Agentic AI is transforming the enterprise, but governance is lagging behind adoption. As organizations deploy thousands of AI agents across SaaS platforms, RPA workflows, embedded applications, and emerging vibe-coded solutions, a new risk is emerging: AI Agent Sprawl. This article explores why AI governance, agent registries, ownership, security, auditing, and lifecycle management will become essential capabilities for every modern enterprise.
Publication and Dissertations
This article develops the synthetic organism as a disciplined alternative to both speculative AGI and shallow agentic automation. Building from the Abstraction Fallacy, it argues that AI systems should not claim consciousness through scale, complexity, or embodiment. Instead, artificial agency can be designed as a governed, memory-bearing, context-aware, and auditable system bounded by what creators can describe, test, supervise, and govern.
Pre-crime may not arrive as a single dystopian machine. It may emerge through the quiet fusion of lawful systems: facial recognition, ALPR, CCTV analytics, police records, broker data, social media monitoring, digital identity, smart-city infrastructure, and AI summarisation. This article argues that the real danger is convergence, where evidence becomes inference, inference becomes a score, and a score becomes consequence before any person has been accused, charged, or convicted.
Traditional institutions no longer control how expertise is created or shared. In a world shaped by AI, social media, and real-time information flows, new bodies of knowledge are emerging faster than academia and professional accreditation systems can respond. This article introduces Adaptive Knowledge Systems, a framework for building knowledge that is rigorous, socially adaptive, governable, and fit for rapidly changing environments.
Artificial intelligence is reshaping software delivery, and QA is at the center of that shift. This article explores how testing is evolving from manual execution and defect detection into a broader quality intelligence discipline focused on risk, governance, traceability, explainability, and human judgment.
Bernie vs Claude argues that the AI privacy crisis is not just a consumer issue but a democratic one. It proposes a Digital Sovereignty Act backed by enforceable rights, transparency infrastructure, human-in-the-loop governance, and a Digital Governance & Enforcement Suite that turns policy into operational reality.