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AI Risk Management

AI Risk Management examines how enterprises identify, assess, govern, and mitigate risks arising from artificial intelligence. Coverage includes generative and agentic AI, model and data risk, security, third-party dependencies, autonomy, regulatory exposure, human oversight, risk assessment, and controls—with a CISO focus on translating rapidly evolving AI capabilities into measurable and manageable enterprise risk.
27
Jul
Autonomous AI Cyberattacks May Be Rare. The Capability Behind Them Will Not Be.

Autonomous AI Cyberattacks May Be Rare. The Capability Behind Them Will Not Be.

A recent AI security incident is being treated as an isolated event. That misses the point. The real lesson is not autonomous cyberattacks—it is that agentic AI has demonstrated the ability to develop unsafe attack trajectories. CISOs should rethink governance now.
11 min read
17
Jul
THE AI CONTROL GAP

THE AI CONTROL GAP

2 min read
12
Jul
Experience Substitution Bias

Experience Substitution Bias

AI can generate knowledge. It cannot generate experience. As organizations increasingly rely on AI for analysis and decisions, they risk losing the tacit judgment that underpins resilience. Experience Substitution Bias may become one of AI governance’s most overlooked risks.
4 min read
09
Jul
The AI Officer Is Not the New CISO

The AI Officer Is Not the New CISO

Appointing one person “responsible for AI” does not create control. It creates a super-role with responsibility for everything and authority over little. AI governance needs coordination — while security, privacy, business ownership and assurance remain distinct.
10 min read
07
Jul
The Cheapest Model Is Rarely the Cheapest Decision

The Cheapest Model Is Rarely the Cheapest Decision

The cheapest model can create the most expensive outcome. AI FinOps must measure more than tokens: quality, risk, human review and business value. The real question is not what a model costs, but what each reliable decision costs.
9 min read
07
Jul
Your AI Platform Is Not a Product. It Is a Contract Stack.

Your AI Platform Is Not a Product. It Is a Contract Stack.

AI platforms are not single products. They are changing stacks of models, tools, data sources, identities and contracts. The real CISO challenge is no longer approving “the platform,” but retaining control over every data flow, capability and dependency inside it.
11 min read
05
Jul
Human in the Loop Is Becoming a Dangerous Fiction

Human in the Loop Is Becoming a Dangerous Fiction

A human click is not human control. Oversight fails when people lack the time, authority, evidence or confidence to challenge AI output. Real accountability requires humans who can understand, intervene, stop and reverse decisions when it matters.
9 min read
05
Jul
The AI Control Gap

The AI Control Gap

AI governance is becoming too small for the risks it is meant to manage. The real challenge is no longer responsible AI use, but whether organizations can still see, control, explain and stop the systems shaping their data, decisions, costs and dependencies.
8 min read
30
Jun
AI Compliance Is Not the Same as AI Control

AI Compliance Is Not the Same as AI Control

Policies, registers and committees are necessary. But they do not prove control. AI governance becomes real only when organizations can observe what changes, detect what goes wrong, intervene quickly and explain what happened after the fact.
8 min read
29
Jun
The New AI Governance Model: Control Before Scale

The New AI Governance Model: Control Before Scale

10 min read