Capella University

DB FPX 9801 Assessment 6 Pre-Implementation Conference Call Presentation Student Name DB-FPX9801 Capella University Professor Name submission Date   Pre-Implementation Conference Call Presentation Slide 01 Hello! I’m the person _______, and I’m here to do a pre-implementation conference call presentation on this subject: adaptive leadership practices to support digital transformation in mid-size technology companies. Slide 02 Introduction Digital transformation is key to the competitiveness and efficiency of operations. A unique set of digital challenges and digital transformation challenges exists for mid-sized tech businesses (Ameen et al., 2022). Some of the common barriers are resistance of employees to change and limited resources (Ramesh & Delen, 2021). Many organizations are not digitized and don’t have up-to-date technological infrastructure (Hojnik & Huđek, 2023). Just a handful view digital transformation as a principal strategy. The application of adaptive leadership can increase innovation and decrease employee resistance (Chughtai et al., 2023). Project leaders discuss the importance of adaptive leadership in any tech company’s success in transforming. Slide 03 Statement of the Problem Problem Statement The overall business challenge is that most organizations cannot manage the complex digital transformational technologies, and as a result, their operations remain less efficient, employees lose engagement, and fail to achieve their strategic goals (Ameen et al., 2022). US technology mid-sized companies often suffer from a lack of competitiveness due to the difficulty of leaders in implementing desired leadership approaches to deal with employee resistance to digital transformation and prevent growth opportunities from falling through the cracks (Skare et al., 2023). Purpose Statement The qualitative inquiry project aims to understand the ideas of the US middle enterprises’ leaders in the field of leadership strategies that can be used to overcome employee resistance to digital transformation technologies. Gap in Practice The disconnect is that little is known about how leaders at US mid-sized technology companies see and engage in leadership strategies to overcome resistance to digital transformation technologies and how this contributes to unsuccessful implementation efforts and the loss of competitive opportunities (Errida & Lotfi, 2021). Slide 04 Slide 05 Theory(s) Supporting Research The theoretical lens used to view the study is that of transformational leadership theory, which looks at how leadership can impact organizational change and innovation. Transformational leadership theory addresses how leadership contributes to change in an organization. Burns (1978) added a new concept of leadership around a shared set of values, motivation, and purpose. Bass built on this work of Burns by introducing observable leadership behaviors (Bass, 1985). Core transformational behaviors include the four 4I dimensions (idealized influence, inspirational motivation, intellectual stimulation, individualized consideration) (Bass & Avolio, 1994). Idealized influence has been defined in terms of leaders as ethical role models and trust (Burns, 1978). Inspirational motivation is about calling forth a common vision and stirring all employees to action (Peláez et al., 2023). The intellectual stimulation promotes innovation and challenges the status quo (Burns, 1978; Schiuma et al., 2024). Doing this involves mentoring and coaching as well as learning/teaching to the individual’s development needs (Trenerry et al., 2021). Adaptive thinking towards technological change is facilitated by transformational leadership (Rahi et al., 2021). The theory is especially applicable in dynamic business environments where digital transformation is essential and provides a competitive edge. The theory advocates digital literacy and readiness to change in mid-sized businesses. Virtual teams and digital innovation were added to the theory. Peláez et al. (2023) agreed with the impacts on success with digital transformation. In the context of technology innovation management, correlations between transformational behaviors and innovation outcomes are found to be strong among modern scholars (Schiuma et al., 2024). Leadership behaviors are a factor in terms of the adoption of digital tools and technologies. Transformational leadership is very appropriate for managers to lead mid-size businesses in transformation. Slide 06 Methodology Research technique is most suitable with a generic qualitative approach, which can reveal the perspectives of leadership in the digital transformation context in regard to adaptive practices. According to Sekar & Bhuvaneswari (2024), it is a type of qualitative study that can be analyzed as the subjective perception of each individual with the study. As the aim of the present study is to reveal the complex, “lived” experiences of the participants related to the context, generic qualitative inquiry has been used as a method appropriate to leadership studies (Fischer & Guzel, 2022). The way is flexible, and it can allow them to analyze all the adaptive leadership practices (Olatunde & Olenik, 2021). This is a result of research aiming/methodology convergence in which the leadership strategies in technological change processes and content have been nuanced. Slide 07 Sample The leadership, by engaging in the digital transformation of the organisations, will be targeted for the study. Some of the respondents are CEOs, CTOs, and digital transformation managers (Campbell et al., 2020). The participants will build on the leadership generalization and understanding amongst the different industries. The respondents will be selected through purposive sampling as they have a first-hand experience in DT. The data collection will include 10 participants to make the data collection process manageable, and simultaneously provide profound in-depth in the behavior of participants. Slide 08 Would you share a little bit about what you do now and how much experience you have in leadership within the tech industry? What is your organisation’s experience with digital transformation over the last few years? What kinds of leadership strategies have you seen work best in overcoming employee resistance to the use of digital transformation technologies? Have you ever experienced a scenario in which you found a way to make an electronic effort work through an employee’s strong resistance? How did you plan to conduct your project? What are some indicators of employee reluctance to new technologies, and what do you do about them? How do you communicate when implementing new digital technologies with your team? What do you do to engage or include employees in decision making about digital transformation efforts? How do you establish trust with workers who aren’t open to technology change? What do you

DB FPX 9801 Assessment 4 Pre-Implementation Conference Call Presentation Student Name DB-FPX9801 Capella University Professor Name submission Date   Pre-Implementation Conference Call Presentation Slide 01 My name is ____ and I’m here today to do a pre-implementation conference call on leadership strategies for implementing machine learning-based fraud detection systems in U.S. financial institutions. Slide 02 Introduction With the increasing automation of transactions and fraudsters constantly bothering with new schemes, financial institutions have made fraud detection one of their top priorities toward both business and cyber security (Joseph & Eaw, 2023). Technological development results have been highly predictive, yet leadership decision making and organizational integration continue to be problematic for organizations in terms of implementation and adoption. The second project is to understand the nature of the interpretation, implementation and operationalization of these ML-based fraud detection systems by the organizational leaders as these are not yet widely in practice. Slide 03 Statement of the Problem Problem Statement The root of the issue is that the financial industry is grappling with an escalating number of challenges from complex fraud schemes that make backscattering money and subject the institutions to regulatory backlash. However for some time there have been also more advanced machine learning technologies for fraud detection, and many companies have yet to achieve effective implementation (Stratton, 2024). The challenge here is that there is the lack of working practices or algorithms to fully incorporate machine learning fraud detection into practices of the financial institution, and in the cases where it was adopted you still find the effectiveness of the systems to have dropped and opportunities missed for proactive fraud mitigation (Bouncken et al., 2025). Purpose Statement The application of the qualitative study is to gain insights into how fraud detection systems with machine learning are implemented in financial institutions. Gap in Practice Most studies on the influence of leadership decision-making and organizational strategies in these systems have only looked at the successful application of high-tech C2 fraud detection technologies (Joseph & Eaw, 2023). Slide 04 Theory(s) Supporting Research Technology acceptance model (TAM) is a framework that is used to elicit how technology will be accepted by understanding cognitive and behavioural perceptions that will be used for decision making processes. TAM assumes that both attitude toward using the technology system (AU) and intentions to use (IU) are functions of perceived usefulness (PU) and perceived ease of use (PEU), and that these two factors also influence actual use (U) of the technology system (Fred Davis, 1989). In the context of financial institutions, perceived usefulness involves leadership beliefs about the attainment of increased accuracy in fraud detection, improved efficiency in operations and increased success in strategic outcomes while perceived ease of use involves the leadership beliefs related to the complexity of implementation and organizational effort (Joseph & Eaw, 2023). The use of the TAM in the management and information systems literature has been well established as it has been a determinant in understanding the adoption of new technologies from organizations, particularly the adoption of new products and services involving artificial intelligence and machine learning (Pajany, 2021). Adoption analysis can be further extended by a complementary theory viewpoints outlined in Unified Theory of Acceptance and Use of Technology (UTAUT) to call attention to performance expectancy, social influence, and facilitating conditions at the organizational level that affect the manager’s decision (Borhani et al., 2021). The adoption of the machine learning-based fraud detection in financial institutions can be explored using the TAM constructs (Masumbuko & Phiri, 2024). Thus, TAM provides the suitable conceptual base to analyze the managerial decision making procedures that result in successful technology adoption in complex monetary contexts. Slide 05 Methodology The study will take a generic qualitative inquiry approach to examine the leadership strategies that are being applied in implementing machine learning–based fraud detection systems in financial institutions in the U.S. It is a qualitative approach as in the research, managerial views, decision-making processes, and organisational experiences, but does not measure any causal procedures and statistical outcomes. A generic qualitative study can be useful to explore participants’ mindsets and perceptions of leadership in real-world settings in complex organisational contexts (Jafri et al., 2024). The main research method will be semi-structured interviews, which will allow flexibility while ensuring that the research objectives are met. To ensure credibility and confirmability methodological rigour will be achieved using reflexive notes, triangulation, and an audit trail. Data collection will be done to achieve data saturation for deep and comprehensive data insights of the themes. Slide 06 Sample Purposive sampling will be used in the study for the participants who have direct knowledge to detect fraud and those who are technology leaders. Purposive sampling enables the qualitative approach, since it identifies which given, so-called, information-rich cases have to offer as information for the study that is congruent with the research focus and questions (Stratton, 2024). Performing qualitative research guidelines that state saturation of the data is usually reached with 9-17 participants, the proposed number of leaders from the U.S. financial institutions is approximately 12. Qualitative approaches are specifically useful in the case of managerial perspectives, decision-making processes, organizational experiences, and where there is a lack of measurement through numbers (Jafri et al., 2024). To be eligible for inclusion, respondents must be bank, credit union, or fintech leaders with first-hand experience in machine learning fraud programs. It will make sure that individuals who are not responsible for leadership or those who have no relevant experience in implementation will be excluded to ensure that data is relevant. To reduce participant attrition, communication, flexible schedules, and transcript review will be provided. Slide 07 Data Collection Before recruitment of the participants, data collection will be done in a structured and ethical manner with a multi-step process with the help of institutional approval. Participants’ credibility and relevance will be ensured through their professional directories, industry associations, and professional networks to identify eligible leaders. Evaluation of methodological rigour and data quality will be ensured through a leadership responsibility screening process, which evaluates experience in