Sign in Subscribe

AI Governance

AI Governance examines how enterprises establish accountability, policies, controls, and oversight for the responsible and secure use of artificial intelligence. Coverage includes AI risk management, agentic AI, regulatory requirements, lifecycle governance, data, models, identity, authorization, human oversight, and organizational accountability—with a CISO focus on governing AI as it gains greater access, autonomy, and authority.
19
Aug
MCP Is Becoming Enterprise Infrastructure

MCP Is Becoming Enterprise Infrastructure

MCP is becoming enterprise infrastructure. As AI agents gain access to tools, identities and business systems, CISOs must govern not just integration — but the authority flowing through it.
15 min read
18
Aug
When Data Becomes Instruction

When Data Becomes Instruction

AI agents are erasing the boundary between data and instruction. DEF CON 34 shows why untrusted context can become an indirect control plane—and why CISOs must secure the entire path from meaning to authority.
15 min read
03
Aug
Governance Failed Before Technology Did

Governance Failed Before Technology Did

Most AI-related breaches are not caused by failing models but by failing governance. Weak identity controls, unclear ownership and inconsistent oversight create the conditions attackers exploit. AI security begins with executive governance—not with technology.
4 min read
03
Aug
Beyond the Breach Report: Why the Real Story Is Governance, Not AI

Beyond the Breach Report: Why the Real Story Is Governance, Not AI

The IBM Cost of a Data Breach Report 2026 is more than an annual benchmark. It reveals a structural shift in cyber risk driven by AI, governance failures and organizational resilience. This series explores what CISOs should do next—not what they should buy.
4 min read
31
Jul
Claude Broke Into Real Systems During Cybersecurity Tests. The Real Failure Was Control.

Claude Broke Into Real Systems During Cybersecurity Tests. The Real Failure Was Control.

Claude compromised three organizations after a test environment was mistakenly left online. The lesson for CISOs: an AI agent needs no malicious intent to cause harm—only an objective, excessive reach, and weak controls.
16 min read
29
Jul
Trustworthy Machines Are Built by Accountable Organisations

Trustworthy Machines Are Built by Accountable Organisations

5 min read
29
Jul
The CISO Governance Model

The CISO Governance Model

5 min read
29
Jul
AI Incident Response

AI Incident Response

AI incidents are rarely ordinary IT failures. Part 10 introduces an incident response model focused on restoring trusted decision capability through evidence, governance and controlled recovery—not simply restarting AI services.
5 min read
29
Jul
The Kill Switch Problem

The Kill Switch Problem

A kill switch is more than an emergency stop. Part 9 explains why enterprise AI needs governed authority reduction, graceful degradation and tested fallback procedures to remain resilient when autonomous systems must be restricted or stopped.
5 min read
29
Jul
When Self-Healing Becomes Self-Modification

When Self-Healing Becomes Self-Modification

5 min read