Aged Care AI Procurement Checklist

An aged care AI procurement checklist helps a provider test policy fit before a contract creates operational pressure. It changes the first vendor conversation from “what can this product do?” to “what will this specific use mean for residents, staff, records, permissions and local policy?” That framing gives procurement teams a clearer basis for comparison and approval.

The checklist is not a promise that a vendor is suitable, and it does not replace technical, privacy, clinical or legal advice. It is a pre-contract working record that gathers the right questions, evidence and decision owners while the provider can still set conditions, decline a feature or choose a smaller pilot.

Define the Proposed Use Before Reading the Sales Material

Write a one-sentence use statement before asking a supplier to complete questionnaires. Identify the users, setting, intended output, person who acts on the output, and the decision or workflow affected. “AI for care” is not detailed enough. “A rostering function that predicts absenteeism for the workforce planner” is a more testable proposal.

Separate administrative support, information retrieval, documentation assistance, resident communication, monitoring, decision support and automated action. The question is not whether a product is generally useful. The question is whether this use has a documented purpose, a responsible owner and controls that fit the provider’s policies. The aged care AI readiness assessment helps teams examine whether the organisation has the data, people and governance foundations for the proposed use.

Test Policy Fit at the Start

List the local policies that apply, then ask the supplier questions against each one. Typical sources include privacy, security, clinical governance, records management, incident management, procurement, delegations, workforce use and AI or automated decision-making. The AI and automated decision-making policy template can help procurement teams frame questions about human oversight, transparency, approved use and incident escalation.

For each policy source, record the relevant rule, the supplier evidence requested, the reviewer and the decision. This produces a decision trail that is much stronger than a general statement that the product is “compliant”. If a policy does not yet address the use, record the gap and the owner of the policy decision. Do not make a contract approval stand in for an internal policy approval.

Ask What the System Does With Data

Procurement should ask for a plain-language data-flow description. What data goes into the service? Where is it processed and stored? What data leaves the service? Does the supplier use inputs, prompts or outputs to improve its product? Can the provider turn that use off? Who can access logs and support records? Answers should cover the product configuration being bought, not only a supplier’s general privacy statement.

Classify the proposed data: resident information, health or care information, worker information, incident data, financial data, operational data, de-identified data or public content. Confirm whether the tool reads, writes, copies, retains or exports data. Ask how deletion, correction, retrieval and access requests would work in the actual workflow. These questions support clear permission boundaries before staff have accounts.

Check Human Roles and Escalation Paths

Ask the supplier to demonstrate the human decision points. Who checks an output before it is acted on? Can staff override or reject a recommendation? Is there a clear warning when the system lacks relevant information? How are exceptions, complaints and suspected errors recorded and escalated? A useful answer names product settings, not just a commitment to human oversight.

For care-related use, test the workflow with the people who would use it on shift. They can identify confusing labels, missing context, unsafe hand-offs and workarounds that a demonstration misses. The guide to using AI tools responsibly in aged care provides a staff-focused resource for recognising AI limits and escalating beyond an AI answer. Procurement should budget for that training and make the expected use part of onboarding.

Request Evidence That Can Be Reviewed

A questionnaire is only a starting point. Ask for the documents or demonstrations that support material answers: architecture and data-flow diagrams, security information, role and permission controls, release notes, support arrangements, incident process, service continuity arrangements, test results, model documentation where available, subcontractor list and contract terms. Date each item and tie it to the proposed configuration.

Assign evidence review to the people who can assess it. IT may assess identity, access and integrations; privacy may assess data handling; clinical governance may assess care workflow; procurement may assess commercial terms; the business owner may assess practical benefit and change readiness. Governa’s AI policy and evidence mapping describes the benefit of making evidence and policy relationships visible rather than dispersing them across folders and email threads.

Assess Integration and Permission Changes

An AI product can change character when linked to another system. A function that drafts a response from public material is different from one that reads care notes, writes into a resident record or triggers a task. Ask which integrations are available now, which are planned, which scopes are requested and how a provider can limit them. Include sandbox, test and production environments in the answer.

Do not approve “future integrations” in broad terms. Treat a new source system, an expanded data category, a changed permission level or automated write-back as a later review point. Governa Connect explains the value of connecting policy and operational information in a common infrastructure, but the procurement decision still needs to define which connections are approved and who can authorise a change.

Compare Vendors on Conditions, Not Marketing Scores

Use a simple decision table that shows required conditions, evidence received, residual questions, reviewer recommendation and final decision. A vendor may be suitable only for a limited data set, a supervised pilot or a non-clinical workflow. That is a useful outcome. It avoids forcing an all-or-nothing decision when the evidence supports a controlled beginning.

Set non-negotiable gates before evaluation: a defined use, identified owner, policy source list, data-flow answer, human escalation pathway, acceptable permissions, contract review and a change-notification commitment. The Governa policy template library can support the connected policy work around procurement decisions, while grounded AI in aged care explains why aged care staff need answers tied to their own facility context rather than broad online content.

Build the Checklist Into the Contract and Onboarding

Carry the decision into the agreement and implementation plan. Record the approved use, limitations, responsibilities, notification expectations, evidence held, review date, training requirements and conditions for any pilot extension. A contract should not be the only place these details live. Put the approved use into the AI tool register and reference the relevant policies so operational owners can find the conditions later.

The Australian Government’s Australian Government guidance for AI adoption describes responsible AI adoption practices including accountability, impact planning, risk management, testing and human control. The Aged Care Quality and Safety Commission’s Quality Standards guidance provide the provider-facing reference for the strengthened Aged Care Quality Standards. These sources give useful context, but a procurement checklist should remain specific to the provider’s service, policies and proposed workflow.

Pre-Contract Checklist for an Aged Care AI Tool

State the intended use, users, setting and decision point.
Name the business owner, accountable approver and specialist reviewers.
Link the relevant local policies and document any gap.
Map inputs, outputs, storage, retention, integrations and permissions.
Test human review, override, escalation and incident handling.
Request dated supplier evidence for material claims.
Set contract conditions, pilot measures, training and change-notification requirements.
Record the approval, limitations and next review in the AI tool register.

Keep the completed checklist with the evaluation record, rather than treating it as a one-time form. It gives future reviewers a clear starting point when the contract is renewed, a feature is activated or the supplier proposes a different data connection. That saves time and keeps the original policy-fit decision visible.

Related Resources

Common Questions About AI Procurement in Aged Care

1. When should an aged care provider use an AI procurement checklist?

Use it before signing, renewing or materially expanding a product that uses AI-enabled functions. It is also useful when a current supplier activates a new assistant, model, integration or data permission.

2. What is the first question to ask an AI vendor?

Ask the vendor to describe the exact proposed use, inputs, outputs, users and decision point in plain language. That answer gives the provider a basis for policy, data and workflow review.

3. Should a vendor’s privacy policy be enough for procurement approval?

No. Request information about the purchased configuration, including data flow, retention, support access, integrations, settings and supplier use of inputs or outputs. Local policy fit also needs its own assessment.

4. Can an AI tool be approved for a pilot only?

Yes. A limited approval can set a narrow use, selected users, data boundaries, review measures and an end date. Record what evidence is needed before any wider use is considered.

Aged Care AI Procurement Checklist: Assessing Vendors Against Your Policies