Ukraine Moves to Data-Driven Drone Procurement

From Technical Specifications to Proven Combat Effectiveness

Complex law. Clear action.

Ukraine is changing the logic of public procurement for unmanned systems. Instead of relying on manually defined requirements and preselected products, procurement decisions will increasingly be based on measurable operational performance, actual demand from military units and data generated by digital battlefield systems.

This is more than the automation of an administrative process. The new model connects three elements that often remain separate in conventional defence procurement: operational demand, verified product performance and government contracting. For manufacturers, access to large-scale procurement will therefore depend not only on codification and compliance with technical requirements, but also on performance demonstrated under real operational conditions.

What Has Changed

On 10 March 2026, Ukraine’s Ministry of Defence announced the introduction of a new approach to UAV procurement. The relevant order was signed by Minister of Defence Mykhailo Fedorov.

Under the new model, the General Staff will compile procurement requirements in response to requests from military units, using technical characteristics rather than identifying a particular product or manufacturer. The specific drones to be procured will be determined by a ranking based on data from five digital systems. Official announcement by the Ministry of Defence of Ukraine

Each system contributes a different category of information:

• ePoints provides statistics on the actual battlefield effectiveness of equipment;

• DOT-Chain and Brave1 Market provide data on the products independently selected and ordered by military units, reflecting real demand at operational level;

• DELTA and Mission Control provide combat-employment analytics and data used to synchronise requirements.

Based on the resulting ranking, the Defence Procurement Agency DOT carries out the contracting process. The procurement mechanism depends on how specifically the requirement is defined. Procurement may involve direct contracts based on a detailed specification or closed competitive procedures where only the tactical and technical characteristics are prescribed.

Both Ukrainian and foreign verified manufacturers may participate in relevant procedures. Ministry of Defence explanation of Ukraine’s defence procurement models

A new budget-allocation principle is being introduced at the same time:

• 80% of the available funds will be directed towards solutions whose effectiveness has been demonstrated by system data;

• 20% will be reserved for innovation and the procurement of new solutions for testing under combat conditions.

The model therefore creates two parallel routes: scaling solutions with proven performance and providing controlled access for emerging technologies to operational testing.

Why This Is Data-Driven Procurement

In a conventional procurement model, the public buyer first defines a requirement and then evaluates whether submitted products meet the prescribed conditions.

The Ukrainian approach adds a closed feedback loop: the operational performance of previously supplied equipment influences subsequent demand generation and budget allocation.

The process can be presented as follows:

1. A military unit identifies an operational task and the required technical characteristics.

2. Digital systems record demand, deployment and product performance.

3. A ranking matches available solutions with verified performance indicators.

4. The General Staff formulates the procurement requirement.

5. The Defence Procurement Agency conducts the contracting process.

6. New operational results are fed back into the system and influence the next procurement cycle.

The digital infrastructure is already operating at a significant scale. According to the Ministry of Defence, by the end of May 2026 military units had received 485,000 UAVs and other items worth UAH 31.4 billion through DOT-Chain Defence. The average period between ordering an available product and receiving it was nine days.

DOT-Chain Defence complements rather than replaces Ukraine’s centralised military supply system. Ministry of Defence data on DOT-Chain Defence

Automation Does Not Remove Human Decision-Making

The announced model reduces the scope for subjective selection of particular products, but it does not eliminate human influence. Instead, human judgement moves to another level: the rules governing data collection and validation, the ranking methodology and the management of exceptions.

Five issues become particularly important.

Data quality and comparability. Operational performance depends not only on the drone itself, but also on the type of mission, operator training, weather, the electronic-warfare environment, munition quality and tactics. The ranking methodology must distinguish product deficiencies from external operational factors.

Evaluation methodology. The number of targets struck may be an important indicator, but it is not universally applicable. Reconnaissance drones, communications relays, interceptors and strike platforms create different types of military effect. They cannot be assessed fairly using a single metric.

Decision traceability. Internal control requires the ability to establish which data and criteria resulted in a product being included in or excluded from a procurement requirement. This is important for audits, challenges and the identification of systematic errors.

Protection against manipulation. Where a ranking affects access to government contracts, market participants may have incentives to influence the underlying data or its interpretation. Appropriate safeguards include access controls, event verification, change logging and anomaly detection.

Cybersecurity and military secrecy. Combining procurement, logistics and battlefield data increases the value of the system, but also makes it a high-value target. Its architecture must balance sufficient transparency for oversight with strict protection of sensitive operational information.

Data-driven procurement therefore requires more mature governance, not less. Trust shifts from an individual decision-maker to the integrity of the entire data chain, from recording an event on the battlefield to generating a ranking and making the resulting procurement decision.

What This Means for Manufacturers

The meaning of competitiveness is changing. Formal compliance with a technical specification remains necessary, but it is no longer sufficient.

Manufacturers will need to demonstrate that:

• the product consistently performs a defined operational function;

• its effectiveness is measured through reliable and reproducible indicators;

• production and delivery can be scaled rapidly;

• the product can be adapted in response to operational feedback without losing control over quality and configuration.

Market access may be particularly difficult for new products. Where a ranking is based primarily on historical performance data, it will naturally favour solutions that are already in operational use.

Reserving 20% of the budget for innovation should reduce this barrier. The effectiveness of that mechanism will nevertheless depend on the rules governing selection, testing, documentation of results and the transition of a successful prototype into the main 80% procurement stream.

For foreign manufacturers and joint Ukrainian–European projects, a technological advantage alone will also be insufficient. The parties must establish a route through codification and operational testing, agree on rights to data and subsequent modifications, protect intellectual property, allocate responsibility for defects and comply with export-control and security requirements.

Relevance for European Defence Policy

The Ukrainian model provides a practical example of procurement decisions being connected to a continuous stream of product-use data.

This experience may be relevant to European programmes seeking to accelerate defence innovation, facilitate joint testing and reduce the time between product development and large-scale deployment.

Transferring the model into an EU setting would, however, require adaptation. Particular attention would need to be paid to:

• competitive access and equal treatment of suppliers;

• documentation of evaluation criteria;

• protection of commercially sensitive information;

• cybersecurity;

• the ability to review automated recommendations;

• procedures for challenging decisions and correcting inaccurate data.

Ukraine’s experience is therefore most valuable not as a template to be copied unchanged, but as a high-intensity operational model for creating a feedback loop between users, data and procurement decisions.

What Companies Should Do Now

Manufacturers and technology partners should:

1. Define the measurable operational effect created by each product.

2. Prepare an evidence base using testing and deployment results.

3. Ensure the traceability of hardware and software versions.

4. Establish rules for data access, verification and permitted reuse.

5. Review contracts covering intellectual property, confidentiality, cybersecurity, liability and export controls.

6. Develop a clear route from pilot testing to serial production and government contracting.

The Corvus AI Perspective

The transition to procurement based on battlefield data changes more than the process for selecting drones. It also changes the legal architecture of the market. Performance data becomes a factor determining access to government contracts, while the methodology used to generate rankings becomes part of the effective framework through which public budgets are allocated.

Corvus AI supports Ukrainian and European developers in building a legally governed route from technology testing to procurement and scaling. This includes defining requirements for evidence, data and contracts; analysing procurement pathways; protecting intellectual property; and addressing export controls, cybersecurity and the allocation of liability.

This article is based on publicly available statements issued by the Ministry of Defence of Ukraine. The detailed ranking methodology and the text of the ministerial order have not been made public in the cited materials. The discussion of governance structures and associated risks therefore constitutes analytical assessment rather than a description of non-public system rules.