Featuring scholarly and practitioner insights from HR and people leaders, industry experts, and researchers.

In this HCI Webinar, I talk with Lauren Tropeano about how companies can tap into the humanity of their people in the era of AI. Lauren Tropeano is the Chief People Officer at Docebo. She brings over 20 years of Human Resources expertise to Docebo, having led diverse, multinational teams for several global, high growth tech organizations. Prior to Docebo, Lauren was the Chief People Officer at Skillshare, a leader in creative learning, from 2022 to 2024. She also held several executive roles leading global People teams at tech companies such as DraftKings from 2018 to 2022, and Cogito, Pivotal Software and Dell/EMC prior. In those leadership roles, she led teams and organizations through several periods of rapid growth and transformation. She is also the founder of Destination People, a boutique human resources consulting firm. Lauren received her MBA from the University of Massachusetts at Amherst and B.A. in Organizational Behavior from Boston College.

Abstract: The personal meaning penalty describes the psychological and performance costs incurred when employees' work misaligns with their core values, sense of purpose, or desired impact. Unlike traditional engagement metrics, this penalty persists even when individuals perform competently and achieve external success. Drawing on self-determination theory, eudaimonic well-being research, and organizational psychology, this article examines how meaning misalignment manifests, its cascading consequences for both individuals and organizations, and evidence-based interventions for addressing it. Analysis reveals that the meaning penalty disproportionately affects mid-career professionals, knowledge workers, and those who prioritized extrinsic rewards over intrinsic alignment. Organizational responses that demonstrate effectiveness include values-alignment processes, job crafting initiatives, purpose-driven communication, and structural accommodations for meaning-making. The article concludes with frameworks for building sustainable meaning infrastructure that benefits both individual flourishing and organizational performance.

This conversation explores the personal meaning penalty, a psychological burden occurring when a professional's core values clash with their daily work responsibilities. This phenomenon often targets high-achievers and mid-career experts who find that external success and high salaries fail to compensate for a lack of intrinsic purpose. Organizations face significant risks from this misalignment, including reduced innovation, cultural cynicism, and the loss of top talent. To mitigate these costs, they suggest implementing job crafting, transparent communication of company impact, and values-alignment during the hiring process. Ultimately, the research emphasizes that human well-being and long-term organizational health depend on synchronizing individual identity with professional contribution. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this podcast episode, Dr. Jonathan H. Westover talks with Lauren Tropeano about how companies can tap into the humanity of their people in the era of AI. Lauren Tropeano is the Chief People Officer at Docebo. She brings over 20 years of Human Resources expertise to Docebo, having led diverse, multinational teams for several global, high growth tech organizations. Prior to Docebo, Lauren was the Chief People Officer at Skillshare, a leader in creative learning, from 2022 to 2024. She also held several executive roles leading global People teams at tech companies such as DraftKings from 2018 to 2022, and Cogito, Pivotal Software and Dell/EMC prior. In those leadership roles, she led teams and organizations through several periods of rapid growth and transformation. She is also the founder of Destination People, a boutique human resources consulting firm. Lauren received her MBA from the University of Massachusetts at Amherst and B.A. in Organizational Behavior from Boston College. Check out all of the podcasts in the HCI Podcast Network (https://www.podbean.com/podcast-network/HCI) !

In this HCI Webinar, I talk with Jevon Wooden integrating empathetic leadership into your strategies. Jevon Wooden is a sought-after speaker, coach, and author specializing in empathetic leadership. A veteran, CEO, and expert in emotional intelligence and DISC, he empowers leaders to build high-performing teams, foster thriving workplace cultures, and achieve sustainable business growth. Jevon's insights have been featured in Forbes, Entrepreneur, Inc. Magazine, and more.

This research explores how artificial intelligence is revolutionizing human resources by identifying managerial performance patterns that were previously hidden by delayed data. By analyzing real-time communication and engagement signals, these advanced analytics reveal that employee retention and burnout are often localized issues tied to specific leaders rather than general company policies. The author argues that this newfound visibility creates a crisis of accountability, forcing organizations to decide between punitive measures or supportive coaching frameworks. To succeed, companies must implement robust data governance and focus on professional development to ensure these insights foster a culture of growth rather than one of surveillance. Ultimately, the source positions AI-driven transparency as a powerful catalyst for improving leadership quality and long-term organizational health.

This video explores the transformative role of AI tools in understanding workplace dynamics and improving management quality. AI now analyzes work data to detect patterns that humans often overlook, such as signs of team stress or early indicators of employee turnover. This capability offers companies a new “mirror” to see problems previously invisible, enabling proactive interventions rather than reactive responses like exit interviews, which arrive too late. The quality of management is pivotal in shaping team morale, productivity, and retention. Good managers act as coaches who nurture individual strengths, foster psychological safety, and create meaningful work environments, whereas poor managers cause disengagement, fear, and attrition. Highlights 🤖 AI tools reveal hidden workplace patterns and predict team stress or turnover early. 🔍 AI acts as a neutral mirror, showing data without judgment to help ask better questions. 👩‍💼 Good managers foster growth, safety, and engagement; bad managers drive attrition. 📊 AI analyzes communication and meeting data to identify signs of low morale or bottlenecks. 🤝 Data should be used for coaching and support, not punishment or blame. 🎯 Tailored, practical training based on AI insights improves managerial skills and team outcomes. 🌱 Using AI for growth builds trust, retains talent, and strengthens company culture. Key Insights 🤖 AI as a workplace diagnostic tool: AI’s ability to analyze vast amounts of anonymized work data provides a unique diagnostic lens for organizations. Unlike traditional reports or exit interviews, which are retrospective and slow, AI offers real-time, predictive insights on team dynamics and stress. This enables companies to intervene early, reducing turnover and improving morale before issues escalate. The shift from reactive to proactive management is a game-changer in employee retention strategies. 🔎 Objectivity and bias reduction in management evaluation: By focusing on factual patterns such as meeting frequency and communication flows, AI reduces human biases and gossip that often cloud assessments of managerial effectiveness. This objectivity leads to fairer evaluations and highlights specific behaviors linked to team health, such as consistent one-on-ones correlating with higher engagement. The depersonalized data allows organizations to address problems constructively without finger-pointing. 👩‍🏫 The central role of managers as culture shapers: Managers are pivotal in connecting individual employees to the broader organization and shaping daily work experiences. The video underscores that good managers act like coaches, identifying unique strengths, fostering psychological safety, and promoting meaningful work. Conversely, poor managers erode motivation and cause talented employees to leave. This insight highlights that investing in managerial quality is critical to organizational success. 🛠️ Data-driven coaching and training as a development model: The recommended approach emphasizes using AI data as a starting point for conversations, not final judgments. Coaching managers with specific feedback about behaviors (e.g., infrequent one-on-ones or poor communication) opens doors to improvement. Further, targeted training—such as inclusive meeting facilitation or effective feedback delivery—provides practical skills development. This process creates a positive feedback loop where AI measures progress, reinforcing continuous learning. ⚖️ Fairness and transparency in AI usage: To gain trust and effectiveness, companies must be transparent about what data is collected and why. Starting with gentle support and escalating interventions only as needed ensures the process is seen as developmental rather than punitive. This fairness protects managers and encourages openness, which is essential for successful adoption of AI-driven insights. 🏗️ Distinguishing structural versus managerial issues: AI can help pinpoint whether challenges arise from management behavior or broader organizational structures. This distinction ensures interventions target the root cause, whether it’s addressing managerial skills or redesigning workflows or communication channels. Such precision avoids misdirected blame and leads to more effective solutions. Like and share if this helped—spread these ideas across your team. #PeopleAnalytics #ManagerialAccountability #EmployeeRetention #AIinHR #LeadershipDevelopment OUTLINE: 00:00:00 - A New Mirror for Management 00:01:06 - The Hidden Costs of Bad Management 00:02:18 - How AI Finds the Cracks 00:03:30 - Three Practical Steps 00:04:57 - Building a Culture of Growth, Not Blame

Abstract: The advent of AI-powered workforce analytics marks a watershed moment in organizational transparency, one that will fundamentally alter the relationship between management effectiveness and corporate accountability. For generations, high employee turnover has been attributed to compensation structures, market conditions, or cultural misalignment—convenient explanations that deflect attention from a more uncomfortable reality. Machine learning algorithms can now detect what HR professionals have long suspected but rarely proven: specific supervisors consistently drive disproportionate attrition, suppressed engagement, and stunted career progression within their teams. This technological capability forces a reckoning. Organizations face a choice between weaponizing these insights through punitive measures or leveraging them to build managerial competence at scale. The latter path requires reimagining performance data as diagnostic rather than judgmental, establishing psychological safety around developmental feedback, and creating systematic pathways for leadership skill acquisition. Companies that navigate this transition successfully will unlock retention improvements that have eluded traditional interventions, while simultaneously cultivating a management culture grounded in continuous learning. Those that mishandle the moment—either by ignoring the data or deploying it without adequate support systems—will trigger defensive organizational dynamics, potential litigation, and an exodus of talent that recognizes dysfunction long before algorithms confirm it.