



17 episodes
by David Rice · English
The People Managing People podcast equips forward-thinking leaders to thrive in the AI era—reshaping teams, systems, and strategy without losing what makes work human. Hosted by David Rice, each episode brings real-world insights from innovators, executives, and people leaders on topics like AI in practice, people-first leadership, performance systems, and workplace culture.









Why “human oversight” and governance slogans aren’t enough for AI decision-making; the real risk is missing “context” in socio-technical systems.
10 Nov 2026 · 52m · 19 chapters
Why self-knowledge from personality/talent assessments often doesn’t change behavior, and how “behavioral intelligence” can help managers treat people as individuals—improving fairness, team…
3 Nov 2026 · 39m · 16 chapters
Leaders misunderstand work because they rely on org charts and process docs, while real workflows are the sum of handoffs, workarounds, and informal rerouting (“tribal knowledge”).
28 Oct 2026 · 29m · 9 chapters
How AI changes career value from deep domain specialization toward fewer specialists, more cross-domain generalists, and especially “taste” (judgment about what good looks like).
20 Oct 2026 · 36m · 15 chapters
The episode argues that enterprise AI strategy should start with human-AI collaboration, not automation.
13 Oct 2026 · 40m · 26 chapters
How to prove AI agent ROI when returns are small (often ~1%), and how to deploy agents in production without harming early-career hiring or adoption.
6 Oct 2026 · 25m · 9 chapters
This People Managing People episode argues that many organizations deploy generative AI in ways that reduce employees’ critical thinking and create “cognitive debt.” Dr.
29 Sep 2026 · 25m · 9 chapters
Whether leaders are sacrificing long-term workforce capability for short-term AI efficiency, and what HR leaders must do to prevent “entry-level erosion” and failed AI initiatives.
22 Sep 2026 · 36m · 15 chapters
Motivocity’s “appreciation intelligence” on automating recognition and HR communications without making them feel automated, by reducing admin/reporting friction and enabling proactive, human-led…
17 Sep 2026 · 22m · 12 chapters
The “silence tax”: when employees don’t speak up, organizations lose ideas, problem-solving, and market intelligence, leading to missed innovation and market share.
15 Sep 2026 · 42m · 16 chapters
AI transformation ROI depends less on the technology and more on organizational clarity (purpose, excellence requirements), psychological safety, trust, and a structured culture of experimentation.
8 Sep 2026 · 35m · 15 chapters
How to build a CFO/C-suite business case for employee engagement by reframing disengagement as a measurable “tax,” and by treating culture as the foundation for AI-driven productivity.
1 Sep 2026 · 40m · 25 chapters
HR’s role in AI transformation—whether AI will be used to maximize efficiency by “techno-optimists” or to redesign work around human fulfillment, autonomy, creativity, and meaningful impact.
25 Aug 2026 · 59m · 29 chapters
The episode argues that AI workplace monitoring often shifts from legitimate measurement to intrusive surveillance, because it assumes everything important about work is measurable.
18 Aug 2026 · 50m · 15 chapters
The EU Pay Transparency Directive (PTD) as an operating model overhaul, not a compliance checkbox—requiring equal-pay-focused reporting, job categorization of “equal value,” employee rights,…
11 Aug 2026 · 33m · 12 chapters
Why AI investments aren’t translating into productivity gains, driven by adoption gaps, fragmented systems, and missing in-the-flow context—not by model quality.
4 Aug 2026 · 26m · 9 chapters
How executive “AI-native” differs from merely “AI-enabled,” and how executive credibility (especially for CHROs and talent teams) is shifting from vision/strategy to demonstrated deployments and ROI.
28 Jul 2026 · 30m · 14 chapters