An employee wants to summarise a document, improve a proposal or make sense of a spreadsheet. An AI tool offers a quick way forward. But before that information is uploaded, can your business answer a simple question: is this tool approved for this data and this task?
AI can support useful everyday work, from developing ideas to preparing first drafts. Yet convenience alone is not a basis for deciding where confidential information should go. Without clear guidance, employees may make their own decisions about tools, accounts and data sharing—leaving the organisation with limited visibility of how AI is being used.
The objective is not to choose between innovation and control. It is to make responsible AI use practical. That means giving people an approved way to benefit from AI, supported by clear rules, appropriate security and accountability.
The risk starts with how AI is used
Drafting a generic meeting agenda is different from uploading a client agreement, financial forecast or employee record. The potential value may be clear in each case, but the information involved, the consequences of an error and the controls required are not the same.This is why AI governance should consider the task, the data, the tool and the people affected together. A familiar brand name or a paid subscription should not replace an assessment of the specific service, account type, settings and contractual protections.
Unapproved AI use can create a blind spot
When staff use AI tools outside the organisation’s approval process—sometimes called “shadow AI”—the business may not know which information has been shared, which terms apply or whether access can be managed centrally. Personal accounts and unreviewed browser extensions can add further uncertainty.The answer is not simply to issue a warning and assume the problem is resolved. Employees need to know which tools they can use, what they can use them for and how to request approval when an existing option does not meet a genuine business need.
Five foundations for responsible AI adoption
1. Understand where AI is already being used. Start with a practical inventory of tools, business purposes, account types and information involved. Invite teams to explain the problems they are trying to solve. This helps identify useful opportunities as well as gaps that need attention.2. Approve tools for specific uses—not for everything. Review how a service handles inputs and outputs, including retention, any use for model training, access controls, connected services and relevant contractual terms. Approval should make clear which tasks and data categories are permitted. A tool suitable for public marketing content may not be suitable for confidential client records.
3. Set clear boundaries for business data. Define how public, internal, confidential and personal information may be used. Share only what an approved task requires, and do not assume removing a name makes a document anonymous. Where personal data is involved, bring the relevant privacy expertise into the assessment rather than treating tool approval as proof of compliance.
4. Keep people accountable for the result. AI-generated content can be inaccurate, incomplete or misleading, even when it reads confidently. Define who checks facts, figures, references and suitability before an output is relied on or shared. The level of review should reflect the potential impact of an error; generating a draft does not transfer responsibility to the tool.
5. Make governance an ongoing activity. Assign ownership for approvals, staff guidance, incidents and periodic review. Reassess arrangements when tools, features or business uses change. If an AI assistant can access company files or take actions, review its permissions and approval requirements—not just the information employees type into it.
Your AI policy needs to work in everyday situations
A policy that says “use AI responsibly” leaves too much open to interpretation. Useful guidance should help employees decide what to do at the point of use: Can I upload this document? Can I connect this tool to my mailbox? Who must review the answer? What should I do if confidential information is shared by mistake?For example, an employee preparing a proposal could use an approved tool to develop an outline from a generic brief. Adding client pricing, contract terms or personal details should trigger a different check against the organisation’s data rules and the tool’s approved scope. The distinction needs to be explained through realistic examples, not left for each person to interpret.
A licence is a starting point - not a complete governance framework
Selecting an appropriate business service can form part of a controlled AI approach. But procurement alone does not decide which information is suitable to share, whether existing file permissions are appropriate or which outputs need human review. Those decisions remain part of the organisation’s governance responsibilities.Equally, an AI policy on paper is not enough without suitable tools and practical training. Responsible adoption brings the elements together: approved access, clear data boundaries, staff understanding and a way to raise questions or report mistakes promptly.
What should an AI governance and readiness review cover?
A focused review should establish where your organisation stands today and what needs to happen next. It should connect the opportunities teams want to pursue with the risks, responsibilities and practical controls those uses require.- Current AI use and readiness: Identify tools, use cases, staff needs and gaps in visibility or oversight.
- AI risk assessment: Assess data exposure, security, reliability, third-party arrangements and the consequences of proposed uses.
- Responsible AI governance: Define ownership, approval routes, human oversight and review arrangements proportionate to the risks.
- AI policy and staff guidance: Translate expectations into clear rules, realistic examples, training and incident-reporting procedures.
- A prioritised action plan: Address urgent gaps and select suitable pilot uses, with agreed checks before wider adoption.
How BDO Malta Can Help
Whether you are introducing AI, reviewing tools already in use or turning informal guidance into a practical policy, the starting point is clarity. Which uses can create value? Which data needs protection? Who is accountable, and what needs to change before adoption expands?Ready to move from AI experimentation to a more controlled approach? Contact BDO Malta’s Technology Advisory team to book an AI governance and readiness discussion. Explore your priorities for responsible AI governance, AI risk assessment and an AI policy that works in practice.