In this podcast episode, Dr. Jonathan H. Westover talks with Erin DeVito about Amazon HR cuts signal dangerous trend across Corporate America. Erin DeVito is the General Manager of Impact North America, leading teams that design transformative, people-centric learning experiences. Since joining Impact in 2012, she has helped organizations navigate change, strengthen leadership, and build cultures where people thrive. With more than a decade of experience across operations and senior leadership, Erin brings a deep belief in the power of human connection to everything she does. A mom of five, she’s constantly reminded of the beauty in imperfection, growth, and humour in chaos—and she channels that perspective into creating workplaces where people can bring their whole selves to work and do their best, most meaningful work together. 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 Cyndi Wenninghoff about creating a magnetic culture in your organization. Cyndi Wenninghoff has over 10 years of experience working in human resources in various industries including advertising, insurance, and technology. She currently works as the Director of Employee Success at Quantum Workplace in Omaha where she oversees employee engagement, recruiting, DE&I, onboarding, and retention efforts. Previously she was the Director of Human Resources at SilverStone Group, a HUB International company as well as the Head of Talent at Bailey Lauerman. Outside of work, she is a member of the Human Resources Association of the Midlands (HRAM) and the Society for Human Resource Management (SHRM). Additionally, she serves as the Director-Elect for the HR Nebraska State Council. She is also the Communications and PR Coordinator for RISE Omaha, a motivating speaker series designed to inspire and unite women throughout Omaha, helping to connect women leaders and build the next generation of female business leaders.

The widespread narrative that artificial intelligence (AI) is rapidly replacing human jobs and causing massive layoffs oversimplifies a much more complex reality. While AI is indeed transforming workplaces, it currently functions primarily as a powerful assistant rather than an autonomous replacement for human workers. AI excels at handling routine, repetitive tasks and processing vast amounts of data, but it still requires human guidance, oversight, and creative judgment. Many companies use AI as a justification to accelerate job cuts, but these layoffs are often driven more by financial pressures and market demands for quick profits than by genuine technological breakthroughs. Highlights 🤖 AI currently acts as an assistant, not a full replacement for human workers. 💼 Many layoffs attributed to AI are driven more by financial pressures and market demands than by true technological capability. ⚠️ Rapid layoffs harm companies by overburdening remaining staff and eroding institutional knowledge. 😟 Job losses cause deep personal, economic, and social challenges, especially for older workers and affected communities. ⏳ Shorter workweeks without pay cuts help retain talent, boost productivity, and improve worker well-being. 📈 Successful trials of reduced hours demonstrate that less work can mean better results. 🏛️ Government intervention is crucial to coordinate fair worktime policies and support retraining efforts. Key Insights 🤖 AI as a Powerful Assistant, Not a Replacement: Despite fears, AI currently lacks the autonomy to replace complex human roles. Its strengths lie in automating routine tasks and data processing, but it still requires human intervention for accuracy, judgment, and creativity. This distinction challenges the narrative that AI is the primary cause of mass layoffs, suggesting instead that human oversight remains indispensable. 💸 Financial Incentives Drive Layoffs More Than Technology: Corporate leadership is under intense pressure to deliver short-term financial results, often at the cost of long-term sustainability. Layoffs are a fast and visible lever to cut costs and boost stock prices, with AI cited as a convenient, future-facing rationale. This reveals that economic and market forces, rather than technological capability, are key drivers of workforce reductions. ⚖️ The Costs of Rapid Workforce Reduction: Deep and rapid layoffs create cascading negative effects within companies, including increased workloads for remaining employees who must juggle their own responsibilities alongside managing AI systems. This diminishes productivity and morale, undermining the intended efficiency gains, and can cause lasting damage to company culture and operational stability. 👵 Human Impact of Job Losses: Losing a job affects more than finances; it disrupts workers’ sense of identity and stability, especially for older employees with specialized skills. Retraining and transitioning into new roles are fraught with uncertainty and often impose significant financial and emotional hardships, highlighting the socio-economic challenges beyond the immediate workplace. 🏘️ Community and Economic Ripple Effects: Large-scale layoffs in dominant regional employers depress local economies by increasing competition for fewer jobs and pushing down wages. This erosion of economic stability harms communities, exacerbates inequality, and weakens social cohesion, illustrating that the consequences of layoffs extend far beyond individual workers. ⏰ Shorter Workweeks as a Solution: Reducing work hours without cutting pay allows companies to share AI-driven productivity gains with employees. Trials in Iceland, New Zealand, and Japan show that shorter workweeks maintain or improve productivity while enhancing worker well-being and engagement. This approach balances technological progress with humane labor practices and economic stability. 🏛️ The Essential Role of Government Policy: Market competition discourages individual companies from reducing hours if rivals do not. Coordinated government action—through setting worktime standards, offering incentives, expanding social safety nets, and funding retraining programs—is necessary to make shorter workweeks feasible at scale. Public sector leadership can model success, stabilizing demand and promoting inclusive growth. 🌍 Worktime Policy as Macroeconomic Infrastructure: Thoughtfully designed worktime policies help translate AI’s productivity gains into broad-based prosperity rather than concentrated wealth. If you found this useful, please like and share. #AI #ShorterWorkweek #LaborPolicy #WorkTimeReduction #DrJonathanHWestover #FutureOfWork OUTLINE: 00:00:00 - AI as the Layoff Scapegoat 00:01:06 - Short-Term Gains, Long-Term Pains 00:02:59 - The Human Cost of Hasty Decisions 00:04:56 - Sharing Work, Sharing Wealth 00:06:53 - A Call for Collective Action

This research examines how corporate incentives often lead to premature staff cuts following artificial intelligence adoption, even when the technology is not yet ready to fully replace humans. It argues that these reductions are driven by short-term financial goals rather than genuine efficiency, resulting in operational failures and broader economic instability. To counter these risks, the source proposes policy-led work-time reduction as an essential tool for stabilizing the labor market. By distributing productivity gains through shorter workweeks, societies can preserve employment levels and maintain consumer demand. Ultimately, the analysis suggests that treating reduced working hours as foundational economic infrastructure is necessary to ensure AI benefits everyone fairly.

Abstract: As artificial intelligence adoption accelerates across sectors, organizations face mounting pressure to demonstrate immediate returns on AI investments, often through workforce reductions that outpace actual automation capabilities. This pattern reflects longstanding corporate short-termism rather than genuine technological displacement, yet it foreshadows deeper structural challenges as AI systems mature. Drawing on labor economics, organizational behavior, and technology adoption research, this article examines how managerial incentives drive premature workforce contraction, the macroeconomic risks of AI-led unemployment, and evidence-based policy responses. The analysis argues that gradual, policy-led work-time reduction represents not merely a quality-of-life enhancement but essential economic stabilization infrastructure. Through examination of historical work-time transitions, contemporary pilot programs, and cross-sector implementation strategies, the article demonstrates how coordinated reduction in standard working hours can preserve employment, maintain aggregate demand, and distribute productivity gains equitably. Organizations and policymakers that treat work-time policy as foundational economic planning will better position their economies to harness AI's benefits while mitigating systemic instability.

Many organizations invest heavily in training to improve employee performance, yet persistent errors and struggles under pressure remain common. This recurring issue stems not from a lack of skill, but from a lack of readiness—the fluctuating ability and will to perform effectively at any given moment. Readiness is dynamic, influenced by five interconnected states: cognitive, emotional, motivational, physiological, and interpersonal readiness. Each state plays a critical role in enabling consistent, reliable performance. Highlights 🔑 Many organizations confuse skill gaps with readiness gaps, leading to ineffective training investments. 🧠 Cognitive readiness is crucial for focus and decision-making, and can be enhanced by minimizing interruptions and simplifying workflows. 💖 Emotional readiness influences behavior; managing emotions through mindfulness and creating safe spaces improves collaboration. 🚀 Motivational readiness drives engagement by linking work to purpose and granting autonomy. 🛌 Physiological readiness depends on health, rest, and energy; proper scheduling and breaks are essential for sustained performance. 🤝 Interpersonal readiness, built on trust and psychological safety, prevents hidden risks and fosters openness. 🛠️ Leaders must design systems that nurture all five readiness states to reliably translate skills into performance. Key Insights 🧩 Readiness is a dynamic, multidimensional state essential for performance: Unlike static skills, readiness fluctuates moment-to-moment based on cognitive, emotional, motivational, physiological, and interpersonal factors. Recognizing this dynamic nature helps break the cycle of blaming individuals or training programs for recurring errors. Organizations must monitor and support readiness continuously to maintain high performance under pressure. 🧠 Cognitive readiness can be significantly improved by environmental design: Overload and interruptions reduce mental capacity and increase errors. Leaders can protect cognitive readiness by simplifying processes, using clear checklists, and creating “no interruption” zones. This highlights the critical role of work environment and design in enabling skillful execution rather than relying solely on individual effort. 💡 Emotional management is as important as technical ability: Strong negative emotions impair rational thinking and teamwork, while positive emotions broaden creativity. Teaching emotional regulation techniques such as mindful pauses and reappraisal, combined with blameless debriefings, cultivates a psychologically safe workplace that encourages learning from mistakes rather than fear-driven concealment. 🎯 Motivational readiness hinges on meaningful work and autonomy: When employees connect their tasks to a larger purpose and feel empowered to make choices, their intrinsic motivation and ownership increase. This drives innovation and productivity, especially in knowledge-driven sectors like technology, where creativity is critical. 🛌 Physiological readiness underscores the interplay between body and mind: Physical exhaustion, poor sleep, and extended shifts critically undermine cognitive and emotional readiness. Sustainable scheduling practices, enforced breaks, and discouraging overtime are vital interventions. This insight emphasizes that human performance is holistic and must consider health as a foundation for mental acuity. 🤝 Interpersonal readiness fosters trust and psychological safety, reducing hidden risks: In environments where blame and shame dominate, people hide problems, allowing small issues to escalate into crises. Cultivating a culture where asking questions and admitting mistakes is encouraged ensures transparency and collective problem-solving, which is critical in high-stakes fields like healthcare. 🛠️ Leaders must transition from training purchasers to readiness architects: Investing solely in skills development misses the broader system that enables skills to be reliably applied. By educating teams on the five readiness states, embedding readiness checks in meetings, and modeling openness and self-care, leaders can build resilient organizations that sustain humane and reliable performance over time. If this helped you, please like and share the video. #DBRS #BehavioralReadiness #OrganizationalPerformance #Leadership #TrainingFailFix OUTLINE: 00:00:00 - Why More Skills Aren't the Answer 00:00:26 - From Skills To Readiness (DBRS Overview) 00:01:04 - The Five Readiness States (Cognitive, Emotional, Motivational, Physiological, Interpersonal) 00:01:52 - Physiological + Interpersonal Readiness 00:02:36 - Readiness in Action (Real-World Examples) 00:03:19 - How Leaders Can Implement DBRS Today + Culture of Readiness

This research introduces the Dynamic Behavior Readiness System (DBRS), a framework that explains why employees often fail to perform despite having the necessary skills. It argues that consistent performance is not a fixed trait but a result of five fluctuating states: cognitive capacity, emotional regulation, motivation, physical energy, and interpersonal safety. Rather than relying solely on repetitive training, the authors suggest that organizations must engineer environments that protect these states from depletion. By addressing systemic issues like excessive cognitive load and lack of psychological safety, leaders can ensure that staff are mentally and physically prepared to apply their expertise. Ultimately, the source advocates for a shift from measuring static competencies to managing real-time readiness to achieve sustainable organizational success.

In this podcast episode, Dr. Jonathan H. Westover talks with Cyndi Wenninghoff about creating a magnetic culture in your organization. Cyndi Wenninghoff has over 10 years of experience working in human resources in various industries including advertising, insurance, and technology. She currently works as the Director of Employee Success at Quantum Workplace in Omaha where she oversees employee engagement, recruiting, DE&I, onboarding, and retention efforts. Previously she was the Director of Human Resources at SilverStone Group, a HUB International company as well as the Head of Talent at Bailey Lauerman. Outside of work, she is a member of the Human Resources Association of the Midlands (HRAM) and the Society for Human Resource Management (SHRM). Additionally, she serves as the Director-Elect for the HR Nebraska State Council. She is also the Communications and PR Coordinator for RISE Omaha, a motivating speaker series designed to inspire and unite women throughout Omaha, helping to connect women leaders and build the next generation of female business leaders. Check out all of the podcasts in the HCI Podcast Network (https://www.podbean.com/podcast-network/HCI) !