely information and analytical support. In other circumstances, employees may feel constrained by algorithmic recommendations, especially where organisational systems expect employees to follow technology-generated outputs. The ILO’s observation that generative AI can affect work intensity and autonomy demonstrates why AI adoption needs to be examined not merely as a productivity issue but also as a workplace and organisational issue (Gmyrek, Berg, & Bescond, 2023).

Another important issue is the quality and reliability of information used by AI systems. AI systems depend heavily on data. Poor-quality, incomplete or biased data can produce unreliable outputs. In organisational settings, this can affect decisions relating to customers, employees and business operations. NIST’s Artificial Intelligence Risk Management Framework emphasises the importance of managing AI-related risks and promoting trustworthy and responsible AI systems. The framework identifies governance, mapping, measurement and management as important functions in responsible AI risk management (Tabassi, 2023).

The problem of algorithmic bias is particularly important in employee decision-making. An AI system trained on historical data may reproduce patterns present in that data, even where those patterns are undesirable. If employees rely unquestioningly on such systems, organisational decisions may become influenced by hidden biases. For this reason, AI-supported decision-making requires human oversight, appropriate organisational controls and employee understanding of the limitations of AI. The challenge is therefore not simply whether AI should be used but how employees should interact with AI and how organisations should ensure that technology-supported decisions remain accurate, fair, explainable and consistent with organisational objectives.

The relationship between AI and productivity also requires attention. AI can potentially reduce the time required to analyse information, generate reports, identify anomalies and perform routine cognitive tasks. The IMF estimates that AI has substantial potential to affect global employment and productivity, with emerging economies facing both opportunities and challenges depending on their digital infrastructure, human capital and institutional preparedness (Cazzaniga et al., 2024). For Nigerian organisations, the productivity benefits of AI may be significant, but they depend on the ability of employees to understand and effectively use AI-enabled systems.

This issue is especially relevant to large financial holding companies operating in Lagos. Lagos is Nigeria’s major commercial and financial centre and hosts numerous financial institutions, technology firms and corporate headquarters. The concentration of financial and technology activities makes the city an appropriate context for investigating technological changes in workplace practices. Guaranty Trust Holding Company Plc (GTCO) represents a relevant organisational context because its operations span financial services and depend substantially on information, digital systems, data and technology. The organisation’s workforce operates within a highly competitive financial environment in which the speed and quality of decisions can have important implications for customer service, risk management, operational efficiency and business performance.

The study therefore focuses on selected employees of Guaranty Trust Holding Company Plc in Lagos to examine how AI is influencing workplace decision-making. The focus is not limited to whether employees use AI. Rather, the study is concerned with the changing decision-making process: how employees obtain and evaluate AI-generated information, whether AI influences their speed of decision-making, whether employees trust AI recommendations, whether AI changes their level of autonomy, and whether employees continue to exercise human judgement when using AI-supported systems.

The importance of this investigation is reinforced by the increasing sophistication of AI technologies. Generative AI, machine learning, predictive analytics and intelligent automation have expanded the range of tasks that technology can support. Unlike conventional information systems that generally present information according to predetermined rules, newer AI systems can generate recommendations and content and can interact with users using natural language. This means that employees may increasingly engage with technology in ways that resemble collaboration rather than simple tool use. Raisch and Krakowski (2021) describe this emerging relationship through the concept of automation-augmentation paradox, explaining that organisations must balance automation of tasks with augmentation of human capabilities. This perspective is particularly applicable to workplace decision-making because excessive automation may reduce human involvement while effective augmentation may improve human performance.

At the same time, AI adoption creates new responsibilities for employees and managers. Employees need sufficient digital and analytical competencies to interpret AI outputs, recognise errors and make appropriate decisions. Managers need to establish policies concerning acceptable AI use, data protection, accountability and human oversight. Organisations also need to provide training so that employees understand both the capabilities and limitations of AI. The IMF similarly identifies digital infrastructure and digital skills as important conditions for emerging economies to benefit from AI (Cazzaniga et al., 2024).

The central issue, therefore, is that AI is changing not only what employees do but also how they think, evaluate information and make workplace decisions. This transformation presents significant opportunities for faster, data-driven and potentially more accurate decision-making, but it also creates concerns regarding employee dependence on technology, trust, accountability, transparency, autonomy and professional judgement. Understanding these changes at the organisational level is important for ensuring that AI adoption produces meaningful benefits without weakening human responsibility.

It is against this background that this study investigates Artificial Intelligence and the Changing Nature of Workplace Decision-Making among Selected Employees in Guaranty Trust Holding Company Plc, Lagos. The study seeks to provide empirical evidence on the relationship between AI use and workplace decision-making and to determine whether AI primarily functions as a substitute for employee judgement or as an augmentation mechanism that strengthens employees’ decision-making capabilities.

1.2 Statement of the Problem

Artificial Intelligence is increasingly becoming embedded in organisational activities, creating significant changes in how employees perform their jobs and make decisions. Although AI offers opportunities for faster analysis, improved prediction, automation and enhanced productivity, its increasing use also creates concerns regarding how much decision-making authority should remain with human employees. The fundamental problem is that organisations may adopt AI systems for efficiency without fully understanding how such systems change employees’ judgement, autonomy, confidence and responsibility in decision-making.

In financial services, this problem is particularly important because workplace decisions can have direct consequences for customers, organisational resources, regulatory compliance and financial risk. Employees may increasingly depend on algorithmic outputs when analysing information, identifying risks, evaluating customers or responding to operational problems. While AI-generated recommendations can provide useful insights, they are not necessarily infallible. Errors in data, inappropriate assumptions, algorithmic bias or system limitations may produce misleading recommendations. If employees accept AI outputs without adequate verification, the organisation may experience a shift from informed human decision-making to excessive technological dependence.

A related problem is the changing role of employee judgement. Traditional organisational decision-making generally requires employees to combine formal procedures, professional knowledge, experience and contextual understanding. AI introduces another source of decision input: machine-generated analysis or recommendation. The employee must therefore decide whether to accept the recommendation, seek additional information or exercise independent judgement. Where employees lack adequate AI literacy, they may either over-rely on AI or avoid useful AI tools altogether. Both situations may reduce the effectiveness of organisational decision-making.

There is also a problem concerning trust. Employees may regard AI systems as objective and highly accurate because they are based on large datasets and advanced computational processes. However, an AI system’s output is dependent on the quality and relevance of its data and design. Excessive trust can encourage automation bias, while insufficient trust may prevent effective AI utilisation. The challenge for organisations is consequently to establish an appropriate balance between employee judgement and technological recommendations. NIST’s AI Risk Management Framework emphasises the need for organisations to identify, assess and manage risks associated with AI use in order to promote trustworthy AI systems (Tabassi, 2023).

Another problem concerns employee autonomy. AI-supported systems may improve employees’ capacity to make decisions by giving them access to information that would otherwise require substantial time to obtain and analyse. However, where employees are expected to follow automated recommendations, their discretionary authority may become narrower. This creates uncertainty about whether AI is empowering employees or gradually transferring decision-making authority from employees to algorithms. The ILO’s finding that AI can affect work intensity and autonomy further illustrates the need to examine the workplace consequences of AI beyond job replacement (Gmyrek, Berg, & Bescond, 2023).

In Nigeria, the problem is further complicated by differences in digital infrastructure, employee competencies and organisational readiness. Although Nigeria has developed a National Artificial Intelligence Strategy and is promoting AI adoption, the effective use of AI requires adequate infrastructure, skilled personnel and responsible governance. The IMF similarly notes that emerging economies may face difficulties in capturing AI’s benefits because of limitations in infrastructure, skills and institutional preparedness (Cazzaniga et al., 2024). Thus, the mere availability of AI technology does not necessarily mean that employees can use it effectively for workplace decision-making.

There is also a contextual research gap. A substantial body of international literature examines AI adoption, automation, productivity, trust in AI and the future of work. However, much of this literature is conducted in advanced economies or examines AI at broad organisational or labour-market levels. Less empirical attention has been directed towards how employees in Nigerian financial organisations actually experience AI-supported decision-making, particularly regarding the balance between AI recommendations and human judgement. Existing Nigerian literature has established that technological developments are transforming banking operations, but more specific empirical investigation is required into the employee-level decision-making consequences of AI adoption. For example, Samuel-Ogbu (2022) documents the broad transformation of Nigeria’s banking system through digital technologies, while Usoro (2022) discusses AI among emerging technologies shaping financial services.

Consequently, an important unanswered question is whether AI is changing workplace decision-making among employees in ways that improve decision speed and quality, or whether it is creating new forms of dependence, uncertainty and reduced professional autonomy. It is also necessary to establish whether employees perceive AI as a decision-support mechanism or as a technology that increasingly substitutes for human judgement.

The absence of sufficient organisation-specific evidence creates a practical problem for managers. Without understanding how employees interact with AI in their daily decision-making, management may find it difficult to determine appropriate levels of employee training, human oversight and AI governance. There is a need for empirical evidence that reflects employees’ experiences within a Nigerian financial-services environment.

The problem addressed by this study, therefore, is the limited empirical understanding of how artificial intelligence is changing workplace decision-making among employees in Guaranty Trust Holding Company Plc, Lagos, particularly in relation to decision-making efficiency, reliance on AI recommendations, employee judgement, trust and autonomy. Addressing this problem will provide evidence that can assist organisations in designing AI adoption practices that combine technological capabilities with human expertise and accountability.

1.3 Aim of the Study

The main aim of this study is to examine the relationship between Artificial Intelligence and the changing nature of workplace decision-making among selected employees of Guaranty Trust Holding Company Plc, Lagos.

1.4 Objectives of the Study

The specific objectives are to:

1. examine the extent to which employees of Guaranty Trust Holding Company Plc utilise Artificial Intelligence in workplace activities;
2. determine the influence of Artificial Intelligence on the speed and efficiency of workplace decision-making among employees;
3. examine the influence of AI-generated recommendations on employees’ decision-making processes;
4. assess the effect of Artificial Intelligence on employee autonomy and professional judgement in workplace decision-making; and
5. examine the challenges associated with the use of Artificial Intelligence in workplace decision-making among selected employees of Guaranty Trust Holding Company Plc, Lagos.

1.5 Research Questions

The study will answer the following questions:

1. To what extent do employees of Guaranty Trust Holding Company Plc utilise Artificial Intelligence in workplace activities?
2. How does Artificial Intelligence influence the speed and efficiency of workplace decision-making among employees?
3. To what extent do AI-generated recommendations influence employees’ decision-making processes?
4. How does Artificial Intelligence affect employee autonomy and professional judgement in workplace decision-making?
5. What challenges are associated with the use of Artificial Intelligence in workplace decision-making among selected employees of Guaranty Trust Holding Company Plc, Lagos?

1.6 Research Hypothesis

The following null hypothesis will be tested at the 0.05 level of significance:

H₀: There is no significant relationship between Artificial Intelligence utilisation and workplace decision-making effectiveness among selected employees of Guaranty Trust Holding Company Plc, Lagos.

1.7 Significance of the Study

This study will be significant to management of Guaranty Trust Holding Company Plc because it will provide evidence concerning how employees experience and utilise AI in workplace decision-making. The findings may assist management in determining whether AI applications are improving decision speed and efficiency or creating challenges relating to employee dependence, trust, autonomy and judgement.

The study will also be useful to employees because it will draw attention to the changing competencies required in an AI-enabled workplace. As AI increasingly supports analytical and cognitive tasks, employees may need to develop stronger digital literacy, critical thinking, analytical reasoning and AI-evaluation skills. Understanding these requirements can help employees adapt to technological changes while maintaining appropriate professional judgement.

The study will be relevant to human resource managers and organisational development practitioners. Findings may assist in designing training programmes that prepare employees to work effectively alongside AI systems. Rather than focusing only on technical training, organisations may need to develop employees’ ability to evaluate AI outputs, identify potential errors and make responsible decisions.

The study will also benefit policymakers and regulators in Nigeria, particularly those concerned with financial services and technological transformation. Evidence from the study may contribute to discussions on responsible AI adoption, employee competencies, transparency and human oversight in financial institutions.

Furthermore, the study will contribute to academic literature on AI and organisational behaviour by providing empirical evidence from a Nigerian financial-services context. It will complement broader international research on human-AI collaboration, workplace automation and organisational decision-making by focusing specifically on employees’ decision-making experiences.

Finally, the study will be useful to future researchers who may wish to investigate AI adoption, algorithmic decision-making, employee performance, digital transformation, AI governance and the future of work in Nigeria.

1.8 Scope of the Study

The study focuses on Artificial Intelligence and the changing nature of workplace decision-making among selected employees of Guaranty Trust Holding Company Plc in Lagos.

Conceptually, the study focuses on Artificial Intelligence utilisation as the major independent variable and workplace decision-making as the dependent variable. Particular attention will be given to AI-supported information analysis, AI-generated recommendations, decision-making speed and efficiency, employee judgement, trust and autonomy.

Geographically, the study is limited to selected employees of Guaranty Trust Holding Company Plc operating in Lagos. The study does not attempt to generalise its findings to all financial institutions in Nigeria without appropriate qualification.

The study is also concerned with employees’ workplace experiences rather than the technical development or programming of AI systems. It therefore focuses on the organisational and behavioural implications of AI rather than the engineering characteristics of specific algorithms.

1.9 Operational Definition of Terms

Artificial Intelligence (AI): The capability of computer-based systems to perform tasks associated with human cognitive functions, including learning, prediction, analysis, pattern recognition, language processing and recommendation.

AI Utilisation: The extent to which employees use AI-enabled technologies or applications to support their workplace activities and decisions.

Workplace Decision-Making: The process through which employees identify problems, evaluate information, consider alternatives and select courses of action within an organisational setting.

AI-Generated Recommendation: An output, suggestion, prediction or proposed course of action produced by an AI-enabled system to support an employee’s decision.

Decision-Making Effectiveness: The extent to which workplace decisions are timely, accurate, appropriate, informed and capable of achieving intended organisational outcomes.

Employee Autonomy: The degree of discretion and independence employees have in determining how workplace tasks and decisions are performed.

Human Judgement: The employee’s ability to apply professional knowledge, experience, contextual understanding, ethical considerations and critical thinking when making decisions.

AI Trust: The extent to which employees have confidence in the reliability, accuracy and usefulness of AI-generated information or recommendations.

AI-Employee Collaboration: The interaction between employees and AI systems in which technology provides analytical or decision-support capabilities while employees retain responsibility for interpreting information and making or approving decisions.

Workplace Automation: The use of technology, including AI, to perform tasks or processes that were previously undertaken wholly or partly by human employees.

1.10 Organisation of the Study

The study is organised into five chapters. Chapter One presents the introduction, background to the study, statement of the problem, aim and objectives, research questions, research hypothesis, significance, scope and operational definition of terms. Chapter Two will review relevant conceptual, theoretical and empirical literature on Artificial Intelligence and workplace decision-making. Chapter Three will present the research methodology, including the research design, population, sample and sampling technique, instrument for data collection, validity and reliability, data collection procedure and method of data analysis. Chapter Four will present and analyse the data collected for the study and test the research hypothesis. Chapter Five will present the summary of findings, conclusion and recommendations.

Project – Artificial Intelligence and the Changing Nature of Workplace Decision-Making: A Study of Selected Employees in Guaranty Trust Holding Company Plc, Lagos