Impact of Artificial Intelligence in Yoga Personal Training: Need for Enhanced Presence and Scalable Reach for Independent Instructors

Abstract

The scope of this work (DBA) aims to investigate the impact of physiological factors (Melinda B. Abbott, 2018, Melton, Maguire, J. S. 2001) and Artificial Intelligence (AI) on the business potential of freelance yoga instructors (Brown, 2015, Horn Jr.,2005, Ahtinen et al., 2008, Moniz & Slutzky, 2016)). in Bangalore, India. The study utilizes a mixed-methods approach, combining quantitative data from surveys and qualitative data from semi-structured interviews and content analysis. At a high level, the research seeks to address the following questions: ● Do physiological factors limit freelance yoga instructors’ ability to provide personalized yoga instruction? ● Does AI augment or replace traditional yoga instructors, impacting their business opportunities? The study reveals that a significant number of freelance yoga instructors (91%) face negative impacts on their business due to physiological factors, including fatigue, stress, injuries, time constraints, and a perceived need for physical presence. It also finds that while the majority of instructors (77%) perceive AI as a potential threat to their business, 80% also acknowledge its potential to enhance their virtual presence and client relevance. The research highlights the importance of AI in reaching a wider audience through virtual training, offering a solution to the limitations of physical presence. However, it also emphasizes the need to strike a balance between AI's technological capabilities and the human touch that instructors provide. The study concludes that the future of freelance yoga instruction lies in a human-centric AI approach that augments instructor capabilities without replacing them. I first started by analyzing the current context of understanding the scope of business for freelance Yoga instructors and the physiological and AI factors impacting their businesses as part
7 of the literature review that explores in detail the exponentially growing field of AI-powered yoga personal training, examining its potential to enhance market expansion and professional reach for independent instructors. While recent research highlights the potential of AI to automate pose recognition, personalize instruction, and objectively evaluate performance, this review specifically addresses a crucial gap within this field, which is to focus on the potential impact of physiological factors and AI-driven yoga instruction on the businesses of freelance yoga instructors, a segment often overlooked in the broader discussion surrounding AI integration. In Annex 1 , I have collected the metadata that governs the research and analysis covered in the Literature Review of this research, in terms of keywords used for the research, distribution / importance of keywords in the literature, the criteria governing the importance of the keywords, search databases used and the approach. Based on these criteria, I narrowed down to 96 papers as the foundation for literature review. Following this, I grouped the research papers into 5 categories: The rise of hyper-personalization in wellness technologies, Personalized Yoga instruction as complementary and alternative medicine, The potential of AI in transforming Yoga instruction and personal training, Ethical and social implication of AI in Yoga, Landscape of research in Yoga, Meditation and AI. A visual representation of distribution of search keywords is in Annex 2 . I have covered the co-relation of keywords with literature in Annex 3 . To summarize, these researches, I have concentrated on two distinct domains: first, substantiating the significance of practices like Yoga, mindfulness, and meditation for holistic well-being, and second, the integration of Artificial Intelligence (AI) technologies to enhance scalability, automation, user experiences and its business implications. However, a crucial gap remains regarding the potential adverse effects of AI-driven Yoga instruction on the business opportunities for human freelance Yoga instructors. While the goal is not to hinder the use of AI
8 in Yoga, it's imperative to investigate the challenges faced by freelance Yoga instructors and explore a human-centric AI approach. This approach could both mitigate negative impacts (if identified as possible) and amplify opportunities for instructors to expand their presence and reach within the personal Yoga training landscape. I have added the visual summary of literature review in Annex 4 . This research aims to address this gap. From the literature review, 2 broad areas of research problem statements has opened up: RESEARCH QUESTION 1 (RQ1): Part A) Impact of physiological factors on freelance personal Yoga instructors Do freelance Yoga instructors experience a decrease in business opportunities due to their inherent physiological limitations (e.g., time and energy constraints) in providing individualized personal training at a huge scale? Part B) Impact of AI on Yoga personal instruction: B1. Does AI impact (reduce) traditional freelance Yoga instructors’ opportunities with automated self-paced practice instead of augmenting the presence of these Yoga instructors? B2. Can AI advancements augment presence of freelance Yoga instructors for Yoga personal training and scale their market potential? RESEARCH QUESTION 2 (RQ2): Can AI advancements focus on augmenting instructors' capabilities rather than purely replacing them, subsequently enhancing business and physiological well-being for freelance Yoga instructors? Based on the literature review and initial problem statements framed above, I have derived the criteria for which we want to evaluate the hypothesis under research question 1 (RQ 1); it is
9 summarized in Annex 5 . This criteria determines the 9-element ecosystem that would foster our research questions and analysis, this is represented in a tabular format in Annex 6 . Analysis of the row-wise, column-wise and diagonally stacked elements of the ecosystem is done in order to familiarize with the focus areas of the research and to identify the initial research questions. The horizontal, vertical, and diagonal analyses provide distinct perspectives, enabling us to explore the multifaceted relationship between AI advancement and potential to augment the business opportunities for freelance Yoga instructors comprehensively. Image representing this 3-dimensional intersection of the 9-element ecosystem (as an intersection of entities, key areas of research and impact of AI in personal Yoga instruction) is represented in Annex 7 . With this, we have informed context about the elements from which the questions should be addressed and the literature review has given us the background to these questions (that were surfacing in those papers but not necessarily delved deeper in data or analysis), which I have further evolved to study as part of this research. By now we are also equipped with the choice of Research Methodology to conduct the research. The research best aligns with the Post-Postivism (Per Eagleton, 2003: 135) paradigm, following a deductive approach (while ensuring the open ended understanding of the complex nature of the area being studied), is taken for the research starting with a specific hypothesis development based on the literature review, and testing of the hypothesis to check if it holds in particular contexts and the mixed-methods research design to provide a comprehensive understanding of the complex relationships between AI, physiological factors, and the business of freelance yoga instructors. The image representing research methodology and the research components is represented in Annex 8 . The layers of the Research Onion are interconnected and influence each other. The research philosophy (post-positivism) guides the approach (deductive) and strategy (mixed methods), which in turn inform the specific
10 choices regarding data collection and analysis. The core of the onion (KAR) represents the central focus of this research, shaping the entire methodological design. The details of questions for RQ1 (Part A) with their key metrics are in Annex 9 . The key metrics are aligned with the questions as an approximation, to help with processing and analyzing the results. Of course they are more than just data points, some are detailed open ended questions that are much more than metric driven data. The details of questions for RQ1 (Part B) with their key metrics are in Annex 10 . Once the stages, components, research elements, questions (a good combination open ended and data oriented) and key metrics have been organized, the subsequent steps were to conduct the research (research procedure) and analyze results. The research procedure for the 2 enquiries in this thesis can be summarized as follows: This research investigates the impact of physiological factors and AI on the reach and business potential of freelance yoga instructors in Bangalore. The study employs a mixed-methods approach, combining quantitative data from surveys and qualitative data from semi-structured interviews and content analysis. There is a summary of the population, sampling strategy, and research procedures employed to ensure robust and reliable findings in Annex 11 . For organizing and analyzing the findings, I followed the following steps: Analyze the survey data using the statistical tests outlined (correlation). Create tables, charts, and figures to visually represent the findings and highlight significant correlations. Conduct thematic analysis on the interview transcripts and content analysis. Identify key themes, patterns, and recurring ideas that emerge from the data. Identify connections between quantitative and qualitative results and answer: Where do they confirm or challenge each other?
11 The summarized answers to these questions in visualization are available in Annex 12, 13, 14 respectively. To summarize in words, a strong negative correlation is found between physiological strain and business performance stating that if physiological strain increases, business performance decreases. The study also examines the potential of AI to enhance or replace freelance yoga instructors. While a significant majority of instructors (77%) perceive AI as a potential threat to their opportunities, 80% also acknowledge its potential to enhance their virtual presence and client relevance. A weak negative correlation is found between instructors perceiving AI as a threat and believing that AI will enhance their business opportunities stating that there is NO correlation between the instructors perceiving AI as a threat and believing that AI will enhance reach and relevance (business opportunities) for freelance Yoga instructors. While the data suggests that AI may pose a threat to freelance personal yoga instructors, it also highlights its potential for expanding reach and market relevance. Further investigation into the specific applications, the role of human interaction, and the potential evolution of business models will be critical in understanding the true impact of AI on freelance yoga instructors' future. This validates Hypothesis of Research Question 1 Part B 1 and B2. The qualitative analysis provides valuable insights into the physiological challenges and opportunities faced by freelance private yoga instructors in a rapidly changing world. The data in the Venn Diagram depicting the overlap between Physiological Strain and Business Performance Annex 15 , clearly demonstrates that physiological factors play a significant role in their ability to establish and maintain sustainable businesses. The human element of yoga, including personal connection, empathy, and a deep understanding of individual needs, will likely continue to be paramount in ensuring the long-term success of freelance yoga instructors.
12 The qualitative data in Annex 16 addressing the AI impact on business potential of freelance Yoga instructors reveals that freelance yoga instructors in Bangalore view AI as a powerful tool with the potential to augment their presence and business opportunities, particularly in virtual training. However, they also highlight the critical importance of human connection and personalized instruction, suggesting that AI should not replace the role of the instructor. While instructors recognize AI's potential to enhance their virtual presence and business opportunities, they also express concern about AI replacing their opportunities and replacing the human element of their profession. The data suggests that the instructors value the personal connection and personalized instruction they provide. They believe AI should complement, not replace, their role. This analysis points to a key issue in the adoption of AI. While AI can offer efficiency and reach, it must be carefully integrated to avoid replacing the human touch that is often essential for freelance private Yoga instructors’ opportunities and also customer satisfaction. To make sense of the fact that 95% of instructors who see it as a threat also perceive it to enhance business opportunities as observed in the quantitative and qualitative study, I proposed a Problem Statement Analysis that will likely address how instructors perceive the balance between AI and human interaction, providing insights for the future of this industry. The hypothetical statement was aligned to find out if an AI-powered virtual yoga instructor can effectively replicate personalized training, allowing instructors to scale their reach while maintaining client satisfaction? This system would ideally capture an instructor's unique style, preferences, and expertise to deliver customized sessions, even without the instructor being present. The problem statement is detailed in Annex 17 and the response details in Annex 18 .
13 The gist is that Yoga instructors are generally optimistic about the potential of AI to expand their reach and improve client personalization. However, significant concerns remain about the technology's ability to fully replicate the human element of yoga instruction, as well as practical considerations like pricing, quality control, and ethical implications. While many see AI as a valuable tool for business growth, others are cautious about its potential impact on their role and the authenticity of the client experience. Since our Research Question 1 results are validated to be inclined to our initial hypotheses, there is potential future research opportunity for Research Question 2: Exploring a Human-Centric AI Approach to Augment Instructor Capabilities Future research should focus on developing an instructor-augmented, hyper-personalized AI-assisted yoga platform, addressing concerns about AI replacing instructors and exploring strategies for seamless integration of human interaction within the AI-powered platform. The overall research summary is visualized in Annex 19 .