International Journal of Swarm Intelligence and Evolutionary Computation

Artificial Intelligence (AI) and Future Skills-An Integrative Competency Model

Arno Onnen^* Department of Information Technology, University of Library Studies and Information Technologies, Sofia, Bulgaria
^*Correspondence: Arno Onnen, Department of Information Technology, University of Library Studies and Information Technologies, Sofia, Bulgaria, Email:

Received: 02-Oct-2024, Manuscript No. SIEC-24-27096; Editor assigned: 04-Oct-2024, Pre QC No. SIEC-24-27096 (PQ); Reviewed: 18-Oct-2024, QC No. SIEC-24-27096; Revised: 25-Oct-2024, Manuscript No. SIEC-24-27096 (R); Published: 01-Nov-2024, DOI: 10.35248/2090-4908.24.13.388

Introduction

The ongoing digitalization has significantly changed nearly every aspect of life over the past decades. According to a study by McKinsey, by 2030, around 375 million workers worldwide - approximately 14% of the global workforce may need to change occupations to meet the demands of digitalization [1]. This transformation affects not only how we communicate and process information but also has significant impacts on the working world and society as a whole. In the modern workplace, digital technologies are ubiquitous, transforming traditional business models, work processes and the demands on employees. For instance, a study by acatech found that a large proportion of companies in Germany view digitalization as a key driver for the transformation of their business models. Companies must adapt to a fast-paced, technology-driven environment to remain competitive, while the workforce must acquire new skills and competencies to cope with the challenges of digital transformation [2,3].

The importance of digitalization goes far beyond the mere adoption of new technologies. It demands a significant reconfiguration of workplaces, the creation of new job profiles and the continuous development of qualifications. An OECD study shows that about one-third of jobs in OECD countries could be significantly altered by automation [4]. Knowledge workers face the challenge of continuously expanding their digital competencies to succeed in a rapidly changing environment [2]. In this context, not only technical skills are required but also the ability to navigate a connected, data-driven world, solve complex problems and develop innovative solutions. According to a study by the World Economic Forum, skills such as complex problem-solving, critical thinking, and creativity are essential for the future workforce, as they are difficult to replace through automation [5].

The societal integration of digital technologies presents both opportunities and challenges. While digital innovations lead to greater efficiency and new possibilities, they also raise questions about data protection, security and social justice [6]. Addressing these challenges requires a deep understanding and development of digital competencies at all levels of society.

In this context, the topics of digital competencies, future skills and specific competencies for the application of artificial intelligence are gaining increasing importance. The ability to effectively use digital tools, understand new technologies and integrate them into the working world has become a key competency essential for both individual professional success and the competitiveness of companies and economies [7]. According to a McKinsey study, digital competencies are the most demanded skills in the job market [5,8].

Competency requirements

Digital competencies: Digital competencies refer to the specific skills required to effectively use digital technologies and manage digital transformation processes within organizations. For specialists and executives, digital competencies are particularly important as they not only influence their own working methods but also how teams are led and projects are managed.

The European Commission describes digital competencies as essential for agency in a digitalized world, particularly for executives who must strategically use digital tools and technologies to optimize business processes and develop innovative solutions. Digital competencies encompass a broad range of skills and knowledge necessary to use digital technologies safely, effectively and responsibly. These competencies go beyond merely operating computers or surfing the internet; they involve a deeper understanding of how digital tools work and their application in various contexts.

Digital competencies can be understood as the ability to critically understand, apply and actively shape information and communication technologies to be capable of action in a digitalized society. This definition emphasizes the need not only to use digital technologies passively but also to actively contribute to the design and further development of digital environments. The authors highlight that digital competencies are multidimensional, encompassing various subfields such as technical skills, informational competencies and communicative abilities [3].

A key feature of digital competencies is their dynamic nature. As digital technologies continuously evolve, the corresponding competencies must also be constantly adapted and expanded. This requires individuals to be willing to engage in continuous education and adapt to new technological developments.

Unlike traditional IT competencies, which primarily focus on technical understanding of hardware and software, digital competencies aim to enable people to productively and critically use digital technologies in various areas of life. This includes the application of digital tools in professional contexts as well as the use of digital media for information gathering, communication and participation in society.

Dimensions of digital competencies for specialists and executives

Technological competencies: Technological competencies form the foundation for confidently handling digital tools and technologies in an increasingly digitalized world.

On a basic level, technological competencies refer to the ability to safely and efficiently operate various digital devices such as computers, tablets, smartphones and peripherals, as well as the use of standard software like word processors, spreadsheets and presentation tools. Another basic element is the ability to use the internet, including navigating web browsers, using search engines, sending and receiving emails and participating in social networks.

On an advanced level, technological competencies include the ability to understand and use more complex digital systems. This includes, for example, knowledge of programming, data analysis and network technology. These skills are particularly in demand in professions deeply involved in the technical development and maintenance of digital systems, such as IT specialists, software developers, and data scientists. Advanced technological competencies also involve a deep understanding of network technology and cybersecurity. Cybersecurity is a particularly critical area as the threat of cyberattacks increases. According to the Global Risk Report of the World Economic Forum, cyberattacks and data breach are among the greatest risks for companies worldwide [5].

An important aspect of technological competency development is the ability to adapt to new technologies and developments. In the fast-paced digital world, it is essential to engage in continuous education and learn new technologies. This requires not only the willingness to learn new tools and systems but also the ability to integrate them into existing processes and structures. Technological competency development is a dynamic process that requires lifelong learning and continuous adaptation [7].

Informational competencies: Informational competencies are a central dimension of digital competencies and are essential for the safe and effective handling of the vast amount of information available in the digital world. These competencies concern the ability to search for, evaluate, organize, and use information.

The first stage of informational competencies includes the ability to find relevant and reliable information. This begins with the use of search engines and databases to conduct targeted and efficient research. Thordsen et al., emphasize that this competency includes not only knowing how to correctly formulate a search query but also understanding which sources are reliable and how to effectively combine various information sources [9].

A key aspect of this competency is the understanding of how to use digital information resources such as scientific databases, ebooks and specialized professional portals.

The ability to critically evaluate information is a central element of informational competencies. In the digital world, it is important to verify information for reliability, accuracy and relevance. This requires an awareness of possible biases and misinformation, as well as the ability to consider the context and origin of the information.

Critical evaluation is particularly important in light of the increasing spread of fake news and manipulative content on the internet. This competency includes understanding how algorithms and filter bubbles can influence the information a user sees online and the ability to recognize and circumvent these effects. Another important element is assessing the scientific quality and methodological rigor of studies and reports, especially in areas such as medicine, science and technology [3].

Informational competencies also involve the ability to efficiently organize, manage, prepare and effectively share information. This competency is becoming increasingly important as the volume of digital information that individuals and companies must manage continues to grow [9].

Additionally, this dimension includes considering copyright and licensing conditions when sharing and publishing information. Understanding the legal frameworks, such as copyright, creative commons licenses and data protection regulations, is essential for the legally secure use and dissemination of information.

An important component of informational competencies is awareness of data protection and data security. In an era where personal and professional data are increasingly stored and processed digitally, it is important to understand the risks and dangers associated with using digital information. This requires not only technical knowledge but also an understanding of ethical considerations when handling personal data. Data protection competencies include the ability to control access to sensitive information and protect privacy in both professional and personal contexts [9].

Communicative competencies: Communicative competencies concern the ability to effectively use digital technologies for communication and collaboration. In an increasingly connected world, where much communication takes place via digital channels, these competencies are important for professional and personal success. They encompass not only the technical skills needed to handle various communication platforms but also the social and cultural abilities required to communicate effectively and appropriately in different digital environments. This also includes the responsibility to ensure that all team members are capable of following secure communication practices and are aware of the risks associated with digital communication. Regular training on security in digital communication helps employees build the necessary knowledge [9].

These three dimensions technological, informational and communicative competencies together form the foundation for comprehensive digital competency. They enable individuals not only to use digital technologies but also to handle them critically and responsibly. These skills are essential for success in a digitalized society and workplace.

Future skills

Future Skills refers to a group of abilities and competencies that are becoming increasingly important in a constantly changing, digitalized world. These skills go beyond mere technical or digital competencies and include a broad range of cognitive, social and emotional abilities required to succeed in a complex and dynamic work environment. Future Skills are crucial for the adaptability and innovation capacity of individuals and organizations in a future heavily influenced by technological progress and global changes [5].

The importance of future skills is underscored by the rapid pace of technological change and the accompanying shifts in the working world. While technical skills and digital competencies remain important, the ability to develop comprehensive and future-oriented competencies is becoming increasingly central. These abilities enable individuals and organizations to continuously adapt to new conditions, develop innovative solutions and solve complex problems that arise in a highly interconnected and globalized world.

Studies show that companies investing in the development of future skills are more productive and innovative and can better adapt to market changes [7].

The increasing automation and use of Artificial Intelligence (AI) heighten the need for Future Skills, as many technical tasks can be automated, while the skills that make humans unique such as creativity, ethical thinking and social interaction are difficult to replicate by machines. Therefore, future skills are gaining importance in an increasingly automated work environment because they represent the competencies that machines and algorithms cannot easily replicate [7].

Digital competencies primarily refer to the ability to effectively use digital technologies and address technical challenges. In contrast, Future Skills go far beyond the technical use of digital tools. They encompass a variety of competencies required to succeed in a changing work environment, shaped not only by technology but also by social, economic, cultural and ecological changes. Another key difference between digital competencies and future skills lies in their breadth of application: Digital competencies are often applied in specific fields of work or tasks, whereas future skills are relevant across different professions and industries [7]. Future skills, especially for specialists and executives, include the following competencies.

Strategic thinking and innovation capability

For executives, strategic thinking is a central future skill. Digital transformation forces companies to constantly question and adapt their business models. Executives must be able to identify long-term trends, anticipate technological developments and develop strategic plans that keep the company competitive in an increasingly digitalized world [7,10].

Innovation capability refers to the ability to develop new ideas and successfully implement them in practice. This competency is particularly important at a time when technological changes and global competition force companies to continuously seek new ways to improve their products, services and processes. Innovation capability requires a combination of creativity, willingness to take risks and the ability to think outside the box [2].

Executives play an important role in fostering innovation capability within their teams. They must create an environment that encourages creativity and experimentation while ensuring that new ideas are effectively evaluated and integrated into the company's strategy. Innovation capability must be promoted throughout the organization to establish a culture of continuous improvement and innovation [10,11].

Critical thinking

Critical thinking refers to the ability to objectively analyze information and situations in order to make informed decisions. Critical thinking involves questioning assumptions, identifying connections, and evaluating arguments and evidence. In a world characterized by information overload and complex problems, the ability to critically assess information is becoming increasingly important. The growing complexity of technical systems and the need to make decisions based on data analysis require a high level of analytical competence and critical thinking [2,7].

Agility

The speed of technological change requires specialists and executives to be able to quickly adapt to new circumstances and implement flexible working methods. Agility enables companies to respond swiftly to market changes, integrate new technologies and continuously optimize their processes. For executives, agility means not only being able to react flexibly to changes but also designing the organization to be prepared for the unexpected. This involves supporting an agile corporate culture based on collaboration, rapid feedback cycles and iterative processes [12].

Interdisciplinary collaboration and digital leadership

Digitalization increases the need for interdisciplinary collaboration. Specialists and executives must be able to lead teams composed of experts from various disciplines and integrate their diverse perspectives and skills. This requires a high level of social competence and the ability to develop effective communication and collaboration strategies. For executives, this means not only being experts in their own field but also developing an understanding of other disciplines to successfully lead their teams. They must be capable of steering interdisciplinary projects that often involve complex technical and organizational challenges. It is important to develop a shared vision and synthesize the diverse contributions of team members into a systematic whole.

Digital leadership also includes the ability to manage virtual teams that often operate across geographical boundaries. Executives must be able to effectively use digital communication and collaboration tools to coordinate teamwork and create a productive working environment. This requires building trust and enhancing team motivation. Executives must find new ways to inspire, coach and support their teams while ensuring that performance goals are met. This ability requires a high level of emotional intelligence, communication skills and flexibility [13,14].

Artificial intelligence and competency requirements

Artificial Intelligence (AI) is one of the most defining technologies of the 21^st century and has the potential to transform nearly every area of modern life. It encompasses a range of technologies that enable machines to develop humanlike abilities such as learning, problem-solving, perception and decision-making. AI can be applied in various ways, from automating simple tasks to solving complex problems that require human judgment and creativity. AI is used in many industries and areas, offering a variety of opportunities to optimize processes, reduce costs, and develop new business models, including through automation and optimization of business processes and personalization and recommendation systems.

AI-specific competency requirements

Data science and machine learning: Data science and machine learning form the foundation for numerous AI applications.

Companies must develop a deep understanding of how data is collected, processed and analyzed to gain meaningful insights and integrate them into AI models. According to Teuber et al., the ability to understand and manage data is one of the most important technical competencies in an AI- driven work environment [15].

In addition to the fundamentals of data science and machine learning, professionals must master the specific platforms and tools used to develop and implement AI applications. The ability to effectively use modern AI tools is one of the critical competencies for the successful implementation of AI initiatives in companies [14].

Security and privacy

Along with the increasing use of AI technologies, the need to consider security and privacy aspects also grows. Professionals must ensure that the AI systems they develop and implement are secure and compliant with data protection regulations. Hasenbein emphasizes that cybersecurity competencies and a deep understanding of data protection regulations are among the most important technical requirements in an AI-driven work environment [16].

Integration of AI systems

Another important technical requirement is the ability to seamlessly integrate AI systems into existing business processes. Professionals must be able to design and implement AI applications so that they interact effectively with existing IT systems and processes [14,15].

Adaptability

Adaptive skills refer to the ability to quickly adjust to new technologies, work methods, and organizational changes. In a work environment increasingly shaped by AI and digital technologies, these skills are important. Specialists and executives must be able to continuously learn and adapt to changing demands.

This adaptability is one of the core competencies in a future shaped by AI. The rapid development of AI technologies and their integration into ever-new application areas require employees to be willing and able to continually educate themselves and acquire new skills. This pertains not only to technical aspects but also to adapting to new work processes and structures necessitated by the introduction of AI [5].

Adaptability is closely linked to the concept of lifelong learning. In a world where technological innovations are advancing at an ever-faster pace, it is not enough to maintain skills and knowledge acquired once. Instead, specialists and executives must be ready to continuously evolve and expand their competencies to stay up- to-date with the latest technologies.

According to André et al., promoting a culture of continuous learning, flexibility and adaptability within organizations is important to successfully meet the challenges of digital transformation. Companies should provide programs and resources that enable employees to regularly update their skills and adjust to new requirements [14].

Ethics and responsibility

With the increasing spread of technologies such as artificial intelligence and big data, the importance of ethical considerations and responsibility grows. Technological innovations must align with ethical standards and legal regulations. This includes protecting privacy, avoiding discrimination through algorithms and considering the social and environmental impacts of technological decisions [7].

According to Binns, one of the greatest challenges lies in socalled algorithmic bias. This bias can arise when the data on which AI systems are trained reflects existing societal inequalities or when the algorithms themselves exhibit systematic biases. This can lead to AI-supported decisions appearing discriminatory, particularly in areas such as credit granting, human resources, or criminal justice [17].

Another central ethical issue is the transparency and explainability of AI decisions. Miller argues that the acceptance and trust in AI systems depend on the ability to understand and explain the decisions made by these systems. This is particularly important in sensitive areas such as medicine or finance, where erroneous decisions can have serious consequences [18].

A key aspect of ethical responsibility in dealing with AI is the question of accountability and liability for decisions made by AI systems. According to Goodman et al., there are often uncertainties in the implementation of AI systems about who is responsible for faulty decisions or harmful outcomes the developer of the system, the operator, or the user. These uncertainties can cause legal and ethical problems, especially when AI systems are used in critical areas such as healthcare or criminal justice [19].

The General Data Protection Regulation (GDPR) in the European Union is an example of legislation ensuring the protection of personal data in the digital age. These regulations compel companies to carefully consider how they collect, store and process personal data. The ability to comply with these legal requirements is becoming a important competency for companies using AI technologies.

Floridi suggests that organizations should develop specific ethical guidelines for the use of AI technologies, which establish clear standards and principles for the responsible use of AI. These guidelines should include issues of fairness, transparency, security and data protection [20,21].

Development of an integrated competency model

The described competency requirements for specialists and executives resulting from digital transformation and, in particular, from AI can be summarized in an integrated competency model. This model represents a generalized competency framework in which digital competencies, AIspecific competencies and future skills are integrated.

The model encompasses technological skills as well as overarching competencies such as ethical thinking, strategic planning and interdisciplinary collaboration and it can be extended according to organization-specific or role-specific requirements (Table 1).

Table 1: Integrated competency model.

Discussion

The article highlights the diverse competencies that specialists and executives need to successfully meet the challenges of digital transformation. The focus is on digital competencies, future skills and the specific requirements arising from the use of Artificial Intelligence (AI).

Digital competencies encompass a wide range of skills necessary to use digital technologies effectively and responsibly. These competencies range from technical skills to informational abilities and digital communication and collaboration.

Future skills go beyond purely technical abilities and include social, cognitive and emotional skills that are increasingly important in a digitalized and complex work environment.

As the use of artificial intelligence continues to spread, the requirements for specific competencies in dealing with AI also increase. These include knowledge in data science and machine learning, as well as an understanding of the ethical and legal aspects associated with the use of AI.

The article develops an integrated competency model that combines digital competencies, AI-specific skills and future skills. This generalized model serves as a guide for the qualification of specialists and executives in a dynamic, technology-driven work environment.

Conclusion

The digital transformation, accelerated by technological advancements and the integration of artificial intelligence, has redefined the competencies required for professionals and executives in the modern workplace. The development of digital competencies, future skills and AI-specific abilities is critical to ensuring individuals and organizations can thrive in a rapidly evolving environment. As technology continues to advance, the ability to adapt, engage in lifelong learning and address ethical and legal concerns will become even more essential. The integrated competency model proposed in this article offers a comprehensive framework that combines these various skill sets, providing a roadmap for professionals to navigate the complexities of digitalization. This model not only addresses technical expertise but also emphasizes the importance of critical thinking, ethical responsibility and strategic leadership in a future shaped by continuous technological innovation.

References

1. McKinsey. The Future of Work: How Digital Transformation is Shaping the Labor Market. McKinsey Global Institute. 2018.  
2. Acatech. Industry 4.0 Challenges and Opportunities. Munich, Acatech. 2016.
3. Friedrichsen M, Wersig G. Digital Skills for Managers. Berlin, Springer Vieweg, 2020.
4. OECD. The Future of Work: OECD Employment Outlook 2019. OECD. 2019.
5. World Economic Forum. The Future of Jobs Report 2020. 2020
6. Sass E. Management Skills of the Present and Future. Berlin, Springer Gabler, 2023.

   [Crossref] [Google Scholar]

7. Pechstein S, Schwemmle M. Future Skills Navigator: Analyzing Competency Requirements for the Future Workforce. New York, Routledge, 2023.
8. McKinsey. Data and Analytics: A Blueprint for Success in the Digital Age. McKinsey Global Institute. 2021.
9. Thordsen L, Pechstein S, Friedrichsen M. Digital Skills: Basics and Applications in the Modern Working World. Berlin, Springer Vieweg, 2020.
10. Petry T. Successful Leadership in Times of Digital Transformation. Berlin, Springer Gabler, 2019.
11. Tigre FB, Henriques, PL, Curado C. The Digital Leadership Emerging Construct: A Multi-Method Approach. Manag Rev Q. 2024

    [Crossref] [Google Scholar]

12. Rigby DK, SutherlandJ, Noble A. Agile at scale: How to create a truly flexible organization. Harvard Business Review. 2016;94(5):88-96.
13. Bailey D E, Kurland NB. A review of telework research: findings, new directions and lessons for the study of modern work. J Organ Behav 2002;23(4):383-400.

    [Crossref] [Google Scholar]

14. André N, Binns R, Cath C. The interdisciplinary impact of artificial intelligence in the modern workplace. J Bus Ethics.l 2021;163(2):567-589.
15. Teuber F, André N, Hasenbein C. Artificial intelligence and the future of competence: Developing skills for the digital age. J Artif Intell Res. 2022; 75: 321-337.
16. Hasenbein C. Management Skills of the Present and Future: Challenges and Perspectives. Wiesbaden, Springer Gabler, 2023.
17. Binns R. Algorithmic accountability: A framework for identifying and mitigating discrimination in algorithmic decision-making systems. J Ethics. 2018; 22(1):25-41.
18. Miller T. Explanation in artificial intelligence: Insights from the social sciences. Artificial Intelligence. 2019;267:1-38.
19. Bryce GN, Flaxman S. Ethics in AI: Transparency, fairness and accountability. AI Magazine. 2017;38(4):17-26.
20. Floridi L, Taddeo M. What is data ethics? Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 2018; 374(2133): 20180081.

    [Crossref] [Google Scholar]

21. Cath C, Floridi L, Taddeo M. Ethics and governance of artificial intelligence: The need for a comprehensive approach. Ethics Inf Technol. 2018;20(2):167-180.
22. Buschmeyer J, Gasch F, Hartmann E, Juraschek S. Competence Requirements for Employees in a Digitalized Working World. Competency model for digital media literacy. 2019
23. Yukl G. Leadership in Organizations. Pearson. 2013.
24. Davenport TH, Ronanki R. Artificial intelligence for the real world. Harvard Business Review. 2018;96(1):108-116.

    [Google Scholar]

25. Khaw TY, Teoh AP, Khalid SNA, Letchmunan S. The impact of digital leadership on sustainable performance: A systematic literature review. J Manag Dev. 2022;41(9):514-534.

    [Crossref] [Google Scholar]

26. Woydt S.  Leadership and Strategy Development in the Context of Digitalization. Wiesbaden, Springer Gabler, 2020.

    [Crossref] [Google Scholar]

27. Espina-Romero L, Noroño SJG, Rojas-Cangahuala G, Palacios GJ, Ríos PD, Rio CJ. Digital leadership in an ever-changing world: A bibliometric analysis of trends and challenges. Sustainability. 2023;15(17):13129.

    [Crossref] [Google Scholar]