"It's convenient," so staff enter customer data or trade secrets into external AI on their personal accounts — this is called "Shadow AI", a classic route to data leaks. On the other hand, banning AI outright leaves you behind competitors. This article, by an ISMS-certified Chiba AI firm, explains the risks of Shadow AI and how to use AI "safely, company-wide" on a private AI environment.
- "Shadow AI" is the state where staff use AI services the company hasn't approved or managed, on their own judgment — a classic route to data leaks.
- Rather than an outright ban, the realistic and effective approach is to build use rules and a private in-house AI environment together.
- The basics are four things: (1) use rules, (2) a corporate or in-house AI environment where input isn't used for external training, (3) access control and log management, and (4) training — and ISMS (ISO/IEC 27001) thinking can be applied on a risk basis.
- Building a secure AI environment can qualify for the Digitalization/AI Adoption Subsidy's security-focused category, among others (eligibility and screening vary by requirements).
What is Shadow AI, and why does it happen?
Shadow AI is the state where staff use AI services the company hasn't approved or managed, on their own judgment. With ChatGPT and others now easy to use, it spreads quietly because "there are no rules" and "it's convenient and boosts efficiency."
Even without ill intent, entered information may flow outside or be used for training, risking leaks of customer or confidential data.
3 risks of leaving it unmanaged
| ① Data leakage | Risk of leaking customer PII, quotes, drawings or source code by entering them into external AI. |
|---|---|
| ② Compliance breach | Violating PII rules, NDAs or internal policies — eroding client trust. |
| ③ Uncontrolled use | No visibility into who uses what and how — neither quality nor safety is managed. |
4 measures for safe company-wide use
| ① Set use rules | Clarify forbidden inputs (PII, secrets) and define allowed scope and a review flow. |
|---|---|
| ② Private AI environment | Use a corporate plan where input isn't used for external training, or a closed in-house AI environment. |
| ③ Access control & logs | Manage users and permissions, keep usage logs, and handle leaver permissions. |
| ④ Education & embedding | Share why it's risky and how to use it via training, embedding safe use across the company. |
"Protect while you use" with ISMS know-how
MRI Inc. holds the international information-security standard ISMS certification (ISO/IEC 27001). Using a third-party-certified information-management framework, we help build an in-house environment where you can use AI safely while protecting confidential data. See Secure AI Environment and Why choose us.
How to start without failing
| STEP 1 | Understand reality — find out who uses what AI inside the company |
|---|---|
| STEP 2 | Set rules — define forbidden inputs, allowed scope and a review flow, minimally |
| STEP 3 | Provide a safe environment — adopt a corporate/private AI environment |
| STEP 4 | Educate & operate — embed via training and improve while watching logs |
For the big picture, see SME AI adoption — where to start? 5 steps.
Worried about cost? There are subsidies
Building a secure AI environment can qualify for national digitalization/AI-adoption grants (incl. security-focused categories; subject to eligibility and screening, not guaranteed). See 2026 subsidies for SMEs in Chiba adopting AI.
Frequently asked questions (secure AI use inside the company)
What is Shadow AI and how should we counter it?
It refers to staff using AI services the company hasn't approved or managed, on their own judgment. It spreads without anyone noticing and can lead to leaks of confidential information. Rather than an outright ban, it's more realistic and effective to combine clear use rules with a private in-house AI environment.
What's needed to make in-house AI secure (build a secure AI environment)?
The basics are four things: (1) use rules defining forbidden inputs and scope of use, (2) a corporate or in-house AI environment where input data isn't used for external training, (3) access control that manages users/permissions and keeps logs, and (4) embedding this via training. Rules and environment work best set up together.
How can we use ChatGPT safely inside the company?
Clarify whether personal, confidential or customer data may be entered, and use a corporate plan where input isn't used for training, or a closed in-house environment. See our guide on how SMEs should use ChatGPT for concrete rule examples.
How does ISMS thinking apply to AI use rules?
ISMS (ISO/IEC 27001) is a framework that assesses risk to information assets and controls it through rules, structure and records. For AI use too, defining "what may be entered," "who uses it and how," and "how logs are kept" on a risk basis lets you use AI safely. We support this build-out with an ISMS-certified framework.
What exactly is involved in AI access control and log management?
This includes setting permissions per user, managing which departments use AI for what purpose, recording and reviewing usage logs, and cleaning up permissions when staff leave. Visualizing who uses what prevents uncontrolled, person-dependent use.
Can subsidies be used to build a secure AI environment?
It can qualify for the national Digitalization/AI Adoption Subsidy's security-focused category, among others (eligibility and screening vary by requirements). See our 2026 subsidy guide for SMEs in Chiba adopting AI for details.
How should you organize AI use?
Related:
・How SMEs Should Use ChatGPT｜Safe internal rules & where it helps
・SME AI adoption — where to start? 5 steps
・Generative AI for Construction & Professional Services｜Speed up reports & proposals
・2026 subsidies for SMEs in Chiba adopting AI
* This article reflects general information as of June 2026. Check each AI service's latest terms for data handling. Check official sites for subsidy requirements and deadlines.