An AI Usage Policy Template for Finance Teams

As finance teams adopt AI, having a clear policy governing how AI may be used — what is permitted, what is not, and the principles and safeguards that apply — is increasingly important, because it gives the team the framework to use AI well and safely, protecting against the risks of careless or uncontrolled AI use. An AI usage policy sets out how the finance team may use AI — the permitted uses, the rules around sensitive data, the safeguards required, the responsibilities — so that AI is used in a controlled, safe, consistent way rather than in an uncontrolled, risky one. For a finance team or leader looking to establish such a policy, understanding what an AI usage policy should cover and how to approach it is useful. This guide provides a framework and the elements for a finance team’s AI usage policy, which the team can adapt to its situation, rather than a fixed template, since the right policy depends on the team’s circumstances and should reflect the organisation’s wider requirements.

This guide is written for finance teams and leaders looking to establish an AI usage policy. It covers why an AI usage policy matters, the key elements such a policy should cover, how to approach the sensitive-data rules, the responsibilities and safeguards to set out, and how to implement and maintain the policy. It provides a framework and the elements to include, which a finance team adapts to its situation and aligns with the organisation’s wider policies and requirements, rather than a one-size-fits-all template, and where the requirements are complex or the stakes high, appropriate advice should be sought. The aim is an understanding of what a finance team’s AI usage policy should cover and how to establish one, so the team has the framework to use AI well and safely.

Why an AI Usage Policy Matters

An AI usage policy matters because it gives the finance team the framework to use AI in a controlled, safe, consistent way, protecting against the risks of uncontrolled AI use. Without a policy, individuals may use AI in varied, uncontrolled ways — some using it carelessly, some exposing sensitive data, some relying on it inappropriately — creating the risks of careless AI use across the team, with no consistent safeguards. A policy addresses this by setting out how AI may be used, establishing the permitted uses, the rules, and the safeguards, so the team uses AI consistently and safely.

An AI usage policy matters particularly for a finance team because of the sensitivity of finance data and the consequences of AI errors — the policy protects the sensitive data by setting rules around what may be used with AI, and guards against the risks of AI errors by requiring the appropriate safeguards, which are important given finance’s data sensitivity and accuracy demands. The policy gives the team clarity about what is permitted and expected, enabling safe, confident AI use within clear bounds, rather than either uncontrolled use or uncertainty that inhibits beneficial use. Understanding why an AI usage policy matters — because it provides the framework for controlled, safe, consistent AI use, protecting the sensitive data and guarding against the risks — is the motivation for establishing one. An AI usage policy is the framework that lets a finance team use AI well and safely, and understanding its importance is the reason to establish one.

The Key Elements the Policy Should Cover

An AI usage policy for a finance team should cover several key elements, and understanding them helps in drafting one. The policy should cover the permitted and prohibited uses — what AI may be used for and what it may not, setting the bounds of AI use in the team — so the team knows what is allowed. It should cover the rules around data, particularly sensitive data — what data may and may not be used with AI, and how, which is a crucial element given finance’s data sensitivity — so that sensitive data is protected. It should cover the safeguards required — the verification of AI output, the human oversight, the care in using AI — so that AI is used safely.

The policy should also cover the approved tools — which AI tools may be used, since tools vary in their suitability and data handling — so the team uses appropriate tools. It should cover the responsibilities — who is responsible for what in using AI, including the individual’s responsibility to use it properly and verify its output — so accountability is clear. It should cover compliance with the applicable requirements, including data protection and any regulatory requirements. And it may cover training and awareness, and the consequences of misuse. These elements — permitted and prohibited uses, data rules, safeguards, approved tools, responsibilities, compliance — are the key content of a finance team’s AI usage policy. Understanding the key elements the policy should cover helps a finance team draft a policy that provides the framework it needs. The elements together give the team the clear framework for safe, controlled AI use, and covering them is what makes the policy effective.

How to Approach the Sensitive-Data Rules

The rules around sensitive data are a particularly important element of the policy, given finance’s data sensitivity, and warrant careful thought. The policy should establish clearly what data may and may not be used with AI — distinguishing the sensitive, confidential data that must be protected from the data that may be used more freely — so that the team knows what sensitive data is off-limits or restricted for AI use. The rules should protect the confidential financial, commercial, and personal data the finance team handles, ensuring it is not exposed through careless AI use, as covered in the data security guidance.

Approaching the sensitive-data rules well means being clear and practical — giving the team usable rules about what data may be used with which tools, so they can apply the rules in practice — rather than vague or unworkable prohibitions. The rules should reflect the sensitivity of different data and the suitability of different tools, perhaps permitting less sensitive data with approved tools while restricting the most sensitive data, so the team can use AI beneficially while protecting what must be protected. The rules should also reflect the organisation’s wider data policies and any regulatory requirements. A finance team that approaches the sensitive-data rules this way — clear, practical, reflecting the data sensitivity and tool suitability, aligned with wider requirements — protects its sensitive data while enabling beneficial AI use. Understanding how to approach the sensitive-data rules helps a finance team establish the crucial data element of its AI policy. The sensitive-data rules are a crucial part of the policy, protecting the finance team’s confidential data, and approaching them well is central to an effective AI usage policy.

The Responsibilities and Safeguards to Set Out

The policy should set out the responsibilities and safeguards that ensure AI is used safely, and understanding these helps in drafting them. On responsibilities, the policy should make clear that individuals using AI are responsible for using it properly — within the permitted uses, following the rules, applying the safeguards — and for the output they use, including verifying it, so that accountability for proper AI use is clear. The finance professional using AI remains responsible for their work, including anything AI assists with, and the policy should establish this, so that AI use does not diffuse responsibility.

On safeguards, the policy should require the key safeguards for safe AI use — the verification of AI output, particularly anything factual or consequential; the human oversight and judgement, keeping the human in the loop as covered in separate guidance; the appropriate care with sensitive data; and the use of approved tools — so that AI is used with the safeguards that make it safe. By setting out these responsibilities and safeguards, the policy ensures that AI use across the team is accountable and safe, with clear responsibility and the necessary safeguards. A finance team whose policy sets out the responsibilities and safeguards clearly gives its members the framework for accountable, safe AI use. Understanding the responsibilities and safeguards to set out helps a finance team establish these essential elements of the policy. The responsibilities and safeguards are what make the policy ensure safe, accountable AI use, and setting them out clearly is central to an effective AI usage policy.

How to Implement and Maintain the Policy

An AI usage policy must be implemented and maintained to be effective, not merely written, and a finance team should attend to this. Implementing the policy means communicating it to the team, ensuring the members understand it, and embedding it in how the team uses AI — so the policy actually governs the team’s AI use, rather than being an unread document. The team should know the policy, understand what it requires, and follow it, which requires communicating and embedding it, perhaps with training and awareness-building so the members understand and can apply it.

Maintaining the policy means keeping it current as AI, the tools, the team’s use, and the requirements develop — because AI develops quickly, and a policy written once will date as the tools and uses change — so the policy continues to provide relevant, effective governance. The finance team should review and update the policy periodically, keeping it aligned with the developing AI landscape, the team’s evolving use, and any changing requirements. Maintaining the policy keeps it a living, effective framework rather than an outdated document. A finance team that implements and maintains its AI usage policy — communicating and embedding it, keeping it current — has an effective framework for safe AI use; one that writes a policy and leaves it unimplemented or outdated does not get the benefit. Understanding how to implement and maintain the policy helps a finance team make its AI usage policy effective. Implementing and maintaining the policy is what makes it a living, effective framework, and doing so is how a finance team keeps the benefit of its AI usage policy as its AI use develops. This connects to the guidance on data security when using AI and human-in-the-loop AI controls.

Balancing Control With Enabling Beneficial Use

An effective AI usage policy balances controlling the risks with enabling the beneficial use of AI, rather than being so restrictive that it prevents the team capturing AI’s value or so permissive that it fails to control the risks. A policy that is too restrictive — prohibiting most AI use, or hedging it with unworkable rules — may protect against risks but at the cost of the value AI could bring, leaving the team unable to benefit from AI. A policy that is too permissive — imposing few controls — may enable AI use but fail to protect against the risks, exposing the team to the dangers of uncontrolled AI use.

The right balance is a policy that enables the beneficial use of AI within controls that manage the risks — permitting and encouraging AI use for the tasks and data where it is safe and valuable, while restricting and safeguarding the uses and data that carry risk — so the team captures AI’s value while being protected from its risks. Striking this balance requires the policy to be considered and practical, reflecting a genuine understanding of where AI is beneficial and where it is risky, rather than a blanket restriction or a blanket permission. A finance team whose policy strikes this balance can use AI beneficially and safely; one whose policy is too restrictive or too permissive gets either too little value or too little protection. Understanding the need to balance control with enabling beneficial use helps a finance team craft a policy that serves it well. An effective AI usage policy balances controlling the risks with enabling the value, and striking that balance is what makes the policy genuinely useful rather than either stifling or exposing the team.