Introduction

This report is the third and final output of the United Nations Global Compact Human Rights Think Lab on supply chains. It distils practical lessons from 25 leading companies and organisations on how technology can strengthen human rights due diligence (HRDD) in value chains. The initiative operated as a collaborative multi-stakeholder platform from November 2024 to December 2025, convening participants with unique experience in maturing their direct operations and supply chain practices. This report complements previous Think Lab outputs, including the Playbook on Embedding Human Rights Due Diligence and the Insights Report on Strategic Engagement with MSIs for HRDD.

Background

Technological solutions are defined as digital platforms, data systems, and software applications designed to collect, analyse, and manage information relevant to HRDD. Several technology categories assist companies, including internal management software, generative AI tools, traceability platforms, satellite monitoring, adverse media screening, worker voice and grievance platforms, and risk scoring and analytics platforms. Legislative pressure, particularly regarding forced labour and deforestation, has accelerated the adoption of these tools as companies seek systematic ways to meet rising due diligence expectations. However, effectiveness depends on thoughtful integration, data quality, and sustained human oversight.

Overarching insights for implementing technology in HRDD

The Think Lab identified five critical things companies need to know before adopting technology. Firstly, technology is an enabler, not a substitute; no tool replaces the human judgement and contextual expertise required for effective HRDD. Secondly, data quality determines insight quality, as tools are only as strong as the data behind them. Systems often over-represent issues where quantitative data is abundant, such as workplace injury rates, while under-representing risks in informal or lower-tier supply chain settings.

Thirdly, technology categories are not interchangeable; tools like satellite monitoring and grievance digitisation serve different purposes and require different governance. Fourthly, companies must conduct HRDD on the tools themselves to assess risks like algorithmic bias or data privacy breaches. Finally, the risk of supply chain “cleaning” is real, where AI-driven risk screening might incentivise companies to drop flagged suppliers rather than engage to improve conditions, potentially harming the workers the tools are meant to respect.

Conducting HRDD on AI tools

Companies using AI-powered tools have a specific governance responsibility to assess the tool’s own human rights risk profile before, during, and after deployment. Practical steps include conducting a human rights impact assessment (HRIA) on any AI tool before procurement, focusing on training data quality and algorithmic bias. Companies should require AI vendors to demonstrate their own HRDD processes, including how they manage the rights of data labellers. AI outputs should be treated as starting points for human analysis rather than final judgements.

Company case studies: Lessons from practice

Case studies illustrate diverse experiences with technology deployment. Unilever’s ETHICS pilot, developed with IBM, explored how AI could identify potential human rights impacts by scanning open-source data. The pilot found that reliance on freely available data limited the platform’s ability to detect issues already known to practitioners. Another case study, Altana, filters large volumes of procurement data to direct attention to higher-risk relationships, proving valuable for “noise reduction.”

Satellite monitoring tools are used to track deforestation risk in agricultural supply chains, though they cannot detect labour rights violations. Finally, Kakuzi PLC’s SIKIKA grievance mechanism demonstrates how digitising worker voices through WhatsApp or telephone can increase trust and uptake by offering greater perceived privacy than physical suggestion boxes. These examples highlight that while technology manages scale, human expertise remains the critical benchmark for validation.

Key guidance on AI and human rights due diligence

Authoritative guidance has developed rapidly. The OECD Due Diligence Guidance for Responsible AI (February 2026) bridges the OECD AI Principles with existing business conduct frameworks. Other essential resources include the OHCHR B-Tech Project paper on generative AI and the UNDP Human Rights Impact of AI Assessment Toolkit (December 2025). These resources signal concrete expectations for responsible practice, urging businesses to integrate AI oversight into existing management systems rather than creating parallel processes.

Conclusion

Technology offers powerful solutions to manage the scale and complexity of global supply chains, but its role is fundamentally one of enablement rather than replacement. Responsible adoption requires rigorous piloting, prioritising data quality, and ensuring that new systems align with existing workflows. As AI continues to evolve, companies must remain attentive to ensuring that human rights impact continues to guide their due diligence decisions, reinforcing a genuinely impact-driven approach to protecting fundamental workers’ rights.