How ambidextrous entrepreneurial leaders react to the artificial intelligence boom

IAES International Journal of Artificial Intelligence (IJ-AI)
Vol. 14, No. 3, June 2025, pp. 1708~1718
ISSN: 2252-8938, DOI: 10.11591/ijai.v14.i3.pp1708-1718  1708
Journal homepage: http://ijai.iaescore.com
How ambidextrous entrepreneurial leaders react to the artificial
intelligence boom
Kandasamy Indravathy, Noorlizawati Abd Rahim
Department of Business Intelligence, Humanities and Governance, Faculty of Artificial Intelligence, Universiti Teknologi Malaysia
Kuala Lumpur, Kuala Lumpur, Malaysia
Article Info ABSTRACT
Article history:
Received Aug 14, 2024
Revised Feb 26, 2025
Accepted Mar 15, 2025
Artificial intelligence (AI) now plays a central role in enhancing business
competitiveness by transforming systems, frameworks, and managerial
strategies. This study employs a systematic literature review (SLR)
approach, utilizing the 'Consensus AI' search platform to explore the
characteristics and roles of ambidextrous entrepreneurial leaders in the AI
era. Consensus AI is an AI-powered search engine that automates the
processes of reviews, literature searches, screening, and data extraction. It
also utilizes 'research question searches' within SLRs to avoid the challenges
of ambiguity and irrelevant information associated with 'keyword searches,'
delivering more directly relevant results and finding featured snippets that
answer specific questions. A research gap exists concerning how
ambidextrous leadership adapts to the AI boom, highlighting leadership
dynamics in the digital age. The findings emphasize the critical role of
ambidextrous entrepreneurial leadership (AEL) in guiding organizations
through the AI boom, enabling them to leverage AI for innovation, agility,
and competitiveness. Organizations that effectively implement AEL by
integrating AI technologies can position themselves for long-term success.
Key insights show the importance of AEL approaches, and future research
may explore challenges that arise for ambidextrous entrepreneurial leaders in
the era of AI, such as ethical considerations and organizational culture.
Keywords:
Ambidexterity
Artificial intelligence
Consensus
Entrepreneurial
Leadership
This is an open access article under the CC BY-SA license.
Corresponding Author:
Kandasamy Indravathy
Department of Business Intelligence, Humanities and Governance, Faculty of Artificial Intelligence
Universiti Teknologi Malaysia Kuala Lumpur
Sultan Yahya Petra St. (Semarak St.), Kuala Lumpur 54100, Malaysia
Email: indravathy@graduate.utm.my
1. INTRODUCTION
Artificial intelligence (AI) has developed in a sustainable manner and has had a big impact in the
21st
century [1]. In organizations, AI could generate business value with deeper understanding of its adoption,
value-creating mechanisms, key enablers, and inhibitors [2]. The development of AI systems that model
entrepreneurial activity through uncertain environments is promising as it forms new ways of future research
on the entrepreneurial decision-making process [3]. When combined with the positive impact of AI on
entrepreneurship, opportunities, decision-making, performance, and education among other things, the
process of entrepreneurship is growing [4].
AI technologies are progressively emerging as pivotal catalysts of innovation and competitive
advantage, with scholarly investigations concentrating on their influence in reshaping decision-making
processes, enhancing operational efficiency, and refining strategic management within organizations [5], [6].
Current academic discourse underscores the potential of AI to enhance both exploratory and exploitative

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How ambidextrous entrepreneurial leaders react to the artificial intelligence boom (Kandasamy Indravathy)
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organizational mechanisms [7]. However, there exists a paucity of studies that specifically assess its effects
on leadership strategies, especially in the context of ambidextrous entrepreneurial leadership (AEL). This
identified gap underscores a significant imperative to investigate the nexus between AI and leadership, a
correlation that remains inadequately explored within extant scholarly literature.
The effect of entrepreneurial leadership (EL) on decision-making processes is major, as it combines
rational, intuitive, and strategic methods. This combination allows leaders to effectively maneuver
uncertainty and complexity, thus ensuring organizational growth and innovation [8]–[10]. Successfully
exercising this leadership approach demands deep knowledge of individual characteristics, cognitive biases,
and the dynamic relations between the leader and their team [11], [12].
Ambidextrous is the ability to use both hands equally, and in a broader context, especially in
business and management, it is the ability of an organization to manage simultaneously exploratory activities
related to innovation and the discovery of new opportunities with exploitative activities centered on
incremental optimization and efficiency. This dual competency allows organizations to maneuver through an
emerging environment with sustained operational efficiency [13], [14]. In the same vein, EL concerns
managing an organization by simultaneous search for new opportunities and exploitation of current
opportunities [15]. The latter kind of leadership opens and exploits opportunities through the use of
knowledge, cognitive skills, strategic decisions, and dynamic capabilities to integrate exploration and
exploitation in the innovation process and organizational growth [16]–[18]. This approach integrates
exploration and exploitation to drive innovation and organizational growth [19].
Despite comprehensive investigations into the overarching impacts of AI on business operations and
innovation, there exists a significant gap in the scholarly discourse that specifically examines the mechanisms
through which AEL integrate AI into both exploratory and exploitative endeavors. While a considerable
portion of the existing literature has concentrated on the role of AI in augmenting entrepreneurial decision-
making [5], there remains a gap of research addressing how leaders effectively reconcile AI-driven
innovation with the optimization of operational processes [20]. The current body of literature predominantly
underscores the ambidextrous qualities of leadership in promoting both innovation and operational
efficiency, yet frequently neglects the integration of AI technologies within these dual strategic frameworks.
This investigation seeks to remedy this deficiency by exploring the attributes and functions of AEL within
the context of the AI boom, thereby offering a novel perspective point on the evolution of leadership
strategies in response to the exigencies of digital transformation.
Hence, this study aims to explore AEL in the AI boom age for organizations. To date, no previous
research study has focused on the relationship between AI and AEL. Therefore, in continuation of this dearth
of literature about this relationship, the present paper conducts a systematic literature review (SLR) on
studies investigating AEL characteristics and roles and their response to the AI boom. The following research
questions lead the paper study:
‒ What characteristics do ambidextrous entrepreneurial leaders possess that empower them to succeed in
the era of AI?
‒ What roles are carried out by ambidextrous entrepreneurial leaders in leveraging AI in the era of AI?
The results of the research are anticipated to provide valuable insights on the abilities and proficiencies
necessary for proficient leadership within the advancing digital environment, furnishing practical
recommendations for programs aimed at enhancing leadership capabilities and making strategic decisions in
organizations driven by AI.
2. LITERATURE REVIEW
2.1. Overview of artificial intelligence and ambidextrous entrepreneurial leadership
Alternative investment is an integral part of technologies that significantly enhance effectiveness,
accuracy, and creativity in business decision-making. These enhancements lead directly to improved
organizational success. Additionally, AI drives transformative changes in organizational business practices [21].
AI has gone through rapid evolution from its initial development stage. It has now become a flexible
and adaptive method for achieving objectives and tasks far beyond its original scope, emerging as a polished,
workable entity within business [22]. AI creates value by exploring its implications, potential applications, and
methodologies, thereby enabling a clearer understanding of evolving business landscapes and trends [23].
The potential relationship between AI and leadership underscores the necessity to reassess the skill set
essential for future leaders [24]. In organizational contexts, AI is poised to reshape leadership roles. However,
successful decision-making requires a seamless integration of AI functionalities and emotional intelligence to
maintain a competitive advantage [25]. Leadership in the era of AI is of utmost importance as it serves to
motivate and empower individuals, and establishes strategic objectives for organizational change [7], [26]–[28].
It balances AI-driven decisions with ethical considerations and fosters an intrapreneurial organizational culture.
These leadership qualities ensure that AI enhances human potential and drives organizational success.

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Apart from entrepreneurial aspects, ambidexterity involves balancing exploration and exploitation,
which is essential in the current AI era. Ambidextrous leaders are instrumental in promoting innovation and
strategic expansion through careful management of exploration and exploitation activities, nurturing
cognitive ambidexterity, and ensuring ethical integration of AI [7], [29]–[31]. Their adaptability and strategic
incorporation of AI technologies are crucial for organizational success.
The ambidextrous leadership is a combination of the opening and closing behaviors [32]–[34]. This
type of leadership not only encourages innovative behavior in employees but also develops psychological
ownership, and in this process plays the mediator role [35]. Moreover, this leadership balances and manages
exploration and exploitation activities in an organization [36]. Exploration focuses on ambidextrous
leadership toward seeking new knowledge, innovation, and experimentation. It is centered on the
identification of new opportunities as well as the development of new products, services, or processes [37].
Factors that can be related to exploration are enabling a climate that would promote innovative thinking and
risk-taking, the ability to continuously learn, and adaptability [38]. On the other hand, exploitation refers to
the optimization and enhancement of existing resources, processes, and capabilities for better efficiency,
productivity, and incremental innovation [39], [40]. The key features of exploitation include efficiency
initiatives, quality enhancement measures, continuous betterment of available methods, and full
maximization of available resources and capacities in operation [41], [42].
On the other hand, EL can broadly be defined as characterized by dynamism [43], [44] and
innovation [45]. This leadership style integrates principles of entrepreneurship into practice. It emphasizes
highly effective strategies for leading and guiding individuals and teams toward success [46].
2.2. Theoretical perspective
The upper echelons theory [47] proffers comprehensive model of how AEL could, through the effective
exercise of AI, exploit its benefits. This theory suggests that organizational outcomes, including strategic
decisions and performance metrics, are partly impacted by top executive attributes [48]. The ambidextrous
entrepreneurial leader's decisions and actions, in the context of AI, regarding the exploitation-exploration balance
become crucial in guiding organizations through the intricacies associated with integrating AI.
Moreover, upper echelons theory underscores that the experiences, values, and personalities of the top
executives are extremely important because they provide a frame for their interpretations and decisions [48].
AEL will have a distinctive confluence of cognitive flexibility, propensity for risk-taking, and strategic vision in
the organization that facilitates harnessing technological change in favor of AI within the firm [49]. They are
more capable of making strategic decisions balancing short-term operational efficiency with long-term
innovation [47]. This dual emphasis is in line with upper echelons theory, which argues strategic behavior as an
influence of leader background and cognitive foundation, focusing on using AI for competitive advantage [48].
3. METHODOLOGY
3.1. AI-driven systematic search of “research questions”
AI has been well recognized for its development and tremendous accomplishments since 2013 [50].
The application of AI has increased massively following 2013, which caused higher research interest in the
area. The role of AI in organizational contexts has found greater prominence after 2013 [51]. Therefore, this
study performs a SLR on the characteristics and role of the AEL approach applied during 2015-2024.
A standard SLR usually conducts a full review of the literature and reviews through reference
databases such as PubMed, Scopus, and Web of Science (WoS) [52], [53]. The review procedure is conducted
with the support of the preferred reporting items for systematic reviews and meta-analysis (PRISMA)
guidelines [54]. This approach conducts a detailed search strategy formulated and conducted using specific
keywords [55], which could lead to ambiguity if the keywords are too general, potentially pulling in a wide
range of irrelevant information [56]. Additionally, keywords may not always address the research questions.
However, the major issue with searching based on questions is that it has the ability to pull up more relevant
search results or at least reveal some featured snippets in response to the questions being asked. Nowadays, AI
tools can extend their usage to SLRs with specified questions, going beyond the traditional usage of keywords,
which makes the retrieval more relevant and enhances paper selection for review.
In this regard, the Consensus tool is used for conducting the SLR. The search platform is the use of
Consensus AI tools, which are rooted in machine learning and crafted to do searches, screening, and data
extraction in the context of systematic reviews [57]. This tool, by using a research question query, gives an
accurate and related result, hence reducing vagueness and reducing irrelevant information. This thus
increases the effectiveness of this review process. Olson and Salem [58] created the Consensus AI tool,
which was officially launched in the year 2022. The AI-powered search engine is purposely built to enhance
the effectiveness of the search process by automating activities entailed in literature searching, screening, and

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data extraction. Its main purpose is to respond rapidly with evidence by utilizing sophisticated machine-
learning methodologies. Over time, the Consensus AI technology has been developing and growing while
bringing in improvements that involve the Consensus 2.0 functionalities, such as Consensus Copilot and
Consensus Meter, that further enrich its capabilities for better user interaction [59]. Consensus search for
information from well-recognized and trusted databases like Scopus and WoS to ascertain the credibility and
authenticity of the preferred articles. Consensus employs search algorithms that allow researchers to enhance
efficiency by rapidly access a wide range of academic papers and pinpoint relevant studies on particular
topics, authors, or publication periods [60] based on research questions instead of keywords. This is
confirmed when the study cross-checked databases like WoS and Scopus and discovered that Consensus
supports a variety of peer-reviewed articles indexed in databases such as WoS and Scopus, offering
researchers comprehensive and reliable information. However, its application in SLR has not been
sufficiently studied, leading to this research exploring the method of SLR using the Consensus database.
Conducting an SLR with the assistance of Consensus involves a few basic steps aimed at guaranteeing
a thorough and methodical examination of existing literature, alongside the incorporation of consensus-building
techniques. Figure 1 shows the steps conducted in this SLR using Consensus. The flowchart depicted in
Figure 1 delineates the systematic process employed for the identification of pertinent peer-reviewed scholarly
articles pertaining to the subject of AEL. This procedure commences with the articulation of the research
questions and the formulation of sub-questions for each distinct area of investigation.
This SLR was developed through research questions (RQs) defined as follows:
‒ What characteristics do ambidextrous entrepreneurial leaders possess that empower them to succeed in
the era of AI?
‒ What roles are carried out by ambidextrous entrepreneurial leaders in leveraging AI in the era of AI?
Based on these RQs, sub-questions were formulated for searches using the Consensus search engine as follows:
i) RQ 1 sub-questions:
− What are the characteristics of ambidextrous entrepreneurial leaders?
− What are the characteristics of ambidextrous entrepreneurial leaders in this AI age?
− What traits help ambidextrous leaders adapt to AI changes?
− What are the qualities of ambidextrous entrepreneurial leaders?
− What are the qualities of ambidextrous entrepreneurial leaders in this AI age?
ii) RQ 2 sub-questions:
− What are the roles of ambidextrous entrepreneurial leaders?
− What are the roles of ambidextrous entrepreneurial leaders in the age of AI?
− What are the roles of ambidextrous entrepreneurial leaders in the age of AI in organizations?
The search timeframe was filtered from 2015-2024. These sub-questions were adjusted to include
keywords such as 'ambidextrous entrepreneurial leaders, 'characteristic,' and 'role' to ensure relevance to the
topic and facilitate the search for related journals. Furthermore, each identified journal was cross-checked in
the WoS and Scopus databases to confirm its credibility as peer-reviewed information.
The research process included reviewing the 'key takeaway' summary provided by Consensus for
each study, which summarized characteristics or roles of AEL, making the process simpler and more efficient
compared to the PRISMA ‘keyword search’ method. After searching for the research question and sub-
questions, and making adjustments to the keywords for all the questions, this study stopped searching when
the same papers repeatedly appeared in the results within the Consensus tool. This study identified a total of
seven characteristics of AEL that empower them to succeed in the AI age, and seven roles in leveraging AI.
Figure 1. Consensus method flow
Research articles were considered if they fulfilled all of the following inclusive criteria:
‒ This study uses peer-reviewed journal articles, conference papers, and scholarly books that investigate
characteristics and role of ambidextrous entrepreneurial leadership

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‒ Must include the keywords: AI, ambidexterity, entrepreneurial, leadership, consensus, literature searches
‒ The timeframe of the article from 2015-2024
‒ Must be written in the English language
‒ The articles taken from result given by Consensus algorithm
‒ Must cross-checked in WoS and Scopus databases
Articles were excluded if they met any of the following exclusive criteria: i) the papers discuss other than
characteristics and role of ambidextrous entrepreneurial leadership; ii) written in language other than English;
iii) papers written not in timeframe of 2015-2024, iv) not indexed and peer-reviewed in WoS and Scopus
databases.
4. RESULT AND DISCUSSION
The characteristics and roles of AEL are similar to those of EL. This similarity arises due to the
limited existing research specifically addressing AEL. Therefore, this study examines the characteristics and
roles identified in EL literature to identify AEL in the context of AI.
4.1. General characteristics of ambidextrous entrepreneurial leadership
Ambidextrous entrepreneurial leaders exhibit several key characteristics that empower them to
thrive in the era of AI. The characteristics of EL is more prevalent among founder-leaders than non-founder
leaders [61]. This prevalence influences group performance towards recognizing and exploiting
entrepreneurial opportunities [61], [62]. Additionally, EL is associated with cultivating innovative behavior
among employees with higher levels of creative self-efficacy [45], [62] and a passion for invention [45].
Furthermore, entrepreneurial leaders are perceived as visionary entrepreneurs with the motivation and
ethics of a leader, which plays a critical role in venture growth and long-term entrepreneurial success [46]. EL
also refers to improved effectiveness outcomes at various levels, with the cultural context being a key moderator,
while enterprise type and leadership measures show no significant effects [63]. Moreover, EL positively impacts
adaptive innovation in uncertain environments through multiple pathways, such as exploitative learning,
exploratory learning, resource bricolage, and boundary-spanning integration [64]. Tables 1 and 2 explain about
the characteristics of EL. These characteristics are underscored by various scholars, illustrating the manner in
which EL impacts innovation and organizational performance. It is essential for readers to recognize that these
characteristics are integral to the mechanisms through which entrepreneurial leaders facilitate innovation,
particularly within rapidly evolving contexts. These tables further substantiate the significance of EL in
cultivating an innovative organizational culture, a phenomenon that is especially pertinent amid the surge of AI
advancements, and these attributes will be explored in greater detail within the context of AEL.
Table 1. Entrepreneurial leadership characteristics
Reference Characteristics of entrepreneurial leadership
[46] Perceived as visionary entrepreneurs with the motivation and ethics of a leader
[45], [62] Cultivate innovative behavior among employees with higher levels of creative self-efficacy
[45] Fosters employees' innovative behavior through the passion for inventing
[64] Impacts adaptive innovation in uncertain environments
[65] Impacts innovation management and its measurement
[63] Improves effectiveness outcomes at various levels, with cultural context
[61] More prevalent among founder-leaders than non-founder leaders
[61], [62] Recognizing and exploiting entrepreneurial opportunities
Table 2. Role of EL
Author Role of EL
Renko et al. [61] Entrepreneurial leadership is more prevalent among founder-leaders than non-founder leaders, influencing
group performance towards recognizing and exploiting entrepreneurial opportunities.
Newman et al. [62] Entrepreneurial leadership, through role modeling and directing employees to entrepreneurial opportunities,
significantly enhances the link between creative self-efficacy and innovative behavior.
Bagheri et al. [45] Entrepreneurial leadership of CEOs in high-technology new ventures fosters employees' innovative behavior
through the mechanisms of creative self-efficacy and passion for inventing.
Akbari et al. [66] Entrepreneurial leadership positively impacts innovation work behavior in ICT SMEs, with employees' creative
self-efficacy and leaders' support for innovation acting as mediators.
Nguyen et al. [44] Entrepreneurial leadership enhances the performance of IT SMEs through the mediating factors of team
creativity, dynamic capabilities, and competitive advantages.
Bagheri et al. [67] Entrepreneurial leadership improves employees' innovation work behavior by enhancing their individual and
team creativity self-efficacy.
Iqbal et al. [68] Entrepreneurial leadership positively impacts employee innovative behavior in the high-tech services industry,
with affective commitment, creative self-efficacy, and psychological safety acting as mediating factors. In high-
tech service industries, affective commitment, creative self-efficacy, and psychological safety are mediators that
result in innovative behavior.

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While previous research has underscored the significance of entrepreneurial leaders in catalyzing
innovation and the identification of opportunities, our empirical findings elucidate that AEL exhibit
supplementary competencies. These competencies are particularly instrumental in facilitating organizational
adaptation to transformations driven by AI. For instance, AEL leaders not only foster an environment conducive
to innovative behaviors but also adeptly assimilate AI technologies to enhance both exploratory and exploitative
processes, a differentiation that has not been extensively examined in previous scholarly inquiries [19].
4.2. Roles of entrepreneurial leadership
Ambidextrous entrepreneurial leaders play a significant role in leveraging AI in the contemporary
business landscape. The success and competitiveness of enterprises are largely dependent on organizational
flexibility and innovation [69]. Growing these attributes relies on a central role brought by EL, the one that
involves having foresight and strategy that are critical to gaining success in an organization [70], [71].
The indispensable element for promoting innovation is the integration of information technologies,
with EL guiding the organization in embracing and leveraging these technologies [44], [72]. EL with a focus
on the prioritization of adaptability and forward-thinking [46], [64], [73], assumes a crucial function in
nurturing organizational agility [74], which in turn becomes a fundamental constituent for prospering in a
competitive market [75]–[77]. This agility is further accomplished through EL's emphasis on competitive
intelligence and strategic flexibility [78], [79].
Communication is one of the key attributes in organizational innovation. EL environments offer
communication that is both open and effective, which is tremendously important [80]. In general, EL highly
influences organizational success and innovation in the present dynamic business environment due to its
adoption of flexibility, innovation, IT use, agility, and effectiveness in communication. Table 3 outlines the
role of EL in organizational success and innovation.
Table 3. The characteristics and role of ambidextrous EL
Characteristics Roles Outcome
‒ Innovative and visionary
thinking [46]
‒ Recognize and capitalize emerging opportunities [61].
‒ Real case example: Tesla Motors' strategic acknowledgment and
exploitation of the emerging opportunity in the electric vehicle sector
embody fundamental principles. The company's foresight, innovation, and
implementation have not only solidified its position as a market leader but
also hastened the worldwide shift towards sustainable energy and
transportation [61].
Organizational
agility [74]
‒ Strategic flexibility to
balance exploration and
exploitation [61]
‒ Optimize existing resource [64].
‒ Real case example: Toyota's Just-In-Time production system strategically
leverages available resources to attain notable competitive benefits.
Through the minimization of waste, enhancement of operational efficiency,
and elevation of product quality, Toyota successfully maximized its
constrained resources and revolutionized the international automotive
sector [81].
Organizational
innovation [80]
‒ Effective communication
[80]
‒ Integrate AI into organizational operation [82].
‒ Real case example: IBM's Watson utilizes the capabilities of AI to conduct
data analysis, facilitate decision-making, and customize treatment plans.
Through this utilization, IBM has reshaped healthcare practices and
demonstrated the capacity of AI to transform various industries [83].
New value
creation [84]
‒ Passion for inventing [45]
‒ Inspire cultivate innovative
behaviour [45], [62]
‒ Mitigate risks [85].
‒ Real case example: Airbnb's approach to addressing regulatory obstacles
showcases the effectiveness of entrepreneurial leadership in managing
risks. Through proactive engagement with regulators, adjustment of the
business framework, cultivation of community support, guaranteeing
transparency, and allocation of resources towards legal and lobbying
endeavours, Airbnb's leadership successfully navigated through intricate
regulatory environments, thus safeguarding the company's growth and
sustainability [86].
Maintain
competitive
advantage [84]
‒ Creative self-efficacy [45],
[62]
‒ Stakeholder collaboration around AI initiatives [87].
‒ Real case example: Google's AI for Social Good initiative collaborates
with non-profit organizations, academic institutions, governmental bodies,
and communities. Google leverages the combined knowledge and assets of
these stakeholders to develop influential AI solutions. This particular
analysis provides evidence that engaging stakeholders in AI projects is
essential for attaining significant and enduring results [88].
Adoptive
innovation [89]
‒ Competitive intelligence
[78]
‒ Drive exploratory and exploitative learning [64].
‒ Real case example: Amazon, known for its dedication to both exploratory
and exploitative learning, has played a crucial role in its achievements. The
capacity to introduce new ideas while enhancing current processes is key to
sustaining growth and upholding a competitive advantage [19].

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Table 3 provides a comprehensive examination of the attributes and functions of AEL and elucidates
their influence on organizational performance. The table elucidates the manner in which AEL incorporates AI
into operational frameworks, promotes collaborative engagement among stakeholders, and adeptly navigates
the balance between exploration and exploitation, thereby facilitating both innovation and risk management. It
underscores the pivotal role that AEL leaders assume in the governance of risks, the enhancement of
organizational agility, and the promotion of sustainable success within industries influenced by AI.
In contrast to earlier research that primarily examined the contributions of entrepreneurial leaders in
promoting innovation through traditional means [45], our results underscore the distinctive ability of AEL to
leverage AI. Specifically, AEL utilizes AI for both strategic foresight and operational agility. This ability
positions AEL exceptionally well to adeptly navigate the intricacies of the AI-centric business landscape, a
subject that has garnered insufficient scholarly attention in preceding studies.
4.3. The role and characteristics of ambidextrous entrepreneurial leadership in navigating the AI boom
Findings related to AEL suggest the importance of such leadership characteristics in coping with the
AI boom. AEL shares several characteristics with traditional EL, which include fostering innovation,
promoting visionary behavior, and enhancing organizational effectiveness [45], [46]. AEL possesses a
number of resemblances to conventional EL, including the encouragement of innovation and visionary
behavior and improvements in organizational performance. These qualities are particularly important during
the AI boom, where innovation and visionary thinking are vital for effectively leveraging AI technologies
and driving organizational success. By embodying these characteristics, ambidextrous entrepreneurial leaders
can navigate the complexities of the AI landscape, capitalize on emerging opportunities, and mitigate
potential risks [29], [85].
While prior investigations have recognized these attributes within the broader framework of EL, our
empirical study elucidates that adaptive AEL exhibit exceptional proficiency in applying these characteristics
within the domain of AI. This proficiency enables organizations to effectively leverage existing resources
while simultaneously pursuing novel AI-driven opportunities. Consequently, our findings contribute a novel
perspective to the comprehension of EL in the context of a swiftly transforming technological environment.
Other than this, AEL is important in creating organizational agility and innovation, which helps in
adjusting the speeded adjustment brought in by the boom of AI [74]. Ambidextrous leaders can handle both
exploitation and exploration excellently [62], so they allow the organization to exploit new opportunities and
optimize present resources [64]. This agility assists organizations in remaining competitive and dynamic in a
market environment driven by AI.
AEL also supports their organizations in the adoption and exploitation of information technologies,
including AI. In the AI boom period, effective exploitation of AI technologies is important to enhance
competitive advantage and foster innovation [45], [62]. Ambidextrous entrepreneurial leaders, with their forward-
thinking mindset and strategic orientation [31], are pivotal in integrating AI technologies into organizational
operations and leveraging their potential benefits [82]. They ensure that AI initiatives align with organizational
goals and are implemented effectively to drive value creation and maintain a competitive advantage [84].
Moreover, innovation in organizations largely depends on effective communication through EL
[80]. In light of the AI boom, there is a need to develop open and effective communication channels both
inside and outside of the organization for the realization of collaboration, sharing insights, and getting the
stakeholders aligned with AI initiatives [87]. Ambidextrous entrepreneurial leaders create an environment in
which communication takes place, enabling collaboration and sharing of knowledge for harnessing AI
technologies in the process of innovation and organizational success [89].
In essence, AEL is one of the critical issues evident in organizations' reactions to the AI wave. This
leadership approach is particularly significant in fostering innovation, agility, adoption of IT, and
communication. Ambidextrous entrepreneurial leaders provide direction on how organizations can harness
AI technologies most effectively, chart opportunities and risks, navigate an AI-driven business environment,
and lead sustainable growth and success in the digital age.
5. LIMITATIONS
Even with the innovative algorithms that are incorporating advances in search precision, efficiency,
and comprehensiveness, the Consensus tool remains quite vulnerable to algorithmic bias. It can never
completely capture the intricate details of research. The task is made more difficult by the need for authors to
minimize this subjectivity through regular adjustments, reviews, and calibration of the Consensus tool's
algorithms, and human oversight. Another limitation is that this paper looked only into peer-reviewed articles
published in the English language within the specific timeframe of 2015-2024. Lastly, the generalizability
and scope of the study's findings is limited since it was only based on characteristics and role of AEL.

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6. CONCLUSION
AI improves the business competitiveness of organizations through improved systems, models
restructuring, and offers innovation in management approaches to enhance competitiveness in global markets.
This study conducted a SLR to investigate the characteristics of the AEL role and its reaction to the AI boom.
This filled in the gap for lack of study between the boom of AI and AEL. The study tried to identify the features
possessed by AEL that would empower them to succeed and explore the roles that these leaders could carry out
in leveraging AI in the era of AI. An AEL guides organizations through the AI explosion, empowering them to
leverage fully AI technologies in organizational innovation, agility, new value creation, continuous competitive
advantage, and adopt innovation. By being more creative, strategically agile, and effective in stakeholder
partnering, AEL makes a difference in ensuring success in the AI era and beyond. They enable new value
creation and competitive intelligence, bringing about innovative behavior within their firms and enabling long-
term success and resilience in a radically changing digital environment. The leadership at any level needs to be
ambidextrous and entrepreneurial in such a way as to effectively respond to the AI boom by balancing
innovation and operational efficiency while navigating through uncertainty and exploiting emerging
opportunities. This prepares organizations for agility, ensures continuous learning, and integrates AI into
strategic goals while sustaining competitive advantage in a fast-changing environment. Future research could be
based on the challenges awaiting these ambidextrous, entrepreneurial leaders in the AI future.
FUNDING INFORMATION
This work was funded by the Ministry of Higher Education under Fundamental Research Grant
Scheme, UTM, FRGS/1/2022/SS02/UTM/02/3.
AUTHOR CONTRIBUTIONS STATEMENT
This journal uses the Contributor Roles Taxonomy (CRediT) to recognize individual author
contributions, reduce authorship disputes, and facilitate collaboration.
Name of Author C M So Va Fo I R D O E Vi Su P Fu
Kandasamy Indravathy ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
Noorlizawati Abd Rahim ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
C : Conceptualization
M : Methodology
So : Software
Va : Validation
Fo : Formal analysis
I : Investigation
R : Resources
D : Data Curation
O : Writing - Original Draft
E : Writing - Review & Editing
Vi : Visualization
Su : Supervision
P : Project administration
Fu : Funding acquisition
CONFLICT OF INTEREST STATEMENT
Authors state no conflict of interest.
DATA AVAILABILITY
Data availability is not applicable to this paper as no new data were created or analyzed in this study.
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BIOGRAPHIES OF AUTHORS
Kandasamy Indravathy holds a Bachelor of Banking with Honors from
Universiti Utara Malaysia, obtained in 2011. She furthered her education by earning a Master
of Business Administration from Universiti Teknologi Malaysia in 2018. Currently, she is
pursuing a Ph.D. at Universiti Teknologi Malaysia, where she also serves as a graduate
research assistant. Her research interests focus on entrepreneurial leadership, a field where she
has already contributed through her publications. She has published in the Journal of
Theoretical and Applied Information Technology. In recognition of her research efforts, she
received the Best Research Poster (Silver Award) at the Research and Project Poster
Competition in the Social Science category, organized during Razak Research Week at
Universiti Teknologi Malaysia. She can be contacted at email: indravathy@graduate.utm.my.
Noorlizawati Abd Rahim is senior lecturer in the Department of Business
Intelligence, Humanities, and Governance, Faculty of Artificial Intelligence, Universiti
Teknologi Malaysia (UTM). She has a multidisciplinary background with a foundation in
B.Eng. Electrical and Electronic Engineering from Cardiff University, advanced studies in
M.Sc. Nanotechnology (Department of Electrical and Electronic Engineering) at University
College London, and expertise in technology entrepreneurship through her Ph.D. from UTM.
She is a Board of Governors member and serves on the publication and conference committee
for IEEE Technology and Engineering Management Society (IEEE TEMS). She has also
earned the AI for Business Specialization certification from University of Pennsylvania and
No code AI and machine learning: building data science solutions’ certification from
Massachusetts Institute of Technology (MIT) Professional Education. Her research interests
include technology entrepreneurship, intersection of AI in business applications, innovative
pedagogies in entrepreneurship education, entrepreneurial leadership and opportunity
recognition in digital markets. She can be contacted at email: noorlizawati@utm.my.

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