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AI in Tender Evaluations


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Added by:   OECD analyst
Added on:   27 Oct 2026
Updated by:   OECD analyst
Updated on:   27 Oct 2026

The DTA is using AI to support the evaluation of tender submissions for the Digital Marketplace Panel 2. The initiative helps evaluators analyse large volumes of tender information more efficiently and consistently. All assessment decisions remain the responsibility of human evaluators. Ongoing monitoring and review processes are built into the governance structure to ensure continued fairness. The tool was developed to reduce administrative burden and enhance efficiency and transparency.

Initiative overview

The Digital Marketplace Panel 2 (DMP2) supports Australian Government procurement of digital and ICT services. Evaluating supplier submissions for DMP2 involves reviewing large volumes of structured and unstructured information against defined criteria, which can be time consuming and resource intensive.

The DTA is using an AI enabled tool to support evaluators by providing a check of an assessment as an AI check tool. The capability is used strictly as decision support and does not make automated recommendations or determinations.

The objectives are to improve evaluation efficiency, promote greater consistency across assessment teams, and enable evaluators to focus more time on professional judgement, risk assessment and value for money considerations.

Results, outcomes and impacts:
The initiative is focused on testing feasibility and usability rather than delivering measurable efficiency gains. Initial observations suggest AI support may assist evaluators to navigate large and complex submissions and identify areas requiring closer review.

Challenges and lessons learned:
Key challenges include managing information security and privacy, avoiding overreliance on AI outputs, and ensuring alignment with procurement and probity requirements. These risks are mitigated by limiting AI use to decision support, requiring human validation of all outputs, and maintaining clear audit trails. A key lesson is that strong governance, clear guidance for evaluators, and careful prompt design and testing are essential. Success depends on transparency, human oversight, and clear communication that AI does not replace professional judgement.

About the policy initiative


Category:

  • AI policy initiatives, programmes and projects

Initiative type:

  • AI use cases/projects in the public sector

Status:

  • Active

Start Year:

  • 2025

Target Sectors:


Other relevant urls:

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