Your Team Is Already Using AI. But Is It Safe?

AI tools like ChatGPT, GitHub Copilot, and Microsoft Copilot are rapidly becoming part of daily work. Whether for analysis, reporting, communications, or development, they offer clear productivity gains. But here’s the problem: most organisations haven’t yet put clear guardrails in place.

If you’re not actively guiding AI use, your team is likely experimenting anyway, often with free tools, little oversight, and a lot of uncertainty. That’s a risk. It’s time to move from casual use to structured, safe adoption.

Why It Matters

Your team is already using AI. If you haven’t approved tools or provided direction, people will find their own workarounds. That can expose sensitive information, produce inconsistent results, and lead to avoidable mistakes.

More importantly, without clear policies, you can’t support your team to use AI effectively or ensure you’re complying with evolving legal, compliance, and ethical standards.

What Can Go Wrong

When AI use isn’t managed properly, the risks add up:

• Leaking confidential or client data through public platforms
• Employees using unapproved tools without your knowledge
• Relying on inaccurate or biased AI-generated content
• Breaching data protection, FCA guidance, or copyright laws

A Smarter, Safer Starting Point

Instead of banning AI tools, embrace the opportunity on your terms. Start with platforms that offer privacy, control, and support for professional use in financial contexts:

• Microsoft Copilot: Embedded in Excel and Outlook to support financial modelling, reporting, and client communications
• GitHub Copilot: Useful for internal tools or fintech teams writing code
• Notion AI: Helps draft documentation, meeting notes, policies, or investor updates
• Custom GPTs: Private assistants trained on internal knowledge (e.g. investment memos, client FAQs, compliance manuals)
• ChatGPT Team: Ideal for summarising financial articles, generating market briefings, or preparing internal research drafts

These tools support faster, more consistent outputs—so long as they’re used responsibly.

Five Steps to Get Ahead

1. Survey your team: Find out what AI tools are already being used
2. Approve one or two core tools: Start small and standardise
3. Draft a one-page policy: Set clear rules and use cases
4. Train your people: Make sure they understand the risks and best practices
5. Review and update: Technology moves quickly—your policy should too

Support Learning, Not Just Compliance

A good policy doesn’t just say what not to do it helps people use AI well. Focus on building an AI-literate workforce. That means training on prompt writing, reviewing AI output critically, and knowing when human oversight is essential especially in regulated industries like finance.

What Should Your Policy Include?

Keep it simple. Your AI use policy should clearly outline:

• Which tools are approved and how to access them
• What AI can and can’t be used for (e.g. never for final investment decisions)
• A reminder not to enter confidential or client-sensitive data
• That AI is a drafting assistant, not a decision-maker
• Who to contact with questions or compliance concerns

Example line:
“Use only company approved AI tools for work tasks. Do not input confidential or client data into any AI system unless explicitly authorised.”

The Bottom Line

AI isn’t a passing trend it’s becoming foundational to how we all work. The question isn’t whether your team will use it, but how. With a clear, practical policy, you can reduce risk, improve productivity, and give your team the confidence to use AI safely and effectively.