Cybersecurity Governance on Christa Burger

Give AI a Job Description Before Giving It Access

Wed, 03 Jun 2026 00:00:00 +0000

Before giving AI more access, give it a job description.

What is it responsible for?
What should it ignore?
What does good output look like?
What tools can it use?
When should it escalate?
What should it never decide?

This sounds obvious.

It is apparently not.

People will give AI access to meaningful workflows with less role clarity than they would give an intern named Brayden who starts Monday and says “for sure” too much.

Accountability Should Not Require Archaeology

Mon, 18 May 2026 00:00:00 +0000

If accountability requires archaeology, the system is under-designed.

People should not need to dig through inboxes, Slack threads, meeting notes, and the memory of whoever was least distracted at the time.

That is not a process.

That is a scavenger hunt with legal exposure.

AI should make this better.

Every meaningful AI-assisted workflow should be able to answer:

What did it do?
What inputs did it use?
What changed?
What did it recommend?
What did a human approve?
Where is the evidence?

This is not just a security or compliance concern.

"I Think We Talked About This" Is Not a Control

Fri, 15 May 2026 00:00:00 +0000

The worst time to document a decision is after something goes wrong.

Everyone is calm. Everyone remembers clearly. No one is searching email for “final_final_ACTUAL_USE_THIS_ONE_v7.”

Obviously.

AI can help us stop doing this.

It can capture decisions as they happen:

What was known?
What was decided?
Who decided it?
What changed later?
What evidence existed at the time?

That is incredibly valuable.

But only if we design for it.

Otherwise AI just helps us create more outputs with less traceability.

Human-in-the-Loop AI Is Not Enough

Wed, 29 Apr 2026 00:00:00 +0000

“Human in the loop” has become one of those phrases we say to make everyone feel better.

Like “cross-functional alignment.” Or “quick sync.” Or “this should be straightforward.”

The issue is not whether a human is somewhere in the loop.

The issue is whether the human is in the right place.

Before the AI acts?
After it drafts?
When risk is detected?
When money is involved?
When customer trust is at stake?
When a decision needs authority?

That matters.

What AI Governance Actually Means (And Why Most Organizations Get It Wrong)

Sat, 28 Mar 2026 00:00:00 +0000

When most organizations hear “AI governance,” they think one of two things: a policy document nobody reads, or a legal team saying no to everything.

Neither is governance. Both are avoidance.

Real AI governance is the architecture through which an organization makes decisions about AI — consistently, accountably, and in alignment with its values. It answers three fundamental questions:

Who decides? When an AI system affects employees, customers, or communities — who has authority over that decision? Who can challenge it? Who is accountable when it goes wrong?