AI has become one of the most common topics in technology conversations. Some organizations are already using it extensively, while others worry they're falling behind.
My advice is simple: don't start with the AI tool. Start with the problem you're trying to solve.
AI can be incredibly useful for improving productivity, organizing information, and helping employees work more efficiently. It can also introduce security, compliance, and data protection concerns if it's used without the right guardrails.
1. Define What You Want AI to Do
Before opening ChatGPT, Copilot, Gemini, Claude, or any other AI platform, ask yourself:
What problem am I trying to solve?
Good Uses for AI
- Drafting emails
- Summarizing meeting notes
- Creating first drafts of content
- Brainstorming ideas
- Organizing information
- Researching a topic
- Explaining complex concepts in simpler terms
Poor Uses for AI
- Making legal decisions
- Replacing compliance reviews
- Sharing sensitive information without approval
- Making business-critical decisions without human oversight
If you can't clearly explain the problem you're solving, you may not need AI at all.
2. Understand Shadow AI
Shadow AI refers to the use of AI tools that have not been approved by your organization's IT or security team.
Most employees aren't trying to create risk. They're simply trying to work faster. The challenge is that organizations often have little visibility into which AI tools are being used or what information is being entered into them.
Examples include:
- Personal ChatGPT accounts used for work
- Uploading company files into public AI tools
- Unapproved AI plug-ins or extensions
- Department-specific AI tools that haven't been reviewed
As AI adoption continues to increase, visibility and governance become just as important as the technology itself.
3. AI Dos
Do Use Approved AI Tools
If your organization has approved AI platforms, start there.
Different AI tools have different security models, privacy practices, and data handling policies. Just because two products appear similar does not mean they provide the same protections.
Why Many Organizations Choose Microsoft Copilot
For organizations already invested in Microsoft 365, Copilot is often a natural place to start.
Copilot works within existing Microsoft 365 permissions and respects the same access controls users already have. Security controls such as data classification, encryption, and data loss prevention policies can continue to play a role in protecting information.
That doesn't eliminate risk. Organizations still need governance, policies, and user training. AI should be treated like any other business technology: useful, but requiring oversight.
Do Start With Low-Risk Tasks
Great beginner projects include:
- Rewriting emails
- Creating meeting agendas
- Summarizing notes
- Brainstorming ideas
- Organizing information
Do Verify Results
AI can be helpful, but it can also be wrong.
Always:
- Fact-check responses
- Review important recommendations
- Confirm statistics and numbers
- Validate information before acting on it
Do Understand Your Data
Know the difference between:
- Public information
- Internal information
- Confidential information
- Regulated information
If you're unsure whether a piece of information should be entered into an AI system, stop and ask. The few minutes spent getting clarification are worth avoiding a security incident.
4. AI Don'ts
Don't Paste Sensitive Information into Public AI Tools
Examples include:
- Customer data
- Patient information
- HR records
- Financial information
- Contracts
- Proprietary business information
Always follow your organization's policies regarding approved AI use and data handling.
Don't Assume Deleting a Chat Solves the Problem
One of the most common misconceptions is:
"It's okay. I deleted the conversation afterward."
Deleting a conversation does not change the fact that the information was entered into the system in the first place.
The better approach is making sure sensitive information was approved for use in that platform before it's ever entered.
Don't Trust the First Answer
AI generates responses using a combination of its training, the information you provide, and, depending on the platform, information from connected systems or the internet.
That means:
- Context can be misunderstood
- Information can be incomplete
- Recommendations can be inaccurate
- Responses can be outdated
Treat AI like a helpful assistant, not a final authority.
Don't Let Convenience Override Security
The fastest solution is not always the safest one.
Saving five minutes today isn't worth creating a compliance issue, exposing sensitive information, or introducing unnecessary risk to the organization.
5. The Risks of Vibe Coding
Vibe coding is the practice of creating software primarily through AI-generated code.
A user describes what they want:
"Build me an employee time-off tracking system with approvals and reporting."
AI generates much of the code. While that can dramatically speed up development, it can also introduce risks if nobody reviews what was created.
Common risks include:
|
Risk |
Example |
Key Takeaway |
|
Working code that isn't secure |
An AI-built application functions correctly but lacks proper access controls. |
If it's not secure, it's not ready for production. |
|
Exposed credentials |
Passwords, API keys, or sensitive information are embedded in the code. |
Never assume AI follows security best practices. |
|
Applications nobody can support |
The creator doesn't understand how the system works. |
If nobody can maintain it, it becomes a business risk. |
Our Advice on Vibe Coding
Before relying on an AI-generated application, ask:
- Do I understand how this works?
- Could I troubleshoot it tomorrow if it broke?
- Has someone reviewed it for security concerns?
- Has someone verified it isn't exposing sensitive data?
- Would I trust it with company information?
If the answer to any of those questions is no, the project needs more review before it's ready for business use.
Building a Responsible AI Culture
Successful AI adoption doesn't come from choosing the right chatbot.
It comes from:
- Employee education
- Clear policies
- Security controls
- Leadership involvement
Encourage Safe Innovation
Organizations should encourage employees to explore practical AI use cases. In many cases, the biggest risk isn't AI itself. It's employees adopting tools without guidance.
A practical approach includes:
- Training employees on appropriate use
- Defining acceptable and unacceptable use cases
- Providing approved AI tools
- Reviewing risks without creating unnecessary barriers
AI isn't going away. The organizations that will benefit most are the ones that balance innovation with responsible governance.
Start with the business problem, understand the data involved, put reasonable guardrails in place, and expand from there.
