During the last decade, the literature and industry have emphasized Artificial Intelligence (AI) and Big Data technologies, particularly breakthroughs in machine learning approaches. While AI and big data can tackle a broad variety of issues, practical implementation and a lack of understanding about how to strategically employ AI to create economic value remain hurdles. The rising trend toward digitization is affecting businesses of all sizes and sectors. To stay competitive in the future, organizations must grasp and resolve digitalization’s long-term benefits and challenges. Businesses should ensure their survival in the digital age by implementing a comprehensive digitization strategy that incorporates all aspects of their operations. This paper seeks to determine the implications of Dataism and its role in shaping the future of corporate strategy.

1.0 Introduction

As a consequence of the rapid transformation of the traditional economy into a digital and intelligent economy powered by artificial intelligence, big data, cloud computing, blockchain, and the industrial internet, digital transformation has become a critical mechanism for businesses to achieve breakthrough innovation and long-term growth. According to a recent analysis conducted by International Data Corporation (IDC FutureScape: Global Digital Transformation Forecast in 2021), direct investment in digital transformation would exceed USD 6.8 trillion between 2020 and 2023. As a result of COVID-19,” digitalization has been critical in reviving and rehabilitating businesses (Zhang et al., 2021). There is a widespread belief that digitization is an excellent method to increase organizational resilience. To put it differently, adaptability is described as an organization’s capacity to absorb, respond to, and ultimately adapt to disruptive events that threaten its survival.

Digital transformation has evolved From a technological opportunity into a crucial component of meeting the demands and objectives of the world’s rising population. Digital transformation’s new processes and procedures can alter the fundamental foundations of how a business operates, which has resulted in significant changes in several organizations. However, Benlian et al. (2018) assert that firms that do not accelerate their digital transformation efforts would struggle to compete in the new digital environment. However, this new reality should not be overlooked, as each transition process has unique risks and problems.

However, as far as we are aware, no empirical study has been conducted on the impact of digital transformation on organizational resilience. According to Helbing & Hausladen (2022), there are two divergent perspectives on the influence of the digital revolution on society. The functional school of strategies asserts that organizations can successfully manage risks and adapt to changing environmental conditions due to digitalization (Appio et al., 2021). For instance, big data is the bedrock for data analysis and processing. Digital transformation and other digital technologies may assist businesses in making informed decisions during times of crisis and increase the resilience of supply chains and platform ecosystems. Stylos & Zwiegelaar (2019) discovered via their research that social media might help communities strengthen their resilience in the face of adversity. Despite this, dysfunctional schools view digital change as a threat to businesses, believing it would negatively impact them. This article examines the influences of digital transformation on strategic behavior and the social conditions essential for successful digital strategy.

2.0 The Impacts of Dataism on our Societies

With the rapid digital transformation, firms now desire lower wait times and more awareness. Numerous firms have embraced cutting-edge technology to increase efficiency and acquire a competitive edge. Artificial Intelligence has garnered scientific and industry attention (Kitsios & Kamariotou, 2021 ). Artificial intelligence (AI) is defined as a computer’s capacity to learn from its experiences, adapt to new inputs, and do jobs that people perform. As previously said, artificial intelligence (AI) may be the most disruptive innovation of the twenty-first century. Similarly, artificial intelligence (AI) is the domain’s fundamental general-purpose technology, particularly machine learning tools.

Digital transformation, to adapt to rapid and unpredictable change, demands the merging of the “digital world” and the “physical world,” According to Scholz (2017), organizations’ risk assessment and resilience management processes must be reinforced during times of transformation. Over half of the businesses he spoke with are underperforming or on the verge of going out of business due to their digital transformation initiatives. Zhang et al. (2022) recently disclosed that organizations would rebuild their organizational competence, develop ambidextrous organizational capability, and deal with the obstacles associated with digital transformation during the digitization process. The dynamic capability hypothesis posits that digital transformation initiates developing dynamic capability by reengineering internal and external resources, processes, and structures (Hung et al., 2010). Both exploratory and exploitative innovation are included in an organization’s ambidextrous capabilities

On the other hand, some entrepreneurs are fearful of the reality of digital transformation. The term “waiting for death without transformation or dying faster from transformation” has come to represent the digital revolution in recent years. Digital transformation, on the other hand, has the potential to disrupt existing corporate practices and structures; thus, firms are concerned about the potential impact on their operations. Entrepreneurs are frequently baffled by digital development’s complexity and imprecision (Nwankpa & Roumani, 2016). When it comes to digital transformation, it’s essential to address the inherent conflicts that develop and strengthen businesses’ organizational resilience.

An organization’s present resources and capabilities can be restructured by exploratory innovation, whereas they can be expanded by exploratory innovation. Making the most of present assets and capabilities while also generating new resources and capabilities consistent with earlier development pathways is achievable (Zhou & Wu, 2010). “Ambidexterity” refers to a business’s potential to simultaneously investigate and exploit new prospects while also altering its strategy overtime in the dynamic world of business. As a result, this theory sheds light on the link between organizational resilience and digital transformation. Some of the key influences of Dataism on society are discussed below;

2.1 Aligning Dataism with Human Values

There appears to be a bigger risk of big data and algorithms taking over if they are employed for the sake of data flow rather than for objectives other than those we as humans intend. “good human goals” (however precisely defined) account for a negligible proportion of all feasible objectives. Because there are no alternatives, we must do all possible to mitigate their impact on the global society (Larsen, 2020).

The long- and short-term advantages, on the other hand, are substantial. According to Harari, democracy is under threat due to the transfer of power to “data,” which he views undesirable. One may respond by highlighting present democratic shortcomings and the promise of new technology to strengthen democracy (Araki, 2020).

Even the intrinsic value of human life has been questioned in its current state. The world would be a much better place if we could replace humans with clever and caring machines. Even though it seems improbable, it motivates us to work for it.

2.2 Societal Perception of Digital Transformation

Numerous facets of society must be considered while creating a successful digital strategy. Apart from impacting individual firms, technological advancements may profoundly affect how consumers perceive value in general. A data-driven economy no longer stresses a product’s unique characteristics. Nowadays, it’s all about efficiency, convenience, and simplicity of use (Cantamessa et al., 2020). Individual end-users drive the digital revolution, whether sales are made directly to consumers or through business-to-business (B2B) models. It is a model for established businesses to adapt to the digital era via B2B digital transformations. In a nutshell, innovation is driven by society’s value systems. There is a clear link between this increased demand for technologically advanced products and services and the components required to connect them to the Internet of Things. Clients may be unaware of their contribution to technical developments in research laboratories.

2.2.1 Effects on the perception of service innovation and value

As several articles have demonstrated, digital transformation and company strategy are inextricably linked. We investigated approaches for using digital transformation to enable machine-to-machine communication in new organizational opportunities but eventually abandoned our proposals. On the other hand, several studies discovered that enterprises benefited from new product development and additional services (Chae, 2014). According to Zaki, artificial intelligence has the greatest influence on industry innovation (2019). For instance, Kohler et al. (2014) assert that machine learning and artificial intelligence (AI) rapidly alter the way humans communicate with one another, enabling novel forms of human-machine interaction. Few publications have addressed customer experience, making it challenging to leverage digital transformation technology for customer and employee engagement properly. Due to the complexity of using artificial intelligence (AI) in human contact, Holmlund et al. (2020) .’s findings cannot be generalized. Humans may be unaware they are being served or evaluated by a machine. The firm may find itself in hot water, depending on how this unfolds.

Firms may

gain a competitive edge by leveraging digital transformation technology to improve user experience and engagement with digital strategy-driven apps. Businesses will be able to use the cognitive potential of the new digital revolution through the development of new goods. To capitalize on the new era of artificial intelligence and create innovative goods and solutions, there must be alignment between competitive and cognitive strategies (Ross et al., 2017). Businesses must leverage cutting-edge digital transformation technologies and a well-defined business strategy that balances business requirements, regulatory constraints, and automation to remain ahead of the competition. As a result, CEOs in the age of digital transformation must also be adept at developing competitive and cognitive strategies. As a result, it is critical to understand why individuals utilize cognitive technology products and services.

2.3 Organizational Implications

Businesses should accelerate their digital transformation activities to increase their resilience to digitalization. When it comes to overcoming uncertainty and change, digital transformation is an inventive approach that assists firms in overcoming pain. With digitalization’s long-term influence on companies, senior executives must possess digital thinking talents and professional expertise and understand the organization’s internal and external settings to thrive. It is required to assess and grasp the underlying logic of company development via digital transformation (Privono et al. 200), integrate, control, and manage internal and external human, material, and financial resources, and establish an effective digital strategy.

Future business intelligence and real-time decision-making analysis and visualization tools will maximize the value of data, aid businesses in intuitively identifying concerns, forecasting market changes, and supporting decision-makers in making future operations more adaptive and robust. Organizational resilience cannot be attained only through digital transformation; businesses that do not transition may struggle to maintain high levels of organizational resilience. As a result, businesses must develop digital transformation plans tailored to their unique resource endowments to boost organizational resilience (Gobble, 2018).

Exploratory and exploitative innovation can be coupled to increase organizational resilience through digital transformation. When exploratory and exploitative innovation activities are used, organizational resilience and digital transformation are linked. Entrepreneurs must be aware of and explain current industry trends and strengthen their organization’s capacity to identify future opportunities. Similar to how profitable innovations are pushed and existing operations may be altered and reconstructed in response to changes in the external environment, the organization’s current value system is frequently questioned (Gavrila & Ancillo, 2021). A company’s digital transformation plan may be used to incrementally improve existing capabilities and rebuild them through creative destruction in response to the external environment’s complexity and changeability.

Both exploratory and exploitation inventions are evenly balanced to keep the strain in control. Businesses must make the best judgments feasible despite perceived managerial inconsistencies. According to the research findings, businesses can increase their resilience by balancing exploitative and exploratory innovations. Organizational design principles such as segregating exploitative and experimental processes inside distinct organizational entities may be utilized to deploy a variety of innovations across several business units during the digital transformation process. Thus, the overall organization’s internal architecture reflects both the consistency of internal business unit operations and the internal business unit’s resilience to fast restructuring within the organization (Jones et al., 2021). A senior management team’s leadership style must balance short-term efficiency and long-term flexibility to deal with various managerial styles. While exploitative innovation should be favored for short-term stability, long-term flexibility and organizational resilience may be accomplished by combining exploitative and exploratory innovations as long as control and stability are prioritized.

3.0 Strategizing a Digital Future

Digitalization’s expanding relevance is affecting businesses of all sizes and sectors. The future success is contingent upon its capacity to identify and solve the long-term possibilities and difficulties presented by digitalization. Companies can develop a comprehensive digital strategy that includes all aspects of their business, allowing them to go through a complete digital transformation and assure their survival in the Digital Age (Rachinger et al., 2018).

Adapting to a new digital era necessitates a complete reengineering of an organization’s value chain to accommodate new technologies and digital demands. Businesses must change their business models and adopt new technology to remain competitive in the digital era. Adopting future (digital) business models demands businesses in the era of digitalization to have a well-defined strategic direction to optimize their value creation potential.

It is not an issue of when but how businesses execute digital transformation initiatives in this scenario. Businesses must coordinate their strategy at the corporate level to capitalize on the potential influence of new digital technology. Digitization is a critical strategic objective for the company, intending to lower costs, generate income, enhance efficiency, and introduce new business models (Fitzgerald et al., 2014). As a result, firms of all sizes and sectors must have a well-defined digital strategy.

3.1 Aligning Dataism with Business Strategy

According to Becker et al. 2020, aligning a business strategy and digital transformation process must encompass organizational and Dataism strategy and the infrastructure of business and IT operations. A company’s competitive edge is preserved by prudent AI use in this situation. Numerous theories, concepts, and approaches have been advanced in studying the relationship between information technology and corporate strategy and operations (Tallon & Pinsonneault, 2011). Digital technology has been rapidly growing its role in company planning. Some of the most crucial factors that need to be considered in strategizing a digital future are discussed below;

An organization’s ability to create and deploy evolving information technology must be shown before launching a digital strategy. Choosing whether to use current market technology or construct one’s own is critical for firms to gain market leadership. Digital innovations that have the potential to disrupt established business models must be prioritized by businesses of all sizes, according to Kitsios & Kamariotou (2021) and Becker et al. (2020). For businesses of all sizes, new digital technologies provide both possibilities and risks.

Because technical innovation influences a firm’s whole value chain, it frequently changes how additional value is produced. Businesses must determine how their new (digital) operations vary from their old, analog core business, as well as the markets and consumers they want to serve (Yin et al. 2020). Additionally, research indicates that value creation has migrated away from physical goods in favor of “intelligent” products and data. This enables businesses to diversify their product and service offerings, resulting in a greater need for technology and product-related skills. On the other side, businesses face increased risk since they typically lack experience in these emerging industries.

To properly address the difficulties of digital transformation and associated obligations, a firm must have an appropriate organizational structure to integrate new technologies and shift value-generating. Becker and associates (2020). In this situation, the whole organizational architecture of the corporation must be changed to changing conditions by optimally integrating new digital activities into corporate structures and their impact on commodities, processes, and talent inside the firm. This enables businesses to integrate newly developed tasks into current and new areas. Meanwhile, integrating new (digital) technologies necessitates “differences in mindsets and skillsets compared to previous waves of transformative technology,” from previous waves of transformative technology, as well as “differences in mindsets and skillsets” from previous waves of transformative technology (Fitzgerald et al. 2013). Additionally, an agile organizational structure coupled with flexible and agile working habits is critical for implementing changes more quickly due to the digital transformation.

Conclusion

To conclude, the world is swiftly moving toward a digital future that will significantly alter the way people work and the way they live. While the new Digital Transformation will bring numerous benefits, the introduction of the “smart factory” and the digitization of industry as a whole, or its constituent sectors, will inevitably result in changes to labor markets and work methods, as well as a transformation of the nature of work and employment. Simultaneously, social fragmentation and marginalization, as well as commercial networking and labor “flexibility,” are eroding the strength of some social groups, most notably labor unions. Businesses must adapt their corporate operational strategy to the digitally transformed business world to remain competitive and grow operations. Before defining a digital strategy, organizations must assess the strategic value of developing information technology and demonstrate their capability to develop and deploy it

References

Appio, F. P., Frattini, F., Petruzzelli, A. M., & Neirotti, P. (2021). Digital transformation and innovation management: A synthesis of existing research and a plan for future studies. Journal of Product Innovation Management, 38(1), 4-20.

ARAKI, N. (2020). Harari and Kaku. Bull. Hiroshima Inst. Tech. Research Vol, 54, 19-28.

Becker, W., & Schmid, O. (2020). The right digital strategy for your business: an empirical analysis of the design and implementation of digital strategies in SMEs and LSEs. Business Research, 13(3), 985-1005.

Benlian, A., Kettinger, W. J., Sunyaev, A., Winkler, T. J., & Guest Editors. (2018). The transformative value of cloud computing: a decoupling, platformization, and theoretical recombination framework. Journal of management information systems, 35(3), 719-739.

Cantamessa, M., Montagna, F., Altavilla, S., & Casagrande-Seretti, A. (2020). Data-driven design: the new challenges of digitalization on product design and development. Design Science, 6.

Chae, B. K. (2014). A complexity theory approach to IT-enabled services (IESs) and service innovation: Business analytics illustrates IES. Decision support systems, 57, 1-10.

Feldmann, N., Kohler, M., Kimbrough, S. O., & Fromm, H. (2013, February). Service innovation analytics: Towards an approach for validating frameworks for service innovation capabilities via text mining. In International Conference on Exploring Services Science (pp. 73-85). Springer, Berlin, Heidelberg.

Fitzgerald, M., Kruschwitz, N., Bonnet, D., & Welch, M. (2014). They are embracing digital technology: A new strategic imperative. MIT Sloan management review, 55(2), 1.

Gavrila, S. G., & Ancillo, A. D. L. (2021). Entrepreneurship, innovation, digitization, and digital transformation toward sustainable growth within the pandemic environment. International Journal of Entrepreneurial Behavior & Research.

Gobble, M. M. (2018). Digital strategy and digital transformation. Research-Technology Management, 61(5), 66-71.

Helbing, D., & Hausladen, C. I. (2022). Socio-economic implications of the digital revolution. Helbing. D. and Hausladen, C.(2022), Socio-Economic Implications of the Digital Revolution, in Chen, P., Elsner, W. and Pyka, A.(eds.), Handbook of Complexity Economics, Routledge, London, New York.

Holmlund, M., Van Vaerenbergh, Y., Ciuchita, R., Ravald, A., Sarantopoulos, P., Ordenes, F. V., & Zaki, M. (2020). Customer experience management in the age of big data analytics: A strategic framework. Journal of Business Research, 116, 356-365.

Hung, R. Y. Y., Yang, B., Lien, B. Y. H., McLean, G. N., & Kuo, Y. M. (2010). Dynamic capability: Impact of process alignment and organizational learning culture on performance. Journal of world business, 45(3), 285-294.

Jones, M. D., Hutcheson, S., & Camba, J. D. (2021). Past, present, and future barriers to digital transformation in manufacturing: A review. Journal of Manufacturing Systems, 60, 936-948.

Kitsios, F., & Kamariotou, M. (2021). Artificial intelligence and business strategy towards digital transformation: A research agenda. Sustainability, 13(4), 2025.

Kohler, M., Feldmann, N., Kimbrough, S. O., & Fromm, H. (2014). Service innovation analytics: Leveraging existing unstructured data to assess service innovation capability. International Journal of Information System Modeling and Design (IJISMD), 5(2), 1-21.

Larsen, M. (2020). Memory as tyranny: A dataset argument for posthuman interconnectivity in Humans and Real Humans. Memory Studies, 1750698020982062.

Liang, H., Wang, N., Xue, Y., & Ge, S. (2017). Unraveling the alignment paradox: how does business-IT alignment shape organizational agility?. Information Systems Research, 28(4), 863-879…

Nwankpa, J. K., & Roumani, Y. (2016). IT capability and digital transformation: A firm performance perspective.

Priyono, A., Moin, A., & Putri, V. N. A. O. (2020). Identifying digital transformation paths in the business model of SMEs during the COVID-19 pandemic. Journal of Open Innovation: Technology, Market, and Complexity, 6(4), 104.

Rachinger, M., Rauter, R., Müller, C., Vorraber, W., & Schirgi, E. (2018). Digitalization and its influence on business model innovation. Journal of Manufacturing Technology Management.

Ross, J. W., Beath, C. M., & Sebastian, I. M. (2017). How to develop a great digital strategy. MIT Sloan Management Review, 58(2), 7.

Scholz, R. W. (2017). Digital threat and vulnerability management: The SVIDT method. Sustainability, 9(4), 554.

Stylos, N., & Zwiegelaar, J. (2019). Big data as a game-changer: How does it shape business intelligence within a tourism and hospitality industry context?. Big data and innovation in tourism, travel, and hospitality (pp. 163-181). Springer, Singapore.

Tallon, P. P., & Pinsonneault, A. (2011). Competing perspectives on the link between strategic information technology alignment and organizational agility: insights from a mediation model. MIS Quarterly, 463-486.

Yin, J., Wei, S., Chen, X., & Wei, J. (2020). Does it pay to align a firm’s competitive strategy with its industry IT strategic role?. Information & Management, 57(8), 103391.

Zaki, M. (2019). Digital transformation: harnessing digital technologies for the next generation of services. Journal of Services Marketing.

Zhang, J., Long, J., & von Schaewen, A. M. E. (2021). How does digital transformation improve organizational resilience?—Findings from PLS-SEM and fsQCA. Sustainability, 13(20), 11487.

Zhang, X., Gao, C., & Zhang, S. (2022). The niche evolution of cross-boundary innovation for Chinese SMEs in the context of digital transformation——A case study based on dynamic capability. Technology in Society, 101870.

Zhou, K. Z., & Wu, F. (2010). Technological capability, strategic flexibility, and product innovation. Strategic management journal, 31(5), 547-561.

Hire a Writer