Introduction

Today, the world is crowded with challenges such as resource scarcity, intensifying conflicts, and economic competition among nations in the race to seize opportunities. Institutional governance has emerged as one of the vital topics that have garnered increasing attention in light of the growing role of technology, particularly in the field of artificial intelligence. This focus is aimed at developing and directing institutions, improving decision-making, and gaining competitiveness to achieve sustainable development.

Accordingly, the subject of leveraging artificial intelligence may be of great importance in serving the organization and its governance, as it represents the most effective digital technology tool in the lives of organizations in the third millennium.

This study will therefore focus on the subject of institutional governance, especially in its administrative and financial aspects, with the potential of employing artificial intelligence as an effective tool to reach good governance standards and strengthen the foundations of organizations to sustain their economic and social roles in development. Building a tight, purposeful relationship between technological data and management signifies that management has succeeded on its path towards sustainability and enhancing competitiveness.

However, applying artificial intelligence within organizations is not that simple. Success requires substantial effort from management, particularly in its interaction with a world that is open to everything, where nothing remains hidden. Secrets, knowledge disclosure, and transfer have become routine and difficult to control. This is clearly reflected in the dynamics between the United States and China—and even Europe—especially in light of the recent changes made by the new U.S. government in 2025 regarding the exposure and rapid transfer of knowledge. This applies both at the level of individual institutions and entire states globally.

In the Arab world, the issue of knowledge transfer—particularly on the technical and practical levels—has been more challenging due to the preoccupation of Arab states with other issues that hinder their institutions from effectively engaging with emerging technologies. This distraction results in a weakness or delay in keeping pace with modernization and good governance, as well as building a sustainable future vision. However, this does not negate the existence of promising and commendable experiences in some Arab countries, especially the Gulf States, which will be referred to within this study.

To provide a clear framework for this topic, its sections and chapters will be addressed according to a suitable research methodology. This topic is predominantly descriptive and interpretative in nature, rather than quantitative, as its measurement is linked to non-quantitative concepts. It is worth noting that quantitative data for the topic is still largely unavailable or unconfirmed by researchers and remains in its early stages.

Accordingly, this study will cover the subject through three main chapters. The first will present the methodology and a review of previous studies, including references to international and Gulf experiences. The second chapter will present the concepts and aspects related to institutional governance and artificial intelligence. The third chapter will be dedicated to examining the levels of compatibility and contradiction between governance and artificial intelligence and the reasons behind them. Finally, the study will conclude with the main findings and recommendations.

Chapter One Methodology and Literature Review

This chapter includes a presentation of the methodology, encompassing the research problem, significance, objectives, hypotheses, research model, and more. In addition, it will review several previous studies that addressed one or more aspects of the research topic to understand what has already been discussed within the field of governance and artificial intelligence. This chapter will also highlight the experiences of certain countries that have been ahead of others in the Arab world in dealing with artificial intelligence and its applications.

First: Research Methodology

Research Problem:

: The research problem revolves around the extent to which compatibility exists between the use of artificial intelligence in institutional governance and an organization’s ability to increase alignment between the elements of governance and the characteristics of artificial intelligence, which it employs as tools to achieve success in institutional governance. This, in itself, is not an easy task. If the organization fails to achieve such alignment, it will face significant challenges. One of the most notable issues in the application of AI in governance is the digital or informational disruption caused by the massive amount of data used in the system. This often results in numerous errors, manipulations, and forgeries, especially in financial areas.

Problems may also extend to other areas, such as social and environmental aspects. This requires organizations to carefully control the use of automation and AI, avoiding widespread and rapid implementation due to the potentially difficult consequences.

These challenges and obstacles can be reflected in several key research questions, including:

1.Does the lack of privacy and human management in AI pose serious problems for organizations and their governance?

2.To what extent can data manipulation or misinformation affect decision-making and the soundness of those decisions?

3.Does the rapid advancement of AI disrupt governance roles and lead to a loss of control over institutional management?

4.To what extent do some governance stakeholders exploit the system for personal interests over shared interests? What is the impact of this on the performance of institutional governance?

5.Does the modernization of development institutions require an increased use of artificial intelligence?

Research Significance:

The importance of this topic stems from the increasing and accelerating use of artificial intelligence across all sectors, especially in public and private business organizations. This rapid growth necessitates organizations to prepare and effectively plan for dealing with digital management technologies and to enhance transparency as a core principle in institutional governance—particularly in production and administrative fields—while confronting the associated challenges. This is critically important for building sound and sustainable development pathways for organizations.

Research Objectives

Based on the questions raised in the research problem and the importance of the topic regarding the relationship between artificial intelligence and institutional governance, the research objectives are as follows:

1.To present the relationship between governance and artificial intelligence in terms of concepts, components, and core characteristics, while indicating the level of integration or contradiction between their roles, particularly in using AI in institutional governance.

2.To employ inductive and deductive analysis of selected views and studies related to the topic, in order to clarify the paths of institutional governance using AI.

3.To assess the degree of alignment or harmony between governance components and AI characteristics—or the lack thereof—and the implications in both cases.

4.To present key findings as viewpoints open to discussion, debate, and modification, with potential benefits and applications for organizations.

5.To offer several proposals and recommendations that may benefit stakeholders.

Research Hypothesis:

The hypothesis, which will be tested for validity based on reviewing relevant previous studies and expert opinions, states the following: (Governance principles can significantly align with the characteristics and elements of artificial intelligence application in institutions).

Research Model

The research model illustrates the relationship between the two main variables—governance and artificial intelligence—and their respective principles and characteristics. This model serves as the basis for examining their compatibility or contradiction. The diagram below illustrates this relationship.

Figure 1.The Relationship Between Governance Principles and Artificial Intelligence

Research Method

: It can be said that the most appropriate research methodology to achieve the objectives of this study and test its hypothesis is the inductive followed by the deductive method. This approach will explore the views and ideas presented regarding governance and artificial intelligence and evaluate them. Artificial intelligence will be considered a dependent variable influenced by the independent variable representing institutional governance.

Second: Previous Studies and Some International and Arab Experiences and Interests: To examine the key findings from studies, research, and international experiences, a number of these efforts will be reviewed, highlighting the levels of artificial intelligence usage in various national activities:

1.George Michel's Study (2023), titled "The Role of Artificial Intelligence in Corporate Governance" This study focused on the significant role of artificial intelligence in corporate governance and its capacity to increase productivity and organizational efficiency. It argued that this is achieved through process automation and enhanced decision-making. AI, therefore, can align with governance principles and enhance an organization’s competitiveness. The researcher emphasized AI's role in increasing data analytical capacity, particularly in the financial domain of companies. The study also highlighted AI's contribution to developing organizational oversight, supervision, and auditing functions.

The study’s main recommendation was for corporate governance to adopt digital management and utilize AI to develop and sustain organizational services.

2.Houria Cheriet’s Study (2023), titled "The Organization and the Challenges of the New Millennium: A Reading in Light of Organizational Thought" This study examined contemporary organizational concepts based on the evolution of organizational theory, aiming to revise certain classical assumptions and highlight the key challenges of the third millennium. Among the most critical challenges identified were the emergence of Web 4.0 technologies and the shift towards digital business management.

The researcher concluded that it is essential to move beyond rational illusion to rediscover organizations and adopt strategic foresight research that addresses internal and external environmental challenges. The study recommended that AI should be ethically framed to function as a tool—not a decision-maker—within organizational activities, to avoid risks. This means preventing AI from dominating the financial and business sectors.

3.Mona El-Sayed Adel Abdelshafi Ammar’s Study (2023), titled "Corporate Governance Through Artificial Intelligence Technology" This study addressed the recent global advancements in developing technological tools across various life sectors. The latest of these advancements is artificial intelligence, which has been widely integrated into management and finance, especially in corporate governance. AI is utilized to implement governance principles and protect the rights and interests of the organization’s stakeholders. It also aids in increasing corporate transparency and information disclosure.

Despite highlighting the need for legal frameworks to address AI-related liabilities, the study extensively presented AI’s benefits in governance, such as reducing discrimination among stakeholders, ensuring equal opportunities, minimizing fraud and financial corruption, and achieving justice. These benefits, the study argued, can be realized through robots simulating governance-related human roles. It recommended the development of AI-specific legislation to facilitate its use in community services.

4.Giro Cocorio’s Study (2022), titled "Digital Economy: In Search of New Governance Mechanisms" The study’s summary highlighted the global expansion of the digital economy and its applications, raising essential ethical questions about digital technology usage, information management, and regulation (referring to AI).

The study aimed to identify new principles for effective AI governance policies. It noted the economic shift from industrial to digital economies, which necessitates balancing data usage for trade with the societal benefit of privacy protection. In Western contexts, personal privacy is considered a human right, whereas Eastern perspectives view individual values as collective assets serving public interests. The study thus advocated for a new model that transcends individualism and returns to a culture of participatory management.

5.Raafat Al-Awadhi and Dima Abu Latifa’s Study (2020), titled "The Impact of Employing Artificial Intelligence on Developing Administrative Work in Light of Governance: A Field Study on Palestinian Ministries in the Gaza Governorates" This study examined how AI impacts administrative development in organizations by applying governance principles. The researchers used a descriptive-analytical method on a random sample of administrative staff from ministries and main departments in Gaza.

The study used a questionnaire to test its hypotheses.

Key findings included:

1.Employee perception of AI employment in administrative work was not high, with only 62% acknowledging its use. Respondents emphasized that administrative development is strongly linked to educational qualifications.

2.Commitment to governance principles, especially participation, was high—reaching 85%.

The main recommendations called for expanding AI application in administrative development and encouraging staff training.

Current Study and Previous Research (Differences and Similarities): Before reviewing the real-world application of AI in some Arab countries and its global status, it is important to note that previous studies focused on the positive aspects of AI while briefly touching on potential risks. In contrast, this study provides a comprehensive and concise concept of governance, examining possible compatibility between governance principles and AI characteristics. It identifies whether this compatibility is full or partial. It will also outline the areas of contradiction or misalignment between governance and AI—something not addressed in previous studies or in practical experiences.

Third

The Level of Artificial Intelligence and Its Applications Globally and in the Arab World: Despite the variance in quantitative data about global AI activities and applications, indicators used by leading AI-active countries—according to WIPO and HAI reports (2023)—rank the top AI-advanced countries as follows: Switzerland, the United States, Sweden, the United Kingdom, the Netherlands, Singapore, Finland, China, France, and Japan.

In the Arab world, the United Arab Emirates, Saudi Arabia, Qatar, and Egypt lead the way, followed by Tunisia, Morocco, and Bahrain.

It is worth noting that AI rankings rely on more than 155 criteria within major indicators such as government strategy, R&D and expertise, infrastructure, operational environment, and commerce.

Section Two Institutional Governance and Artificial Intelligence: Basic Concepts

First

The Concept of Corporate Governance

As is commonly known, concepts related to any subject typically appear in the form of definitions that express the essence of the term. Regarding the definition of corporate governance, its synonyms include institutional governance, institutional control, good governance, among others, all conveying a closely related meaning.

Hence, focus will be given to definitions considered as references, particularly those provided by internationally relevant institutions and widely acknowledged by authors and researchers.

One of the most prominent definitions is provided by the International Finance Corporation (IFC), which offers a concise and comprehensive definition, stating that governance is a system for managing companies through which their operations are controlled (Tariq, 2007).

The Organization for Economic Cooperation and Development (OECD) refers to governance as a set of relationships that connect stakeholders within a company to establish its objectives, execution tools, and performance monitoring (Holmes, 2022).

Others describe governance as the principles and systems that regulate relationships among various stakeholders in the company—particularly between the top authority and the rest of the stakeholders—in order to ensure optimal protection of everyone's interests (George Michel, 2023). Optimal protection implies that the system or principles are characterized by responsibility, integrity, and transparency.

Thus, it is evident from the above that these definitions agree on protecting the interests of stakeholders through integrity and transparency in the behavior of all parties, especially the top authority (Board of Directors).

Accordingly, it can be said that the definitions and concepts of governance focus on the integrity, responsibility, and transparency of behaviors and actions to protect the interests of all. Governance, in a simple yet comprehensive manner, aligns with the meaning of the Qur’anic verse:

"So remain on a right course as you have been commanded, [you] and those who have turned back with you [to Allah], and do not transgress. Indeed, He is Seeing of what you do." (Surah Hud, Ayah 112).

The verse is addressed to the Prophet Muhammad (peace be upon him) and all Muslims, emphasizing adherence to divine commands and righteous guidance. God Almighty commands justice and excellence, which means doing good in an excellent manner. All of this represents an ideal definition of governance in terms of protecting all parties' interests, ensuring integrity, and regulating behavior.

Second

The Concept and Definition of Artificial Intelligence (AI)

The concepts and definitions of artificial intelligence are also numerous and varied, as presented in previous studies and by researchers and specialists. The most prominent definitions include:

•According to Oxford University, artificial intelligence (AI) is the development of computer systems to perform tasks that typically require human intelligence, such as perception, speech recognition, and decision-making.

•Boden (2018) defines AI as a computer-programmed device using algorithms and procedures designed to perform a specific task according to the program. This definition notably emphasizes the technical and procedural aspects.

It is worth noting that the use of algorithms originated with the astronomer and mathematician Abu Abdullah Muhammad ibn Musa Al-Khwarizmi, who founded the science of algebra and introduced many important mathematical theories that later evolved into today’s field of artificial intelligence.

AI today represents a digital technology capable of performing human cognitive tasks by analyzing and executing vast amounts of data in a single second (Tohanean, 2018).

Thus, with its enormous digital capability, AI simulates human reasoning through machines to help achieve objectives without the direct involvement of humans.

This raises a question: Can organizations eventually function without human workers, relying instead on smart electronic governance? If so, will such a shift lead to a transformation in organizational and administrative thinking? (Sharit, 2023; Kokorio, 2022)

After presenting the main concepts and definitions of governance and AI, we now move to explore the principles, foundations, and characteristics of both to determine whether they are compatible or contradictory in achieving the research objectives.

Third

Principles, Foundations, and Characteristics of Governance and Artificial Intelligence

1. Governance Principles and Standards:

Most researchers and international organizations such as the OECD, Bank for International Settlements (BIS) through the Basel Committee, the International Finance Corporation (IFC), and others agree on a set of governance principles, summarized as follows:

a. Fairness (Equal Treatment):

Fairness requires an effective governance framework aligned with divine orders as stated in the Qur’an: “Indeed, Allah commands justice and excellence” (Surah An-Nahl, Ayah 90), in addition to legal provisions that ensure equal treatment and protection of all stakeholders' rights. This is achieved by adhering to organizational values and codes of conduct in decision-making and actions, requiring proper distribution of responsibilities within decision-making centers.

b. Accountability:

Accountability is a crucial governance principle, originally emphasized due to financial crises and rising administrative and financial corruption. It necessitates strong oversight, auditing, and verification of data accuracy. Electronic governance—later evolving into AI governance—has emerged to mitigate these challenges.

Governance thus grants stakeholders, especially shareholders, the right to hold senior and executive management accountable for performance and failures. Every organizational level must be accountable to its subordinates, with internal and external audit functions playing a role in identifying weaknesses and ensuring timely implementation of standards and plans. This enhances rights protection, reputation, risk reduction, and sustainable development (Securities and Commodities Authority – UAE, 2021).

Accountability is closely tied to transparency in holding individuals responsible for any failures or deviations. It is important to note that accountability also includes recognizing excellence, rewarding outstanding employees, and encouraging dedication.

c. Disclosure and Transparency:

Most studies agree on disclosure and transparency as fundamental modern principles of governance. International organizations stress the importance of adhering to global standards to ensure high-quality information disclosure.

Although transparency has been heavily emphasized in accounting and auditing, it also extends to administrative conduct and social responsibility. This leads to social justice, equal opportunity, and improved competitiveness (Ben Azzouz, Sabounji, 2024).

Indicators of transparency include:

•Availability of regular reports and financial statements, often publicly accessible.

• Easy access to statistics and organizational data.

• Freedom of expression within the organization.

d. Responsiveness:

Responsiveness focuses on meeting legitimate stakeholder demands promptly, including material and social aspects reflecting the organization's role in its community. Successful responsiveness is achieved when stakeholder needs are met quickly and effectively—characteristics of high-quality organizations.

The diversity of governance types contributes to goal achievement. Today, governance includes participatory, environmental, and other forms (H.B.R., 2019).

2. Components and Characteristics of Artificial Intelligence:

To frame the general components and characteristics of AI, one must understand its capabilities as an independent learning system unrelated to biological human activity. AI is now widely used in many sectors, yielding significant benefits depending on the field.

AI has proliferated in healthcare—especially in diagnosis and patient care—as well as transportation, including unmanned vehicles and self-driving systems. AI robots are extensively used in industry, and AI is common in online shopping.

AI has also advanced in financial institutions by reducing reporting costs, enhancing data analysis, and informing future insights.

However, AI also comes with significant drawbacks and risks, sparking debates about its future and acceptance (Glauner, 2021). In the U.S., more than 50% of citizens believe AI poses a danger to humanity, and over 61% view it as a threat to civilization (Abdulrazzaq Al-Dulaimi, 2023).

The most prominent AI-related risks include:

•Fabricated information and its immense dangers.

•An AI arms race and the military use of AI (e.g., drones, smart bombs, stealth aircraft).

•Risks of system errors and unintended consequences.

•Limited capabilities in certain applications due to the complexity of algorithms and a lack of regulations clarifying legal responsibility in AI-related incidents.

•Reduction in financial managers' privacy and data control.

•Automation (a key AI element) has led to job losses—what once required 60,000 workers now needs fewer than 3,500. AI workers still make up less than 1% of organizational staff.

AI experts express concern over these issues, particularly regarding data integrity—78% are concerned, while 22% are not. Military, medical, and criminal uses of AI remain especially controversial (United Nations, 2024).

Key AI characteristics relevant to assessing compatibility with institutional governance goals include: (Mona El-Sayed Ammar, 2023; Norton, 2022):

•Thinking, perception, and learning to support decision-making and problem-solving, thereby enhancing institutional performance and sustainability.

•Quick response to emerging situations and intelligent decision-making.

•Imagination and creativity in understanding organizational contexts.

•Emulating human thinking and behavior in task execution.

•Processing and analyzing vast amounts of data to achieve high levels of accuracy and prediction, unmatched by human capabilities in short timeframes.

AI’s core components can be summarized in four main characteristics:

Learning – Reasoning – Problem-solving – Perception.

These serve as tools for comparison with governance principles in the next section.

Section Three

Compatibility and Conflict Between Governance and Artificial Intelligence and the Resulting Implications

This section addresses both inductive and deductive comparisons between governance and artificial intelligence. Its purpose is to clarify the areas and extent to which artificial intelligence can be utilized or harnessed for corporate governance. This will be conducted based on the concepts and foundations of both governance and artificial intelligence, which were previously outlined in a summarized manner as part of prior studies or brief viewpoints, with the aim of framing the topic clearly and concisely.

First: Compatibility and Conflict Between Governance and Artificial Intelligence

This will be presented in the form of an inductive comparison table that outlines the compatibility or conflict between artificial intelligence and governance, the degree of this relationship, and the underlying reasons—serving as a core conclusion of the research process—as shown below:

It is important to note that the optimism regarding AI’s role in governance, and human activities in general, depends largely on the governance framework applied to AI itself. Rapid and uncontrolled adoption of AI development may lead to a situation where humans become subservient to AI — a state where AI becomes “superintelligent.” This must be avoided; humans should remain the masters of AI, not its servants.

The rapid pace of AI development and its wide dissemination may result in unintended consequences. In other words, every advancement might trigger counter-effects, implying that such rapid progress can lead to risks and negative outcomes if adopted without careful and detailed study.

Achieved and Expected Results:

The key takeaway regarding the results—both achieved and potentially achievable—is summarized in two simple terms reflecting the positive and negative aspects of AI application within governance:

•Strong Alignment (Gain or Advantage): When AI contributes effectively to the organization’s goals and benefits all stakeholders.

•Strong Contradiction (Problem or Crisis): When AI use leads to material or moral losses or fails to meet organizational objectives.

Every advantage or benefit represents a high degree of alignment, while every problem or crisis signifies a significant contradiction. This applies equally to current and future outcomes, including situations where no objectives are achieved.

Recommendations

Based on the above results, the following recommendations are proposed:

1.Conduct thorough studies, analyses, and continuous development of successful organizational applications of AI, especially in governance, to reinforce and sustain alignment, which will positively impact organizations.

2.Investigate and address failures in AI applications, avoiding causes of failure to prevent contradictions in governance practices.

3.Expand the use of AI in entrepreneurship, particularly in areas that improve customer satisfaction and strengthen organizational competitiveness.

4.Organizations should systematically evaluate the impact of AI on their governance activities, marketing functions, and profit maximization.

5.Finally, when organizations consider the interests of their stakeholders through governance frameworks, they should prioritize AI applications that have proven successful globally, such as process automation, service quality improvement, and fraud detection across key economic sectors like healthcare, banking, finance, and industry.

Moreover, participatory management philosophy should prevail as the preferred administrative approach, replacing outdated individualistic management styles.

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