AI in Government

Public procurement accounts for roughly 13% of GDP across OECD countries — making it one of the most impactful domains for AI adoption in government. From streamlining workflows and enhancing oversight to fostering market transparency, AI is helping procurement systems become faster, more data-driven and more accountable. While most use cases remain focused on process optimisation, the field is evolving rapidly, offering a vision of more dynamic, responsive and transparent procurement ecosystems.

The current state of play

AI is being used throughout the public procurement lifecycle — from pre-tender planning to contract management. Key areas of application include:

• Streamlining operational tasks. AI can automate rule-based procedures such as classifying spend data, predicting procurement categories and flagging errors — saving time and improving consistency.
• Enhancing procurer–supplier relations and public servant capacities. AI-powered chatbots and digital assistants are helping suppliers navigate procedures and support procurement officers with form-filling, policy advice and real-time assistance.
• Improving risk management, oversight and accountability. Machine learning is used to detect anomalies, flag irregularities and support audit efforts. Some systems even analyse bidding patterns or text to identify fraud and corruption risks.
• Empowering external actors and strengthening trust in government. AI-driven analytics and dashboards allow civil society, oversight bodies and the public to monitor procurement activity in real time — increasing transparency and reinforcing accountability.

 ^{Potential use of AI and data analytics throughout the public procurement cycle.}

Despite these developments, implementation is still constrained by outdated legal frameworks, fragmented and inaccessible data, skills gaps and limited investment in infrastructure. Challenges around skewed data and transparency are particularly sensitive in procurement, where fairness and competition must be guaranteed.

Examples from practice

• Ukraine: Real-time procurement analytics with ProZorro. Ukraine’s e-procurement platform uses AI to improve CPV classification, detect risks and power dashboards used by over 30,000 users annually — supporting savings and regulatory reform.
• Chile: AI-powered procurement monitoring. ChileCompra’s Public Contracting Observatory applies LLMs to detect irregularities. The system also includes AI-ready templates that mandate ethical safeguards in procurement processes.
• United States: 24/7 chatbot procurement support. In North Carolina, an AI assistant answers staff questions about IT procurement processes — reducing bottlenecks and streamlining internal workflows.
• Brazil: Fraud detection and audit automation with Alice. The Alice system flags suspicious tenders, automates audits and has led to contract cancellations worth billions. It reduced average audit times from 400 days to just eight.
• Portugal: Enhancing audit targeting with AI. Portugal’s Court of Audit is working with the OECD to develop machine learning tools that flag risks in procurement, helping focus audit resources where they are most needed.

Untapped potential and the way forward

AI can support public procurement by anticipating market trends, matching suppliers to needs, setting price benchmarks and promoting integrity. Tools like LLMs can aid in screening and fraud detection, but adoption is still limited. Progress will require better data, stronger skills and user-centred design, along with clear governance, ethical safeguards and continuous evaluation to ensure fair and transparent use.

Learn more

Review a detailed section on AI in public procurement here.