Managing AI Tools in Business: Build an Inventory and Review Use

Register the use, not just the product

An AI use inventory records where an organisation uses these tools and how each use is controlled. A shared file with restricted access can be a starting point; a new system is not essential. A use case is a specific task, such as summarising meeting minutes. Outputs are the text, recommendations or other results the tool produces.

One product can support several activities with different consequences. Drafting a public event description is different from analysing employee records or recommending a customer credit decision. Record each material use separately, even when those uses sit within one approved organisational workspace.

The US National Institute of Standards and Technology (NIST) includes system inventories in its AI Risk Management Framework (AI RMF 1.0). This appears in GOVERN 1.6 of the framework, published in 2023. The framework is voluntary, not a law. The practical register proposed here is a management aid inspired by that principle, not a certificate of compliance. Its detail should reflect the organisation and the possible effect of each use.

Find existing uses without encouraging concealment

Ask departments which tasks use AI, what information is entered and where outputs go. Review approved purchasing and software records through authorised internal processes. Explain that the aim is to establish safe, useful working arrangements, not to reward teams for reporting no use.

Distinguish an experiment from an approved operational use. Give trials an owner, a limited purpose and an end date. A trial should not become a permanent process simply because nobody reviewed it. Also record AI features embedded in existing software, even when they have no separate subscription. Integrations are connections that allow a tool to exchange data with other systems. Record these and browser extensions when they change access to organisational information.

Keep a small, useful set of fields

After the initial inventory, create a row for each material use and give it a permanent reference number. Start with the following fields, adding detail according to the possible consequences:

Link the record to the approved configuration and vendor information rather than copying pages of terms into it. Record when those details were checked. Product names, account tiers and settings can change; an old approval should not silently cover a materially different service.

Turn the inventory into a scoped decision

Listing a tool does not approve its use. Add a clear status, such as “under assessment”, “limited trial”, “approved with conditions” or “suspended”. Link it to the decision owner, date and scope. When an important question remains unanswered, record what is needed to resolve it rather than adding a general approval tick.

In a hypothetical example for illustration, a team wants to summarise internal meetings. Evaluation starts with sample text containing no confidential or personal information. The owner reviews accuracy and omissions, then checks access settings and vendor documentation. Passing this trial does not automatically permit real recordings. Changing the input data requires a separate review appropriate to that information.

Use boundary

Prepare an internal draft only, with no automatic sending or execution of decisions.

Acceptance evidence

Samples retained under policy, reviewer observations and the result of checking approved settings.

Stop condition

The team cannot maintain the data boundary, or material errors exceed what the available review can correct.

This is an illustrative management record, not a complete legal checklist or an endorsement of a product. Uses affecting people or their rights may need deeper assessment than a tool for brainstorming public ideas.

Review changes that matter

Set the next review date according to the use’s consequences and rate of change. Also define triggers for an earlier review. A new data category, broader user access, an important vendor change or a move from drafting to automated action can require reassessment. The relevant question is whether the use still fits its approval, not whether the tool is still fashionable.

Check current vendor documentation and organisational settings for input and output retention periods and use in model training. Training uses data to develop a model’s performance; this differs from retaining data to provide the service. Do not assume that all plans from the same provider have identical terms. In the UAE, assess applicable data-protection requirements for the organisation and processing involved; different regimes and circumstances can require specialist advice.

Identify where users should report a data leak or material error. Assign someone to decide whether to suspend use and select a temporary alternative. An urgent problem should not wait for the next scheduled review.

Measure useful work and the cost of checking it

Choose task-level evidence such as accepted drafts, correction effort or completed requests. Compare the full workflow, including review and rework, with a baseline: the task’s time, cost and quality before using the tool, under comparable conditions. Faster generation is not necessarily faster completion. Include subscription, setup, training and support costs alongside the time spent completing and reviewing the task.

In a hypothetical example for illustration, preparing and reviewing a report manually takes 60 minutes. With the tool, preparing inputs and generating a draft takes 15 minutes. Review and correction take another 35 minutes. The total is 50 minutes, saving only 10 minutes per report, provided both methods achieve the same acceptable quality. Claiming a 45-minute saving from drafting time alone would be misleading.

This is a time saving, not a verified financial saving: subscription and setup costs have not been deducted. Test several comparable tasks before generalising. If correction consumes most of the benefit, narrow the use or improve the review method.

Make updates part of handing over the work

Assign responsibility for updating the register when an owner leaves, a contract changes or another team takes over. Review connected accounts and integrations. Ensure the replacement owner can access the approved instructions. The reasons for allowing some data and excluding other information should not depend on one person’s memory.

During a periodic review, trace one use from input data to the output actually used. Compare practice with the register. If only the documentation is wrong, correct the description. A change in actual use is not approved simply by updating the register. Suspend the unapproved activity until the responsible person decides. Keep the change date and reason without copying sensitive information into the register. This turns an expanding list of names into a record of responsibility that the team can check.

Retire duplicate or unsuitable uses deliberately

Before closing an account, identify work that depends on it and confirm an approved replacement or manual route. Export necessary business records where permitted, transfer ownership and remove integrations and access. Handle retained data according to applicable contracts and policies. Closing a subscription alone may not complete the exit.

Keep a short record of why the use ended and any unresolved issue. This prevents another team from repeating an unsuccessful trial without learning from it. Do not retain unnecessary personal data simply to document the decision.

Start with one department

Inventory current uses in one team, resolve unclear ownership and choose the highest-consequence gaps first. Expand the register once people can maintain it as part of ordinary work. A complete-looking spreadsheet that nobody updates gives false confidence.

ATMACSS innovation and future foresight can help organisations connect AI opportunities with practical governance. For software acceptance methods, see turning requirements into test cases; the examples there concern HR systems, but the discipline of explicit acceptance is also useful here.