Chatbots' role in fostering self-reflection is now widely recognized, especially in inducing users' behavior change. While the benefits of 24/7 availability, scalability, and consistent responses have been demonstrated in contexts such as healthcare and tutoring to help one form a new habit, their utilization in coaching necessitating deeper introspective dialogue to induce leadership growth remains unexplored. This paper explores the potential of such a chatbot powered by recent Large Language Models (LLMs) in collaboration with professional coaches in the field of executive coaching. Through a design workshop with them and two weeks of user study involving ten coach-client pairs, we explored the feasibility and nuances of integrating chatbots to complement human coaches. Our findings highlight the benefits of chatbots' ubiquity and reasoning capabilities enabled by LLMs while identifying their limitations and design necessities for effective collaboration between human coaches and chatbots. By doing so, this work contributes to the foundation for augmenting one's self-reflective process with prevalent conversational agents through the human-in-the-loop approach.

In the competitive realm of sports, optimal performance necessitates rigorous management of nutrition and physical conditioning. Specifically, in badminton, the agility and precision required make it an ideal candidate for motion analysis through video analytics. This study leverages advanced neural network methodologies to dissect video footage of badminton matches, aiming to extract detailed insights into player kinetics and biomechanics. Through the analysis of stroke mechanics, including hand-hip coordination, leg positioning, and the execution angles of strokes, the research aims to derive predictive models that can suggest improvements in stance, technique, and muscle orientation. These recommendations are designed to mitigate erroneous techniques, reduce the risk of joint fatigue, and enhance overall performance. Utilizing a vast array of data available online, this research correlates players' physical attributes with their in-game movements to identify muscle activation patterns during play. The goal is to offer personalized training and nutrition strategies that align with the specific biomechanical demands of badminton, thereby facilitating targeted performance enhancements.

Automated coaching messages for weight control can save time and costs, but their repetitive, generic nature may limit their effectiveness compared to human coaching. Large language model (LLM) based artificial intelligence (AI) chatbots, like ChatGPT, could offer more personalized and novel messages to address repetition with their data-processing abilities. While LLM AI demonstrates promise to encourage healthier lifestyles, studies have yet to examine the feasibility and acceptability of LLM-based BWL coaching. 87 adults in a weight-loss trial rated ten coaching messages' helpfulness (five human-written, five ChatGPT-generated) using a 5-point Likert scale, providing additional open-ended feedback to justify their ratings. Participants also identified which messages they believed were AI-generated. The evaluation occurred in two phases: messages in Phase 1 were perceived as impersonal and negative, prompting revisions for Phase 2 messages. In Phase 1, AI-generated messages were rated less helpful than human-written ones, with 66 percent receiving a helpfulness rating of 3 or higher. However, in Phase 2, the AI messages matched the human-written ones regarding helpfulness, with 82% scoring three or above. Additionally, 50% were misidentified as human-written, suggesting AI's sophistication in mimicking human-generated content. A thematic analysis of open-ended feedback revealed that participants appreciated AI's empathy and personalized suggestions but found them more formulaic, less authentic, and too data-focused. This study reveals the preliminary feasibility and acceptability of LLM AIs, like ChatGPT, in crafting potentially effective weight control coaching messages. Our findings also underscore areas for future enhancement.

Doctors believe Artificial Intelligence is now saving lives, after a major advancement in breast cancer screenings. A.I. is detecting early signs of the disease, in some cases years before doctors would find the cancer on a traditional scan. Artificial intelligence could hold the key to "the fountain of youth" for America's aging population, as AI-powered fitness equipment stakes a bigger claim in the world of health, according to the CEO of a high-tech gym franchise. When COVID-19 pandemic restrictions kept Americans from public spaces, including gyms, people flocked to innovative ways to stay in shape, including downloading apps such as FitnessAI, which generates personalized workouts using AI, or buying personal expensive AI-powered equipment. The Exercise Coach, which has fitness studios across the country and overseas in Japan, has risen in popularity since 2020 by the tune of 125%, according to the company's CEO Brian Cygan.

Artificial intelligence is gaining ground and offering new possibilities for coaching. Whilst many coaches are not using AI yet its use is gaining traction and it may be wise for coaches to understand how they can use it. Coaching can be an effective practice that many organisations include in employee professional development programmes to increase their self-efficacy and capability. Traditional coaching is a face-to-face, usually dyadic (two person) interaction designed to facilitate the exchange of knowledge between coaches with specific areas of expertise and less experienced employees who need to improve their skills. If you haven't got anything from us (check your junk mail) the email address may not be quite right – please try again.

We've allowed artificial intelligence into our lives almost without even realising it. Alexa (or one of her competitors) will tell us what the weather will be like tomorrow from a barely distinct command. Netflix's algorithms suggest what we might like to watch based on viewing habits. Health apps are crunching data and drawing conclusions about our wellbeing as we go about our business. The CIPD's April 2019 report, People and Machines: From Hype to Reality, found that – despite the technology being in its relative infancy – 32 per cent of UK organisations had already invested in AI and automation, with 22 per cent introducing software to perform cognitive tasks. Many HR departments are already using text-based chatbots of the kind deployed by banks or retailers to handle customer service queries by mimicking natural conversations.

Professional athletes are no strangers to the power of artificial intelligence. Whether it's the computer vision tools that help pitchers perfect their delivery or the machine learning platform that predicts when soccer players are at risk of injury, AI is empowering athletes to achieve previously unthinkable levels of performance. While spectator gaming events are not yet quite as popular as professional football or soccer, the esports industry is expected to generate $1.65 billion in U.S. revenues by 2020. With so much money at stake in one of the fastest-growing parts of the media landscape, it's only natural that elite gamers are looking for an edge wherever they can find one. Increasingly, this means that gamers are turning to state-of-the-art AI technology for in-depth gameplay analysis, granular predictions and personalized recommendations -- just like their pro sports peers.

In 2016, after four years of running a health and fitness app that lets customers track their daily food and workout routines, health-tech startup HealthifyMe found that it was sitting on millions of data points about its users' lifestyle habits. The Bengaluru-based company's customers were using the app to not only log and track their health regimes, but also talk to nutritionists or fitness coaches. This meant that HealthifyMe had data on everything from users' food and workout logs to the questions they asked the nutritionists and the responses they received. So the company, which is backed by IDG Ventures India, Inventus Capital, and Blume Ventures, among others, decided to feed all this information to a machine-learning algorithm and help fitness coaches respond better to app users. That project has now developed into a customer-facing programme where an AI-driven bot talks to over 25,000 of HealthifyMe's paid subscribers, similar to how Google Assistant or Amazon's Alexa operate.

In 2017, Slice, a New York tech company that builds software solutions for independent pizzerias, had a management problem. The company's tech staff is based in Macedonia, where high unemployment rates mean most of their new hires have never held a formal job prior to Slice. "We have a lot of first-time managers who need coaching," said Rick Pereira, chief people officer. Instead of moving to Macedonia himself, Pereira implemented Butterfly.ai, The tools uses anonymous employee survey results and past performance data to rate managers' performance, then offers tips and training content to help them improve.

Some say people are born leaders. Some say they're groomed to be leaders. Now, artificial intelligence is helping to coach managers into leaders, by teaching them soft skills like clear communication, teamwork, and problem solving. According to the Harvard Business Review, most companies wait 10 years to train managers. If you combine this with the fact that a top reason people leave jobs is due to poor managers, it's clear why building positive soft skills within managers is so important.