Shadow AI – Defining Acceptable AI Use at Work

Why Employees Need Clarity, Not Generic Policy Statements

One of the most common weaknesses in organisational responses to Shadow AI is the reliance on high-level policy statements. Many organisations publish guidance that is well intentioned but abstract. Phrases such as “use AI responsibly” or “avoid sharing sensitive information” do little to influence day-to-day behaviour.

Employees do not make decisions based on policy language. They make decisions based on time pressure, expectations, and what they believe is acceptable within their team. When guidance is vague, employees fill in the gaps themselves.

This lack of clarity creates inconsistency. Some employees avoid AI entirely out of caution, even where use would be low risk and beneficial. Others use AI extensively, assuming that if it has not been explicitly prohibited, it must be acceptable. Neither outcome supports effective governance.

Defining acceptable AI use requires moving beyond generic principles and toward practical categorisation. Employees need to understand which uses are acceptable, which are higher risk, and which are not permitted under any circumstances. This distinction must be grounded in real work scenarios, not theoretical examples.

Acceptable use may include activities such as drafting generic text, summarising non-sensitive documents, or supporting routine analysis using public information. Higher-risk use may involve internal data, client information, or decision-making that requires oversight. Prohibited use may include processing personal data, confidential commercial information, or regulated content through unapproved tools.

Importantly, acceptable use definitions should support judgement rather than replace it. Employees and managers need space to ask questions and seek guidance when situations fall into grey areas. Rigid rules that attempt to cover every scenario quickly become outdated or ignored.

Clarity also supports accountability. When expectations are explicit, managers can supervise effectively, and employees understand their responsibilities. Governance becomes part of everyday decision-making rather than an abstract compliance requirement.

Organisations that invest time in defining acceptable AI use in practical terms reduce confusion, improve compliance, and build trust. They replace uncertainty with shared understanding and enable responsible use rather than driving behaviour underground.