The HCL Review Podcast

Beyond Compliance: How Three Mechanisms—Tech Transparency, Shared Governance, and Capability Networks—Reshape Supply Chain Power for Real Sustainability

Learn more about Dr. Jonathan H. Westover's research, "Navigating Power Dynamics in Sustainability Transformation: Extending Integration Mechanisms Across Organizational Boundaries."

The Invisible AI Workforce: Why the Talent Shortage is a Massive Blind Spot and How to Find the 20x Hidden Talent Pool

Learn more about Dr. Jonathan H. Westover's research, "The Invisible AI Workforce: Redefining Technical Talent Acquisition for Artificial Intelligence."

The Great Senior HR Split: Why Banking and Healthcare are Doubling Down While Tech and Media Cut Deep

Learn more about Dr. Westover's research, "The Strategic Recalibration of HR Leadership: Industry Migration Patternsand Organizational Implications."

$168-to-1 ROI_ The Sociological Strategy That Turns Global HR Into Measurable Social Impact

An overview of Jonathan H. Westover's interdisciplinary career.

Algorithmic Management: Leadership in Organizations Where AI Supervises Humans, by Jonathan H. Westover PhD

Abstract: Algorithmic management—the use of automated systems to direct, evaluate, and discipline workers—has expanded from platform-based gig work to traditional employment across multiple sectors. This shift fundamentally alters workplace relationships, introducing automated decision-making processes that can affect trust, autonomy, and wellbeing while offering potential gains in efficiency and consistency. Evidence suggests that algorithmic supervision correlates with complex outcomes including both performance improvements and worker resistance. When implemented with consideration for transparency, fairness, and meaningful human oversight, algorithmic tools may augment rather than replace human judgment. This article examines the organizational leadership challenge of governing workplaces where AI supervises humans, synthesizing verified research on prevalence and consequences, then outlining practical approaches including explainability frameworks, participatory design, human-in-the-loop architectures, and procedural justice mechanisms. Leaders navigating this transition must deliberately design sociotechnical systems that balance operational objectives with worker dignity and voice.

The Hidden Cost of Poor Job Quality: Why Workers Are Struggling and What Organizations Can Do About It, by Jonathan H. Westover PhD

Abstract: The American Job Quality Study reveals a critical workforce gap: 60% of U.S. workers lack quality jobs across five dimensions—financial well-being, workplace safety and respect, growth opportunities, voice in decisions, and schedule control. This nationally representative survey of over 18,000 workers demonstrates that poor job quality correlates with diminished employee satisfaction, reduced retention, and weaker business performance. Organizations face mounting pressure to address systemic deficits in worker agency, with 62% lacking schedule control and 55% reporting limited input on decisions affecting them. This article presents evidence-based interventions spanning transparent communication, procedural justice, capability development, operating model redesign, and comprehensive benefits. Building long-term workforce resilience requires organizations to recalibrate psychological contracts, distribute leadership authority, and embed continuous learning systems that elevate job quality from compliance checkbox to strategic advantage.

Claude Skills and the Organizational Redesign of Work: Simplicity as Strategic Infrastructure, by Jonathan H. Westover PhD

Abstract: Claude Skills, introduced by Anthropic in October 2025, represent a paradigm shift in organizational AI adoption through radical simplification. Unlike previous approaches requiring complex protocols and substantial technical infrastructure, Skills employ a deceptively simple architecture: Markdown files containing task instructions, optional supporting scripts, and minimal metadata. This simplicity enables organizations to rapidly develop and deploy specialized AI capabilities across functions without extensive engineering resources. This article examines how Skills redefine work design by democratizing AI capability development, enabling rapid organizational learning cycles, and potentially flattening traditional skill hierarchies. Drawing on research in organizational learning and technology adoption, we analyze Skills' implications for capability building, knowledge management, and workforce transitions. Organizations that strategically cultivate "skills engineering" as a core competency while addressing governance challenges stand to gain significant competitive advantage in the evolving landscape of human-AI collaboration.

Bridging the AI Implementation Gap in HR: From Hype to Value, by Jonathan H. Westover PhD

Abstract: Despite surging interest in artificial intelligence within human resources, most organizations remain in the early stages of their AI journey, with two-thirds having less than one year of implementation experience. This article synthesizes research and practitioner insights from David Green's comprehensive September 2025 HR analytics review to examine why many HR departments struggle to realize value from their AI investments. The analysis explores the implementation gap between AI ambition and business outcomes, revealing that successful organizations prioritize workflow redesign over technology adoption, take a product-centric approach to implementation, and maintain a focus on human oversight. The article provides a structured framework for HR leaders to move beyond pilot implementations to achieve scalable, value-generating AI applications that augment rather than replace human capabilities.

When AI Investments Fail: Why Work Redesign, Not Technology Deployment, Unlocks ROI, by Jonathan H. Westover PhD

Abstract: Despite widespread adoption of artificial intelligence tools at the individual level, organizational returns remain disappointing. Recent industry research indicates that only a small fraction of companies achieve significant value from AI investments, with satisfaction rates similarly low. This gap between individual experimentation and enterprise-scale value realization stems not from technological limitations but from a fundamental mismatch: organizations layer AI onto legacy processes rather than redesigning work systems to exploit AI's capabilities. This article synthesizes evidence from management consulting, organizational design, and human-computer interaction research to demonstrate that sustainable AI value requires systematic work redesign. Organizations must analyze and reconstruct roles, cultivate hybrid digital-domain expertise, and realign skill requirements to match augmented workflows. Without intentional redesign of work architectures, AI initiatives remain trapped in pilot purgatory, generating demonstrations rather than transformative business outcomes. Evidence-based interventions spanning process deconstruction, capability development, governance structures, and change management offer pathways from tactical adoption to strategic value creation.

Organizational Structure for AI-First Operations: Beyond Traditional Hierarchies, by Jonathan H. Westover PhD

Abstract: Organizations deploying artificial intelligence at scale face a fundamental structural challenge: traditional hierarchies built for human decision-making prove inadequate when algorithms assume core operational roles. This article examines how AI-first operations—where AI systems execute primary workflows rather than merely supporting human tasks—necessitate new organizational forms that blend human oversight with algorithmic autonomy. Drawing on research across technology, financial services, healthcare, and logistics sectors, we identify how leading organizations are reconfiguring decision rights, accountability frameworks, and team structures to accommodate hybrid human-AI operations. The analysis reveals that successful AI-first organizations adopt platform-based structures with distributed authority, create new coordination roles bridging technical and operational domains, and establish governance mechanisms that maintain strategic human control while enabling algorithmic execution. These structural innovations carry significant implications for organizational performance, workforce adaptation, and operational resilience in an increasingly automated economy.