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Article

Artificial Intelligence Adoption and Digital Innovation: How Does Digital Resilience Act as a Mediator and Training Protocols as a Moderator?

by
Xiaochun Zeng
1,
Suicheng Li
1 and
Zahid Yousaf
2,*
1
School of Economics and Management, Xi’an University of Technology, Xi’an 710048, China
2
Higher Education Department, Government College of Management Sciences, Mansehra 23100, Pakistan
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(14), 8286; https://doi.org/10.3390/su14148286
Submission received: 16 May 2022 / Revised: 23 June 2022 / Accepted: 4 July 2022 / Published: 6 July 2022
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Abstract

:
This study aims to discover how technology firms accomplish digital innovation through AI adoption. The current research also investigated digital resilience’s role as a mediator and training protocol’s role as a moderator between AI adoption and digital innovation links. The data collection and analysis were conducted using a quantitative method. To examine the research hypotheses, we chose technology firms that face problems regarding the enhancement of digital innovation. The findings confirmed that the digital innovation of technology firms is forecasted through AI adoption. The results proved that digital resilience plays a mediating role between AI adoption and digital innovation links. Technology firms play a key role in the advancement of digital technology. This research study adds to the existing knowledge by offering a digital innovation model with the combined influence of AI adoption, digital resilience, and training protocol. This study will be helpful for top management by showing when, why, and how AI adoption helps firms in their achievement of digital innovation. Moreover, digital resilience’s role is also important in the current digitalized world; thus, we used digital resilience as mediator in this research.

1. Introduction

In the modern era, AI adoption has radically changed the pattern of performing trade and business. AI adoption has brought the latest functional applications and digital transformation in organizations that change the pattern of work performed by HR in technical organizations [1]. Firms that transform themselves digitally not only change the way of conceiving of what their consumers want, but also design operating models that give them new possibilities with different identities from competitors [2]. AI adoption standardizes the cost and time required for repetitive tasks in organizations. AI adoption helps in employee training, retention, recruitment, and engagement, which in turn aids in more accurate time-saving, task completion, and cost reduction [3]. AI adoption will assist technical organizations to enhance the effectiveness and efficiency of their talent acquisition performance and their function towards the achievement of digital innovation [4]. AI adoption is a critical topic in the research, as it provides a better understanding of the digital resilience for the achievement of digital innovation [5]. In the contemporary era, digital innovation is the important critical factor for the growth of technology firms, the development of society, and for the preservation of competitive benefits in the emerging market [6]. In addition, digital innovation is an uncertain, path dependent, iterative, context specific, interactive, and the multi-tasking settlement [7]. Therefore, AI adoption remains the key input with which businesses can recognize accurate solutions for the implementation of the innovative process, which enables an improved understanding of digital resilience that helps in the diffusion of novel ideas in markets and facilitates the attainment of digital innovation via the design of novel products [8]. Currently, we all face major challenges with the COVID-19 pandemic outbreak that broadly affect the potential future of humanity. Everywhere, human dealings are increasingly customized by palliative track and trace competences carried out through digital technologies. In this situation, not only are all global logistics, transport networks, value chains, and office tasks disturbed, but human freedoms and rights are intensely restructured [9]. The emergence of tracking/tracing digital technologies has facilitated the ex-post supervision of communities by AI adoption and other recent technologies but has also created tension between civil liberty defenders and digital Leviathans combined with an increasing amount of new risks [10]. From this perspective, the important concerns are how to ensure digital resilience, collective well-being, and how to safeguard individual rights within this context. Digital resilience entails the capability of facing constant changes and shocks in a way that conserves a community’s well-being, without compromising the heritage of future generations [11]. Generally, social media, mobile applications, and digital technology particularly exploit this novel computing paradigm, as they all have some advantages but also several risks, which are to be monitored, anticipated, and avoided in accordance with “digital idealism” [10]. We are entrenched in a growing digital world, and so firms must be capable of adopting and quickly moving toward new digital solutions to recover as well as move and rebound forward when situations transpire incorrectly. However, even now many firms are still unaware of the importance of digital transformation and its associated risks [12]. The COVID-19 fallout shows the significance of digital-technologies and the need for digital transformation towards a digitally relevant future; hence, the relevance of digital resilience has not been ignored to ensure that society develop a sustainable set of manners [8]. Various previous researchers have paid attention to the rapid advancements that occur in digital innovation practices, which influence all the functional areas of business. Different prior studies have investigated the various important factors/preconditions that have assisted in the determination of digital innovation across many firms until now. However, the preceding literature has barely focused on the role of digital innovation in business firms [13], knowledge management systems [14], the automotive industry [15], but has not exposed its impact on technology firms. In technology firms, there is a need for the implementation of enhanced digital innovation processes, which is a difficult and complex job without the adoption of AI applications. Several scholars have conducted research into technology firms; however, they have placed emphasis on constructs such as market orientation [16], management factors [17], innovation, networking, and proximity [18], which provide support for the improvement and performance of technology firms. Nevertheless, our study model adds a unique advantage by selecting three variables such as AI adoption (independent variable), digital resilience as a mediator, and training protocol as a moderator in the link between AI adoption and digital innovation. This research study not only elucidates the impact of AI adoption on digital innovation, but also explains the accelerating outcomes of digital resilience and digital innovation through the help of AI adoption. As digital innovation changes business processes, market offerings and models are derived from an enhanced understanding of digital resilience and training protocols. Therefore, the main objective of this research is the improvement and enhancement of the digital innovation in technology firms of both developing and developed countries. This study also focused on the key roles of AI adoption and digital resilience, which are the most valuable advancements in firms and that aid in the implementation of digital technologies for various innovation processes and strategies. Furthermore, the training protocol supports the management of risks, the acquisition of the latest advantages, and the implications of digital technology, which provide information about whether innovative changes are emerging and consequently how to accommodate them through the latest applications of digital technology, which in turn aids the creation of innovative products that enable digital innovation [19]. It is important for technical organizations to be acquainted with their training protocol if they want an innovative and different internal structure; therefore, they must design the training protocol to support AI adoption in their technology management and processes, as these tools provide easy access to the knowledge and information for the design of innovative products and services in the organization.
The current study contributes to the theory and extends the existing knowledge by adding AI adoption as a major antecedent of digital innovation. The importance of the adoption of AI helps management to innovate the traditional patterns for analyzing, sharing, and storing information. This study also emphasizes the preconditions, such as AI and digital resilience, which support the implementation of digital innovation in firms. A comprehensive Theoretical Model is developed based on previous studies, and it is tested. The main contribution of this study to the existing literature is an explication of the role of digital resilience as a mediator. This study provides some insights to practitioners and managers concerning how AI adoption is implemented and used to foster the operational functions in organizations for the achievement of digital innovation, and how it decreases cost and saves time for repetitive tasks. Our study also contributes to the stream of practical implications by providing unique insights into the practical management of the development of digital innovation through AI adoption, digital resilience, and training protocols.

2. Literature Review

AI adoption refers to the use of AI applications and capabilities such as computer vision and machine learning to boost unique strengths and enhance business efficiencies [4]. AI adoption helps the business to improve its customer services and design innovative products to accelerate innovation solutions in business functions [10]. Digital resilience refers to an individual’s understanding of how to safely engage in different challenges and emerging opportunities using digital technologies, and how to handle appropriate issues and crises such as cyber-attacks. It is the vibrant personality assets that help when someone is in danger online, along with knowing what actions to take and how to handle challenges when something functions incorrectly [8,10]. Digital innovation refers to the development of the advanced innovation market offerings, models, and business practices using the latest digital technologies [7]. It facilitates business in innovative idea design through the latest digital applications that increase the response speed to market changes and provide competitive benefits for improving the quality of innovative products/services [15]. The training protocol is the set of rules and policies used for developing an individual to an agreed proficiency standard. It comprises the instruction of proper conduct and the practices that must be followed when communicating with others via electronic devices [19].

2.1. Hypothesis Development: AI Adoption and Digital Innovation

In the contemporary era, the adoption of AI advancements can change the pattern of information processing in different fields such as marketing, recruitment, financial management, etc., which improves the digital innovation practices in firms [20]. AI adoption leads to incredible changes and advancement in worldwide, which increases the profitability, productivity, and digital innovation of the firm, and reduces the risk mitigation in the firm, which improves customer loyalty [21]. AI adoption can support multifaceted analysis and reckoning tasks that were previously performed using human proficiency, which is the foremost factor for the redefinition of digital innovation boundaries among machine and human specialist expertise [2]. AI adoption can lead to the diffusion of the latest technology applications, which helps in the redesigning of various business practices [22]. The latest advancements in AI have the potential to accelerate digital development and the invention processes of innovation, which aids the designing of novel products/services in firms by influencing their data analysis via computational power in the difficult competitive environment [23]. Therefore, AI adoption provides new patterns for the processing of information, which helps to introduce novel ways of digital innovation in technology firms. AI adoption helps in the storage and sharing of digital information in firms through the re-programmability and self-referencing ability that increases the digital innovation in firms [24]. Digital innovation is the formation of the advance market offerings, models, and business practices resulting from the usage of AI adoption applications [25]. AI adoption permits artifacts to combine the experience of users, e.g., by phone and internet content, and focuses on the transformational role that is enabled by the re-programmability and variation of the features [26]. AI adoption can help in the generation of innovative products and services that promote the capturing of new business value through digital innovation [27]. AI adoption increases the artifacts’ ability to build functional and value-driving links with other performers, and it allows multiple technology systems to be used simultaneously by different users/artifacts [21]. Digital innovation is a versatile phenomenon that is linked with the creation, exploration, and combination of various roles that are enabled through AI adoption.
Hypothesis 1.
AI adoption predicts digital innovation.

2.2. Digital Resilience as Mediator

AI adoption applications focus on the improvement of a person’s digital resilience-related ability to cope with emerging risks in online activities that act as hurdles in transformational activities and cause financial or reputational loss [28]. The advancements in AI demonstrate how one’s digital resilience ability increases security levels and maintains the high-performance level of the innovation processes that increase digital innovation practices in a given firm. Previous studies also show that employees with a high digital resilience are capable of interacting with both innovation practices and security needs [29]. The latest AI adoption advancements increase firms’ digital resilience capability, which helps them to increase innovation processes and design new products and services that help them to grow and obtain maximum profit in the emerging market [30]. Digital resilience is the capability of an employee to deal with the anticipated results of adverse cyber incidents encompassing both planned and unplanned acts [31]. AI adoption is a pre-requisite for increasing the individual’s digital resilience ability, which helps them to understand online risks and gives them emotional strength for dealing with the adversity and hardship, thus increasing digital innovation in the firm [32]. Digital resilience acts as a bridge between AI adoption and a firm’s digital innovation. Digitally resilient firms use their resources and their employees’ skills to cope with challenges and acquire opportunities that enhance digital innovation [33]. AI adoption supports a person’s ability to act resiliently and overcome different technological challenges and security threats through their high digital resilience ability by innovatively performing different work practices to design novel products and services that increase the level of digital innovation in the firm [34]. AI adoption is concerned with the artifacts’ behavior, which involves learning, acting, perceiving, and communicating in the complex environment, whereas employees’ digital resilience ability enables them to operate in difficult and upsetting situations by reducing financial loss and reputational damage by increasing innovation activities and implementing practices that increase digital innovation in the firm [35]. AI adoption helps in measuring how well individuals’ digital resilience ability supports the adaptation of the latest technological changes. The implementation of these technological changes in firms increase the flexibility of their digital innovation processes [36].
Hypothesis 2.
Digital resilience mediates the association between AI adoption and digital innovation.

2.3. Training Protocol as Moderator

AI adoption facilitates the innovation processes that are critical in the growing need for the accomplishment of digital innovations in firms [37]. The training protocol is the system of rules/principles that enhance firms’ digital technology proficiency through instructions and facilitate businesses’ use of the latest digital applications, which provides ideas for novel innovative product/services development and accelerate firms’ digital innovation performance [38]. AI adoption helps in the design of firms’ innovative operational methods through the use of advance digital technology applications, which consequently direct how assessments and operations are performed [39]. The training protocol assists the firms in obtaining a better understanding and knowledge of novel technologies that augment their digital innovation performance and productivity [40]. AI adoption facilitates the designing of innovative products/services through digital technologies that increase the value creation of the products for customers and innovation practices in firms, which enhances digital innovation in firms [41]. The training protocol is the set of rules and regulations that increase an individual’s ability to resist extremism and hate online, and which motivates them to take part in the latest online communities to conceptualize innovative product designs [42]. Training protocols strengthen the association between AI adoption and digital innovation through instruction and practices related to specific competencies. AI adoption aids the implementation of the latest digital technologies that help businesses to remain competitive in the modern emerging marketplace through successful and efficient operational practices, such as the launching of innovative products/services [43]. The training protocol is the set of principles that deal with media literacy and digital skills, particularly towards the challenges of intolerance, online hate speech, and the latest technology applications that fulfill informatics requirements about speed and demand changes to the design of innovative products for consumer [44].
Hypothesis 3.
The Training protocol plays the moderating role between digital resilience and digital innovation.

2.4. Theoretical Framework

Figure 1 shows the Theoretical Framework of study.

3. Methodology

3.1. Research Design

This research study used a cross-sectional approach for the survey. The inspected element in this research comprises technological firms in Pakistan that use different AI adoption applications for innovation activities in enterprises of different sectors. Digital innovation is mostly dependent on the latest digital technology applications and the digital resilience ability of the firm employees, which support the responsible and safe use of online applications. The main strength of this study is that the results generalized from small sample are applicable to the whole population.

3.2. Data Collection

Data collection was performed using questionnaires and interviews. Four criteria were set for the selection of sample firms: first, the firms must be based on IT and use digital technologies for business operations; second, firms must deal with customers via online transactions; third, firms should be regularly involved in the development and adoption of IT applications in their firm; finally, firms should be operating from last 6 years’ experience in IT applications implications and provide/introduce innovative software/applications to emerging markets for overcoming the traditional practices in various firms. Questionnaires were distributed through research assistants in the hard-form to include only permanent employees who have more than 5 years of experience with an IT-related position and education. Respondents were IT Specialists, Software Engineers, and other technology-based position holders. A total of 450 questionnaires were dispersed among participants, and after 1 month 395 questionnaires were returned to the research associates; after checking for missed and incomplete information, only 357 questionnaires were completed and useable for the analysis. A total of 55 questionnaires were discarded for being incompletely filled and not useable for further analysis. The return rate of the questionnaires was 87.77%. Before the distribution of questionnaires, the questionnaires were checked by experts and academics and their feedback was appropriately considered appropriately, thus verifying the validity of study instruments. These experts were informed about the purpose and scope of the study before assessment.
Structural equation modeling was employed for examination of the information. The information about demographic factors such as age, which was between 25–55 years; education; and field experience was gathered and examined.
Questionnaires of this study comprise 2 sections. Section 1 contains demographic variables such as age, education, work experience, etc., and Section 2 consists of items used for research constructs (Appendix A).

3.3. Measurement of the Variables

All variables of this research were calculated with previously used and designed scale. Questionnaires were examined through pilot test to check the validity, accuracy, and reliability of measures. For the measurement of items, 5-point Likert scale was used, i.e., strongly agree = 1 to disagree strongly = 5. The measurements of variables are discussed below.

3.3.1. AI Adoption

The AI adoption is measured through 7-item scale adapted from [45].

3.3.2. Digital Resilience

For the measurement of digital resilience, we used 7-item scale adapted from [46], which was previously used by the researchers [47,48].

3.3.3. Digital Innovation

Our study used 6-item scales for the measurement of digital innovation, which was adapted from [49].

3.3.4. Training Protocol

To measure the Training Protocol, we used the 3-item scale developed by Gagneur et al. [50].

3.4. Discriminant and Convergent Validity

Discriminant and convergent validity were measured in Table 1. According to the approach of Fornell and Larcker [51], the Average Variance Extracted (AVE) was higher than 0.50. The Composite reliability (CR) was determined and found to be greater than 0.60. Table 1 also shows the result of Cronbach alpha (α), which was higher than 0.70. Therefore, all the verified and measured results that were used in the study were reliable and valid.

3.5. Confirmatory Factor Analysis

Table 2 shows the confirmatory factor analysis (CFA) to check the difference of study variables of AI Adoption, Digital Resilience, Training Protocol, and Digital Innovation. Our hypothesized model examined the best model. Our four-factor model was fit to data and three alternative models were rejected. The fit keys, χ2 = 1020.56, Df = 490, χ2/df = 2.083, CFI = 0.92, and GFI = 0.93, RMSEA = 0.05, showed the overall model fitness. The model fitness was verified according to Anderson and Gerbing.

3.6. Correlation Result

Table 3 shows the results of correlation. The results are presented in Table 3. Artificial intelligence (AI) Adoption was positively significant with DI (r = 0.238*), Digital Resilience was positively predicted with DI (r = 0.289**), and TP was positively associated with DI (r = 0.385**). The VIF scores were below the cut-off value of 10.0, indicating that multi-collinearity is not a problem.

4. Analysis

4.1. Hypothesis Testing: Direct Effect of AI Adoption on Digital Innovation

Table 4 shows the different paths (a, b, c, and cʹ). AI Adoption was positively associated with DI (β = 0.2687, t = 3.8725, SE = 0.0687, p < 0.001→ ‘c’ path was significant). AI Adoption positively and significantly affected Digital Innovation; hence, it was proven that in IT-based firms, the major antecedent of digital innovation is AI adoption. AI adoption allows firms to be flexible enough to adopt any required changes. This adaptive skill and the ability to upgrade technologies lead to digital innovation. Hence, our theory was accepted regarding H1, and it was proven based on the lived experience of IT professionals.

4.2. Mediating Effect of Digital Risilience

The results proved that AI adoption was positively related to digital resilience (β = 0.4237, t = 7.3458, SE = 0.0542, p < 0.001→ ‘a’ path was significant). Digital resilience was positively predicted with DI (β = 0.3476, t = 7.0605, SE = 0.0417, p < 0.001→ ‘b’ path was significant). The results also proved that when digital resilience was controlled, the direct effect of AI adoption on DI was non-significant, indicating a full mediation (β = 0.1476, t = 1.6325, ns, showing that ‘c’ path was non-significant). H2 proposed that the relationship between AI adoption and DI is mediated by digital resilience.

4.3. Moderation Effect of Training Protocols

We used a hierarchical regression to determine the moderation effect of the training protocol on the direct link of AI adoption and DI presented in Table 5. H3 proposed the positive moderation effect of the Training protocol in the relationship between AI adoption and DI. Model 1 showed the result of the control variables and model 2 showed the result of the independent variable with the dependent variable. Model 3 showed the result of the moderation effect and indicated that the TP was a positive moderator and had a significant role in the relationship between AI Adoption and DI, i.e., (β = 0.16**, p < 0.01). Hence, H3 was accepted.

5. Discussion

The proposed conceptual model in this research was used to examine the outcomes of AI adoption in digital innovation through the mediating role of digital resilience and the moderating effect of training protocol. The critical role of AI adoption in the workplace has grown to be a significant need for executives and scholars to comprehend the factors that encourage digital innovation. To become innovative, organizations must consider AI adoption as an essential factor that stimulates digital innovation. Nevertheless, digital resilience insights do not automatically emerge, and individuals must develop digital resilience through an improved knowledge of good or bad, fake or true, and risk or opportunity in online activities. Individuals should train themselves to better understand and develop their digital resilience.Regarding AI adoption, it positively influences digital innovation. Therefore, in this study, H1 is supported by the fact that In the contemporary era, the adoption of AI advancements can change the pattern of information processing in different fields such as marketing, recruitment, financial management, etc., which improves the digital innovation practices in firms [20]. AI adoption leads to incredible changes and advancement in worldwide, which increases the profitability, productivity, and digital innovation of the firm, and reduces the risk mitigation in the firm, which improves customer loyalty [21]. AI adoption can support multifaceted analysis and reckoning tasks that were previously performed using human proficiency, which is the foremost factor for the redefinition of digital innovation boundaries among machine and human specialist expertise [2]. AI adoption can lead to the diffusion of the latest technology applications, which helps in the redesigning of various business practices [22]. The latest advancements in AI have the potential to accelerate digital development and the invention processes of innovation, which aids the designing of novel products/services in firms by influencing their data analysis via computational power in the difficult competitive environment [23]. Therefore, AI adoption provides new patterns for the processing of information, which helps in introducing novel forms of digital innovation in technology firms. AI adoption helps in the storage and sharing of digital information in the firms through re-programmability and self-referencing ability, which increases digital innovation in firms [24]. AI adoption provides an enhanced understanding that drives high digital resilience characteristics in individuals, which facilitates the driving and increasing of digital innovation in firms. The H2 of our study corroborated that digital resilience plays the mediating role in the association between AI adoption and digital innovation. AI adoption can help in sharing and collecting data with the assistance of different applications that successively lead to improved digital resilience features and the improved development of new products and services. Digitally resilient firms are capable of designing innovative products and services and can attain digital innovation. Previous research shows that AI adoption applications focus on the improvement of digital resilience-related ability of a person to cope with emerging risks in online activities that act as hurdles in the transformational activities and cause financial or reputational loss [28]. Advancements in AI demonstrate how the digital resilience ability increases security levels and maintains the high-performance levels of the innovation processes that increase digital innovation practices in firms. Previous studies also show that employees with a high digital resilience are capable of interacting with both innovation practices and security needs [29]. The latest AI adoption advancements increase firms’ digital resilience capability, which helps them to increase innovation processes and design new products and services that help them to grow and obtain maximum profit in the emerging market [30]. Digital resilience is the capability of an employee to deal with the anticipated results of adverse cyber incidents encompassing both planned and unplanned acts [31]. AI adoption is the pre-requisite to bolstering an individual’s digital resilience ability, which helps them to understand the online risks and provides emotional strength for dealing with adversity and hardship, which increases the digital innovation in firms [32]. Digitally resilient firms use their resources and employees’ skills to cope with challenges and acquire opportunities that lead to enhanced digital innovation [33]. Training protocols help to increase the digital resilience ability of employees, and if firms adopt AI applications, it assists HR managers in their selection of the right candidates and provides better control and decision-making power for the development of novel products that improve digital innovation. The H3 reveals that training protocols moderate the relationship between AI adoption and digital innovation. The H3 outcomes support the previous studies’ results that AI adoption facilitates the innovation processes that are critical regarding the growing need for accomplishing digital innovation in firms [37]. The training protocol is the system of rules/principles that enhance digital technology proficiency through instructions in firms and facilitate businesses’ use of the latest digital applications, which provide ideas for novel innovative product/services development, and accelerate firms’ digital innovation performance [38]. AI adoption helps in the designing of innovative operational methods in firms through the help of advanced digital technology applications, which consequently direct how assessments and operations are performed [39]. Training protocols assist the firms inobtaining a better understanding and knowledge of novel technologies that augment their digital innovation performance and productivity [40]. AI adoption facilitates the designing of innovative products/services through digital technologies, which increase the value creation of the products for customers and innovation practices in firms that enhances digital innovation in firms [41]. The training protocol is the set of rules and regulations that increase the individual’s resilience towards extremism and hate online and motivates them to take part in the latest online communities to conceive of innovative product designs [42]. Training protocols strengthen the association between AI adoption and digital innovation through instruction and practices related to specific competencies. AI adoption helps in the implementation of the latest digital technologies that help businesses to stay competitive in the modern marketplace through successful and efficient operational practices such as the launching of innovative product/services [43].Overall, this research study adds to the existing knowledge through the combined influence of AI adoption, digital resilience, digital innovation, and training protocols by means of showing when, why, and how AI adoption help firms in the achievement of digital innovation.

5.1. Theoretical Implications

This research adds to the theory in following ways. Firstly, a comprehensive theoretical model was developed showing the interplay among AI adoption, digital resilience, training protocols, and digital innovation. We added that digital innovation is bolstered through AI adoption, which offers newest ways for sharing, analyzing, and reckoning of the information and knowledge. AI adoption determines digital innovation, and this interplay is mediated through digital resilience about which the literature is silent. This is a pertinent contribution to the theory. Accordingly, AI adoption helpsto generate novel methods and ideas for digital innovation activities through available resources. We identified that AI adoption enables firms to develop digital resilience to resist the targets of digital innovation. This digital resilience fosters the operational functions in organization for the achievement of digital innovation through decreasing cost and saving time for repetitive tasks. This study enriches the literature by adding the moderating role of training protocols in the relationship between AI adoption and digital innovation. The adoption of digital technologies and AI is not a simple task. This study added to the theory that training is an important activity and that the impact of AI adoption on digital innovation will be more rapid and effective when leveraged by training protocols. This study extended the innovation theory by focusing on digital innovation through AI adoptions, i.e., it is a newly added factor. This research also adds to the theory of dynamic capability through emphasizing the adoption of AI and digital resilience abilities of firms for improving digital innovation.

5.2. Practical Implications

This study also offers various implications for management in practice. This study recommends that management should consider the latest technologies and adopt AI. This is the arena of digital technologies and firms need to understand the importance of digital innovation. The results of this study show that management should be more flexible to adopt the required changes and have the ability to sustain digital innovation. We offered a practical model that enables firms to extract value from customers by designing innovative products/services that help to meet their demands. Management should consider timely training sessions for their employees and these training sessions will boost the learning process, which can in turn foster the link between AI adoption and digital innovation. The training protocol programs in organizations facilitate practitioners to value how digital technology can increase innovation activities and how a firm’s strategies can harmonize to obtain competitive benefits. This study provides important insights that facilitate scholars’ and practitioners’ understanding and comprehension of the research on how organizational managers can adopt AI applications and use them to bring digital innovation in firms. The current study provides unique insights to HR managers towards the selection, recruitment, and decision-making process using AI applications and proper training.
This study guides management and suggests that using traditional working tool cannot bring digital innovation without implementing AI adoption and digital resilience. Experienced persons who use AI applications in their firm and are digitally resilient specialists can help to increase digital innovation. The digital resilience ability of an employee can help to obtain digital innovation in firms through AI applications. In this regard, this study recommends that management should change their traditional methods and adopt the latest AI advancements to acquire digital innovation in their firms with high digitally resilient employees.

5.3. Directions for Future Research and Limitations

The current study has some limitations that act as direction for future research. Firstly, we anticipated to distribute questionnaires to employees in different work settings within technology firms, mostly high-level positions such as owners, CEOs, and managers, to collect information regarding the implementation process of AI applications. However, our study failed to obtain the perspectives of other working employees who used AI applications during their work. Therefore, future research might consider further employees in different positions that use AI during work. Secondly, in this study, we employ a quantitative approach for the collection of data, which shows the association between variables, but does not explain why this relationship exists. Furthermore, a qualitative research method can be used in the future research studies to determine such a relationship. Thirdly, we inquired into how AI adoption is used and how it helps in the collection and analysis of information. Although these processes perform vital roles in firms, they do not sufficiently explain other daily activities. Thus, this bounds our understanding concerning other activities in firms such as planning, decision-making, and others. Fourthly, the data collection was performed on different technology firms. Thus, future studies should be conducted in different countries with larger sample sizes. Digital resilience was tested as a mediating variable in this study; in future studies, comprehensive research could be performed to investigate digital resilience and its outcomes. Finally, the current study emphasizes the positive outcomes of digital resilience that can develop and are carried out through AI adoption and progress digital innovation. In future studies, researchers can determine the negative outcomes of digital resilience that are relevant to the concept and are affected through the latest digital technology.

Author Contributions

Conceptualization, X.Z.; methodology, Z.Y.; software, Z.Y.; validation, X.Z.; writing—original draft preparation, X.Z.; supervision, Z.Y.; project administration, S.L.; All authors have read and agreed to the published version of the manuscript.

Funding

National Natural Science of China, Grant/Award Number: 71872148.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of GovtCollege.of.Management.Sciences-Mansehra-Pakistan ref approval ID: (GCMS-Msr/213; dated 4 Febuary2022).

Informed Consent Statement

All participants provided ICS.

Data Availability Statement

Due to confidentiality purposes, data are not publicly available.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
Table A1. Questionnaire.
Table A1. Questionnaire.
VariableItemsConstructs
AI adoptionAIA1AI adoption is more cost effective than other technologies
AIA2AI adoption saves cost and time related to other terminologies
AIA3AI adoption saves time, effort, and cost required for relative advantages
AIA4AI adoption assists human resource managers in their selection of the right candidate
AIA5AI adoption facilitates enhanced quality decisions for recruitment and selection
AIA6AI adoption increases the effectiveness of technology related actions
AIA7AI adoption provides control and better speed for decisions related to security and confidentiality
Digital resilienceDR1Digital technology use disturbs the regular activities (reversed)
DR2Digital technology takes time that I want to use for the studying (reversed)
DR3I waste more time in non-academic activities and postpone learning/studying when I use technology tools (reversed)
DR4Digital tools can help me in presentations through text/images, for instance, in powerpoint
DR5I have used different collaborative tools such as Google Docs and Wikispaces for online writing
DR6Digital tools motivate me and help me in my studies
DR7Technology applications help me in solving study problems
Digital innovationDI1We use superior quality digital solutions as compare to competitors
DI2We use digital solutions that have more features as compared to competitors
DI3We use totally different applications of the digital solutions from competitors
DI4We use different product platform as compare to competitors
DI5We improve our existing products through new digital solutions
DI6We launch some new digital solutions in the market
Training protocolTP1In our firms, training is regularly scheduled
TP2We have acccess to all trainers when we need it
TP3We follow all procedural activities in training, as it is an important part of our firm

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Sustainability 14 08286 g001 550
Figure 1. Theoretical Framework.
Figure 1. Theoretical Framework.
Sustainability 14 08286 g001
Table
Table 1. Results of Factor Loading, CR & AVE).
Table 1. Results of Factor Loading, CR & AVE).
Variable DescriptionFLT-ValueAlphaCRAVE
AI Adoption 0.830.920.64
AIS-10.8415.47
AIS-20.7714.23
AIS-30.8114.57
AIS-40.8215.45
AIS-50.8114.55
AIS-60.8014.21
AIS-70.7613.55
Digital Resilience 0.820.920.63
DR-10.8315.63
DR-20.7714.12
DR-30.8415.52
DR-40.8214.47
DR-50.7213.44
DR-60.7814.54
DR-70.8215.52
Training Protocol 0.860.820.60
TP-10.8215.21
TP-20.7714.51
TP-30.7213.52
Digital Innovation 0.840.890.58
DI-10.8615.47
DI-20.7615.12
DI-30.7514.63
DI-40.7314.41
DI-50.7414.55
DI-60.7213.52
Table
Table 2. Confirmatory Factor Analysis (CFA).
Table 2. Confirmatory Factor Analysis (CFA).
Model Detailχ2Dfχ2/dfRMESAGFICFI
Hypothesized four-factor model1020.564902.0830.050.930.92
Three-factor model1165.423803.0670.130.840.87
Two-factor model1270.323953.2160.180.750.76
Single-factor model1347.213563.7840.220.650.67
Table
Table 3. Correlation Results.
Table 3. Correlation Results.
Variable Description12345678
1Business Age1.00
2Business Size0.121 **1.00
3Respondent Experience0.203 **0.85 *1.00
4Respondent Education−0.040.060.061.00
5AI Adoption−0.01−0.190.02−0.201.00
6Digital Resilience0.05−0.060.096 *−0.030.171 **1.00
7Training Protocol−0.08−0.14−0.060.086 *0.263 **0.367 **1.00
8Digital Innovation0.03−0.13−0.04−0.120.238 *0.289 **0.385 **1.00
Note: ** p < 0.01, * p < 0.05.
Table
Table 4. Indirect Effect of Path (a, b, c & c’).
Table 4. Indirect Effect of Path (a, b, c & c’).
Path DetailsBetaT-ValueSESig
AI Adoption to Digital Resilience→(Path a)0.42377.34580.05420.000
Digital Resilience to Digital Innovation→(Path b) 0.34767.06050.04170.000
Total effect of AI on DI→(Path c) 0.26873.87250.06870.000
Direct Effect of AI to DI→(Path c’)0.14761.63250.07670.1374
Table
Table 5. Hierarchal Regression results for the moderating effect of Training Protocol.
Table 5. Hierarchal Regression results for the moderating effect of Training Protocol.
Digital Innovation
DetailBetaT ValueBetaT ValueBetaT Value
Model1
Business age0.040.180.020.160.010.13
Business size0.050.130.130.840.130.76
Respondent education0.140.260.150.321.041.23
Respondent experience0.160.290.190.940.050.22
Model 2
AI Adoption 0.34 ***7.560.38 ***5.43
Digital Innovation 0.24 ***5.350.34 ***4.46
Model 3
AI Adoption × Training Protocol 0.16 **2.256
F 6.23 *** 16.58 *** 17.42 ***
R2 0.03 0.24 0.25
ΔR2 0.21 0.01
Notes: *** p < 0.001, ** p < 0.01.
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Zeng, X.; Li, S.; Yousaf, Z. Artificial Intelligence Adoption and Digital Innovation: How Does Digital Resilience Act as a Mediator and Training Protocols as a Moderator? Sustainability 2022, 14, 8286. https://doi.org/10.3390/su14148286

AMA Style

Zeng X, Li S, Yousaf Z. Artificial Intelligence Adoption and Digital Innovation: How Does Digital Resilience Act as a Mediator and Training Protocols as a Moderator? Sustainability. 2022; 14(14):8286. https://doi.org/10.3390/su14148286

Chicago/Turabian Style

Zeng, Xiaochun, Suicheng Li, and Zahid Yousaf. 2022. "Artificial Intelligence Adoption and Digital Innovation: How Does Digital Resilience Act as a Mediator and Training Protocols as a Moderator?" Sustainability 14, no. 14: 8286. https://doi.org/10.3390/su14148286

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