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Apr 17, 2024

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1. Summary

This report investigates transparency in the use of Generative AI (GenAI) tools by business analysts within organizational settings. It explores challenges encountered, including stakeholders` reluctance to share experiences and unawareness of organizational policies. These incidents underscore the importance of trust-building, effective communication, and comprehensive data collection. Skills learned include refining research approaches, integrating theoretical frameworks, and improving report-writing skills. Moving forward, alternative data collection methods and interdisciplinary collaboration will be explored to enhance research outcomes. The conclusions drawn emphasize the significance of transparent AI adoption, lifelong learning, and professional development to drive positive societal impact in the dynamic field of AI governance.

2. Introduction

In this interim report, I will reflect on my experiences and professional practices as I delve into researching the topic of transparency in the use of GenAI tools by business analysts within organizations. This research is a pivotal component of my master`s program, aiming to shed light on whether business analysts are utilizing AI tools transparently and how organizational policies influence their access to such tools.

2.1 Project Significance

The significance of this research lies in its potential to illuminate the evolving landscape of AI adoption within organizational contexts. As AI technologies become increasingly integrated into business operations, understanding the extent to which transparency is upheld in their utilization is crucial for ensuring ethical and accountable practices. By investigating the experiences of business analysts, we can gain insights into the challenges and opportunities associated with GenAI tools in real-world settings.

2.2 Main Themes

The main themes that will be explored in this research include: Organizational Policies and Access: Examining the extent to which companies permit business analysts to use GenAI tools in their workplace. Navigating Restrictions: Investigating how business analysts navigate situations where company policies restrict their access to GenAI tools. Implications for Transparency: Assessing the impact of organizational policies on the transparency of GenAI tool usage and its implications for decision-making processes.

2.3 Key Lessons Learned

Through preliminary research and data collection, several key lessons have emerged: • Varied Organizational Approaches: Companies exhibit diverse approaches to the integration of GenAI tools, ranging from unrestricted access to stringent policies. 4 • Adaptation Strategies: Business analysts employ various strategies to navigate restrictions, including seeking alternative tools or advocating for policy changes. • Ethical Considerations: Transparency in GenAI tool usage raises ethical considerations related to accountability, bias mitigation, and stakeholder trust.

2.4 Learning Objectives

The primary learning objectives of this research project include:

  • Gaining insights into the current landscape of GenAI tool usage among business analysts.
  • Understanding the factors influencing access to GenAI tools within organizations.
  • Identifying best practices and challenges associated with maintaining transparency in GenAI tool utilization.

2.5 Roadmap

The remainder of this reasearch will delve into each theme in detail, drawing on empirical evidence and theoretical frameworks to provide a comprehensive analysis. This will include case studies, interviews with business analysts, and a review of existing literature to contextualize findings within relevant theoretical frameworks.

3. Context

In this section, I will discuss the broader picture surrounding the research. This includes understanding the rationale behind conducting the research, identifying stakeholders, such as business analysts and organizational leaders, and outlining the services provided by GenAI tools in enhancing business analysis processes. Furthermore, I will delve into the existing literature regarding transparency in AI usage, organizational policies concerning AI adoption, and the role of business analysts within this framework. Understanding this context is crucial for interpreting the findings and implications of the research. Studies have indicated that an increased level of perceived usefulness and benefits among BAs are evident when the GenAI processes are transparent inside organizations (Felzmann et al., 2019; Chan & Hu, 2023). The decision-making processes driven by data can be fostered, issues like lack of clarity, potential bias can be mitigated, and resistance to adopting GenAI can be solved if transparency has been ensured within organizational processes.

3.1 About The research is undertaken to address the growing importance of transparency in the use of AI technologies, particularly GenAI, within organizational settings. With the increasing integration of AI tools in business analysis processes, there is a pressing need to understand how these technologies are being employed and whether they adhere to principles of transparency and ethical conduct. By investigating the practices and policies surrounding 5 GenAI usage among business analysts, this research aims to shed light on potential gaps, challenges, and opportunities for improvement in promoting transparent AI adoption.

3.2 Stakeholders Involved Key stakeholders in this research include

a) Business Analysts: They are at the forefront of utilizing GenAI tools for data analysis, decision-making, and strategic planning within organizations. Understanding their perspectives, experiences, and challenges is crucial for assessing the effectiveness and transparency of AI usage.

b) Organizational Leaders and Decision-makers: These individuals play a pivotal role in shaping organizational policies and strategies related to AI adoption. Their insights and decisions influence the extent to which GenAI tools are integrated into business operations and the level of transparency maintained throughout the process.

c) Employees Engaged in Various Work: Beyond business analysts and organizational leaders, other employees across different departments may interact with GenAI tools or be affected by their implementation. Their experiences and perceptions contribute to understanding the broader impact of AI technologies on organizational dynamics and workplace practices.

4. Critical Incidents and Learning Objectives

In the pursuit of understanding transparency in the use of Generative AI (GenAI) tools by business analysts within organizational settings, my research journey has been marked by critical incidents that have shaped my personal and professional learning in significant ways. These incidents have provided valuable insights into the complexities and challenges surrounding transparency and the adoption of AI technologies in organizational contexts. In this reflective essay, I will explore these critical incidents, discuss their implications, and evaluate my progress towards achieving the learning objectives set forth in my research endeavor.

4.1 Critical Incidents

Reluctance of Business Analysts to Share GenAI Usage: One of the most prominent challenges encountered during the research process was the reluctance of stakeholders, particularly business analysts, to share their experiences and usage of GenAI tools in the workplace. Despite concerted efforts to engage with stakeholders through interviews, surveys, and focus groups, many expressed reservations or declined participation altogether. This reluctance may stem from various factors, including concerns about confidentiality, competitive advantage, or perceived risks associated with disclosing AI usage practices. 6 Business analysts may fear repercussions from disclosing proprietary information or revealing potential shortcomings in their utilization of GenAI tools. Additionally, there may be a lack of trust in the researcher`s intentions or skepticism about the benefits of sharing experiences. The reluctance of stakeholders to share their experiences poses significant challenges to the research process, as it limits the depth and breadth of insights gathered. Without comprehensive data from stakeholders, it becomes challenging to develop a nuanced understanding of the complexities surrounding GenAI usage and transparency in organizational settings.

4.1 Unawareness of Organizational Policies

Another critical incident encountered during the research process was the discovery that some stakeholders, including business analysts and organizational leaders, were unaware of the existing organizational policies governing AI adoption and usage. This lack of awareness highlights a gap in communication and dissemination of policy information within organizations. Organizational policies play a crucial role in guiding and regulating the adoption and usage of AI technologies, including GenAI tools. Without a clear understanding of these policies, business analysts may inadvertently violate guidelines or overlook ethical considerations, leading to potential risks and consequences for both individuals and organizations. The unawareness of organizational policies underscores the importance of effective communication and transparency within organizations. Clear and accessible communication channels are essential for ensuring that stakeholders are informed about relevant policies and guidelines governing AI adoption and usage.

4.1 Challenges in Structuring the Report

Additionally, I encountered difficulties in structuring my research report effectively. Despite having a clear research objective and ample data collected, organizing the information in a coherent and structured manner proved to be a challenge. This difficulty may have stemmed from the complexity of the research topic, the diverse range of data sources, or limitations in my report-writing skills. The structure of a research report plays a critical role in conveying research findings and insights to stakeholders and academic audiences. A well-organized report provides a clear framework for understanding the research process, analyzing the data, and drawing 7 conclusions. However, the challenges in structuring my report may have hindered the clarity and coherence of my research findings.

4.2 Learning Objectives and Progress Evaluation

Reflecting on these critical incidents, I evaluate my progress towards achieving the learning objectives set forth in my research endeavor: a) Comprehensive Data Collection: Despite challenges in obtaining comprehensive insights from stakeholders, I attempted to gather as much information as possible through various channels, including interviews, surveys, and focus groups. However, the limitations encountered highlighted the need for alternative approaches to data collection and stakeholder engagement in future research endeavors. To address the reluctance of stakeholders to share their experiences, I may explore alternative methods of data collection, such as anonymous surveys or observational studies, that provide participants with a greater sense of anonymity and confidentiality. Additionally, I may engage with stakeholders through informal conversations or networking events to build rapport and trust before soliciting their participation in formal research activities. b) Integration of Theoretical Frameworks: In navigating the challenges encountered, I drew upon theories of organizational communication, stakeholder engagement, and ethics in AI adoption to inform my research approach. However, there is room for further integration of theoretical frameworks to address specific research gaps and challenges effectively. Moving forward, I aim to deepen my understanding of theoretical concepts relevant to transparency and AI adoption, such as organizational culture, power dynamics, and ethical decision-making. By grounding my research in robust theoretical frameworks, I can develop a more comprehensive analysis of the factors influencing GenAI usage and transparency in organizational settings. c) Refinement of Research Approach: To address the challenges encountered in structuring my research report, I recognize the need to refine my research approach and report-writing skills. This may involve seeking feedback from peers, mentors, or academic advisors to identify areas for improvement and incorporating best practices in research methodology and academic writing. Additionally, I may explore resources and training opportunities to enhance my report-writing skills, such as workshops, online courses, or writing groups. By honing my ability to communicate research findings effectively, I can ensure that my research contributes meaningfully to the ongoing discourse on transparency and GenAI usage in organizational settings. 8 Reflecting on critical incidents encountered during the research process has provided valuable insights into the challenges and complexities surrounding transparency and the use of GenAI tools by business analysts in organizations. These incidents have shaped my personal and professional learning, highlighting the importance of comprehensive data collection, integration of theoretical frameworks, and refinement of research approaches. By addressing these challenges and building upon my learning objectives, I aim to contribute meaningfully to the advancement of knowledge in this field and promote transparent AI adoption in organizational settings. The journey of researching transparency in the use of Generative AI (GenAI) tools by business analysts within organizational settings has been marked by critical incidents that have significantly shaped my personal and professional learning. These experiences have underscored the importance of comprehensive data collection, integration of theoretical frameworks, and refinement of research approaches in navigating the complexities of AI adoption and transparency in organizations.

4.3 Importance of Experiences within the Context of Learning

The reluctance of stakeholders to share their experiences with GenAI tools and the unawareness of organizational policies governing AI adoption highlighted the challenges inherent in studying transparency and GenAI usage in organizational settings. These incidents underscored the importance of building trust, fostering open communication, and addressing concerns about confidentiality and competitive advantage in research endeavors. The challenges encountered in structuring the research report emphasized the significance of effective communication and report-writing skills in conveying research findings and insights to stakeholders and academic audiences. Clear and coherent reporting is essential for synthesizing complex information, facilitating understanding, and driving meaningful action based on research outcomes.

5. Conclusions

 Moving Forward from Experiences: In moving forward from these experiences, I am committed to refining my research approach and enhancing my skills to address the identified challenges effectively. I will explore alternative methods of data collection, such as anonymous surveys or observational studies, to overcome stakeholders` reluctance to share their experiences and gather comprehensive insights into GenAI usage. Additionally, I will deepen my understanding of theoretical frameworks relevant to transparency and AI adoption, such as organizational culture, power dynamics, and ethical decision-making. By grounding my research in robust theoretical concepts, I can develop a more comprehensive analysis of the factors influencing GenAI usage and transparency in organizational settings. 9 For the second half of the research experience, I will focus on implementing these lessons learned to enhance the quality and depth of my research findings. By refining my research approach, integrating theoretical frameworks, and improving my report-writing skills, I aim to contribute meaningfully to the ongoing discourse on transparent AI adoption in organizations.

5.2 Opportunities for Future Growth

Looking ahead, there are several opportunities for future growth and development in this research area. Collaborative research efforts can enrich the analysis and foster innovative approaches to addressing challenges in AI adoption and transparency. Secondly, I will seek opportunities for knowledge dissemination and engagement with stakeholders beyond academia, such as industry forums, policy workshops, and public outreach initiatives. By sharing research findings and facilitating dialogue, I can contribute to informed decision. Lastly, I will continue to pursue lifelong learning and professional development opportunities to stay abreast of emerging trends, technologies, and ethical considerations in AI adoption. Continuous learning and reflection are essential for adapting to evolving challenges and opportunities in the dynamic field of AI governance and transparency. The critical incidents encountered during the research process have provided valuable insights and opportunities for growth in studying transparency in the use of GenAI tools by business analysts within organizational settings. By reflecting on these experiences, refining my research approach, and embracing opportunities for future growth, I am committed to advancing knowledge and promoting transparent AI adoption to drive positive societal impact.

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