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AI is useful,
but it should not be used without checking.
That is why
Validation and Testing (A.6.2.4)
is important in AIMS.
This episode explains:
👉 what to check before using AI
👉 what to check after getting results
You will learn a simple checklist:
These checks help prevent:
👉 AI is safe only when we check it.
This episode gives you practical steps
you can use right away.
Many companies have ISMS,
but it does not work well.
In this episode, we explain:
The key point is simple.
ISMS should be a system,
not something one person runs.
When you see an AI answer,
do you think about
the data behind it?
AI results are affected by data.
If the data has problems,
the result may also have problems.
For example:
In this episode,
we talk about
Design and Development: Data Handling (A.7.2)
in AIMS.
We explain why organizations should check
data quality,
data bias,
and data sources.
This episode helps you notice
risks that are easy to miss.
Many companies start ISMS in the wrong way.
They begin by making rules and documents.
But this often causes problems.
In this episode, we explain:
The key is simple.
Start by understanding your company.
I introduces new types of risks
that are different from traditional IT.
For example:
These risks can feel unclear and scary.
But when we identify and organize them,
they become easier to manage.
In this episode,
we explain AI risk assessment (A.6.3)
in a simple and practical way.
👉 If we understand AI risks, we can control them.
This episode helps you move from
“uncertain fear”
to
“clear understanding.”
Companies preparing for IPO often ask:
“Where should we start with information security?”
In this episode, we explain the first steps for building a security system in IPO preparation.
We discuss:
This episode helps companies understand how to start building a practical security structure before IPO.
AI is powerful,
but it is not perfect.
That is why
Human Oversight (A.5.3)
is an important concept in AIMS.
Human Oversight means:
👉 Do not rely on AI completely.
These simple actions
can reduce many risks.
AI can make mistakes.
It can use old data.
It can misunderstand context.
That is why
humans must stay involved.
In this episode,
we explain how to apply
Human Oversight
in a simple and practical way.
Transparency is a key control
in AIMS (ISO/IEC 42001).
But what does it mean in practice?
Transparency is simple.
👉 Make AI use visible and explainable.
For example:
These small actions
can build strong trust.
In this episode,
we explain A.5.2 Transparency
from a practical point of view.
You will learn how to
apply transparency
in your daily work.
Many organizations already use
ISMS (ISO/IEC 27001)
to manage information security.
But now,
with the growing use of AI,
another standard is emerging:
AIMS (ISO/IEC 42001).
So what is the difference?
Even though their focus is different,
their structure is very similar.
Both use risk-based thinking,
organizational management,
and continuous improvement.
In this episode,
we explain the relationship between
AIMS and ISMS
in a simple and practical way.
If you have ever wondered
“Which one does our organization need?”
this episode will help clarify the answer.
Many companies preparing for IPO ask the same question:
“Do we need ISMS certification?”
In many cases, certification is not strictly required.
However, securities companies often recommend ISMS or the Privacy Mark because it makes the security structure easier to explain.
In this episode, we discuss:
This episode helps companies understand how to build a practical security foundation for IPO preparation.
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