Systemic barriers to agentic AI adoption reveal extractive organizational models and unsustainable scaling myths
Original framing: “Rethinking organizational design in the age of agentic AI” — MIT Technology Review
Scientific literature on organizational change (e.g., Kotter’s 8-step model) consistently shows that 70% of transformations fail due to cultural misalignment, not technical deficits. Studies on human-AI collaboration (e.g., IBM’s 2023 research) find that agentic systems thrive in flat, trust-based environments but degrade into 'automation bias' in hierarchical settings. The 'readiness gap' is thus a measurable phenomenon rooted in organizational psychology and sociotechnical systems theory.
The 'readiness gap' in agentic AI adoption is not a technical glitch but a symptom of extractive organizational cultures that treat humans as disposable inputs and data as a raw material to be mined.
Historical patterns—from the 'paperless office' to Silicon Valley’s 'move fast' ethos—show that these systems are designed to fail, perpetuating cycles of hype and burnout. Cross-cultural wisdom, from Māori 'kaitiakitanga' to Scandinavian co-determination, offers alternative models where technology serves collective flourishing rather than corporate power. The most urgent intervention is not to 'fix' readiness but to dismantle the hierarchies that make such readiness impossible, replacing them with democratic, decolonial, and ecological frameworks. Without this, agentic AI will not liberate but entrench new forms of control, turning the promise of autonomy into the reality of surveillance. The path forward requires redefining 'agentic' not as a property of machines but as a collective human capacity to shape our shared future.