AI and Modern Slavery: Supply Chain Due Diligence in Australia

Supply chains are invisible. Your organisation might source components from 200 suppliers across 40 countries, none of whom you’ve visited. How do you know whether any employ forced labour, child workers, or trafficked populations? Historically, the answer was guesswork: compliance questionnaires, third-party audits, and hope. Now AI is changing the game—for both good and harm.

Australia’s Modern Slavery Act 2018 requires entities with annual consolidated revenue above AU$100 million to report annually on how they identify and address modern slavery risks. That reporting obligation now intersects with AI: organisations are deploying machine learning to map supply chains, detect risk signals, and automate compliance. But AI also creates new modern slavery risks: biometric data collection without consent, algorithmic labour exploitation, and supply chain opacity masked by algorithmic complexity.

This guide walks you through your Modern Slavery Act reporting obligations, how AI creates modern slavery risks, how to use AI ethically to combat modern slavery, and what your mandatory statement must disclose.

Modern Slavery Act 2018: Who Must Report and What They Must Disclose

Australia’s Modern Slavery Act 2018 applies to “reporting entities”—entities carrying on business in Australia with annual consolidated revenue of at least AU$100 million. The list includes Australian companies, foreign companies with Australian operations, and statutory bodies. For 2025-26, approximately 3,000 entities are in scope.

What must your statement disclose? The Act requires you to describe:

• The structure and operations of your organisation and supply chains
• Modern slavery risks in your operations and supply chains
• Actions you’ve taken to assess and address those risks
• How you’ve consulted with stakeholders, including workers and unions
• How you’ll measure the effectiveness of your response

Statements must be approved by the board and lodged on the Modern Slavery Statement Register. There’s no prescribed format, but statements should be candid: if you haven’t assessed slavery risks, say so. If you don’t have supply chain visibility, disclose it and outline your plan. The eSafety Commissioner and the recently appointed Anti-Slavery Commissioner scrutinise statements for gaps and lack of rigour. Vague commitments attract regulatory attention.

How AI Creates Modern Slavery Risks

Many organisations view AI as a solution to modern slavery. But AI also creates new risks—often invisibly. Consider three mechanisms:

Supply Chain Opacity Through Algorithmic Complexity

Suppose your organisation uses machine learning to optimise supplier selection based on cost, delivery speed, and quality. The algorithm identifies a network of sub-suppliers, aggregates their data, and recommends purchasing decisions. But the algorithm’s logic is opaque: you can’t easily explain why it selected a particular supplier, which workers produced the goods, or whether those workers faced modern slavery risks. This algorithmic opacity—where the AI system creates supply chain relationships that humans can’t trace—masks modern slavery.

Think of supply chain visibility as cartography: traditional maps show you every route and settlement; algorithmic pathfinding hides the journey. If your organisation can’t explain its supply chain because AI made the decisions, you’ve created opacity that enables modern slavery.

Biometric Data Collection Without Consent or Protection

Some organisations deploy AI-powered biometric systems in supply chain facilities: facial recognition for worker access control, fingerprint scanning for timekeeping, voice analysis for quality assurance. These systems can enhance safety and efficiency. But they also enable surveillance and exploitation. Workers may not understand what data is collected, who accesses it, or whether it’s used to monitor productivity or inform termination decisions. Without strong consent, data protection, and transparency frameworks, biometric AI can facilitate labour exploitation.

Algorithmic Labour Exploitation in Gig and Contingent Workforces

Algorithmic management systems—algorithms that assign tasks, set pay, monitor performance, and trigger termination—are proliferating in gig economy platforms. These systems can optimise labour efficiency but can also enable modern slavery-adjacent practices: workers lack minimum wage protections, benefits, or job security; algorithmic management obscures employment relationships; and workers have no transparency into decision-making. If your organisation uses AI to manage a contingent workforce in supply chains or operations, you must assess whether algorithmic management enables labour exploitation.

Using AI Ethically to Combat Modern Slavery

The flip side: AI, deployed responsibly, can strengthen modern slavery detection and prevention. Consider three applications:

Supply Chain Mapping and Risk Segmentation

Machine learning can ingest vast supplier data—location, industry, workforce size, wage levels, regulatory environment—and flag high-risk segments. For example, AI can identify suppliers in jurisdictions with weak labour protections, high human trafficking prevalence (using Global Slavery Index data), or industries recognised as high-risk for modern slavery (apparel, electronics, agriculture). This risk segmentation helps you prioritise due diligence: you audit high-risk segments more deeply and low-risk segments less frequently, improving efficiency and compliance.

Anomaly Detection and Red Flag Identification

Machine learning can analyse supplier self-assessment questionnaires and supporting documentation to identify anomalies: supplier reporting contradictions, wage data inconsistencies, unusual workforce composition, or labour cost discrepancies. These anomalies may signal modern slavery risk. AI doesn’t replace human investigation—it surfaces cases that warrant deeper review. This automation scales due diligence: you can assess 1,000 suppliers in the time it takes to manually assess 50.

Real-Time Monitoring and Incident Response

AI systems can continuously monitor supplier data—news reports, regulatory filings, labour disputes, financial metrics—to identify emerging modern slavery risks. For example, if a supplier experiences sudden workforce turnover, wage cuts, or regulatory violations, AI flags it for investigation. This real-time approach is more responsive than annual questionnaires and can enable faster incident response.

Building Your Modern Slavery Statement: Mandatory Disclosure Requirements

Your Modern Slavery Statement must address:

1. Supply Chain Risk Assessment

Describe the sectors, geographies, and workforce segments in your supply chain that face modern slavery risk. Don’t be vague: name the regions (Southeast Asia, Sub-Saharan Africa, Eastern Europe), the industries (apparel, electronics, agriculture), and the vulnerable groups (migrants, women, children). Reference the Global Slavery Index or International Labour Organisation data to ground your assessment. If your supply chain includes high-risk segments, say so. If you haven’t assessed slavery risk systematically, disclose that and outline your plan.

2. AI Systems and Their Modern Slavery Implications

If your organisation uses AI in supply chain management, operations, or labour management, describe it: what AI systems do you operate? What personal data do they process? How do they make decisions affecting supply chain partners or workers? What modern slavery risks do they create? For example:

“We use machine learning to optimise supplier selection based on cost, quality, and delivery metrics. This system aggregates data from 800+ suppliers and recommends purchasing decisions. Risk: algorithmic opacity may obscure supply chain visibility and modern slavery risks. Mitigation: we’ve implemented explainability testing to trace algorithmic recommendations back to source suppliers, and we conduct manual due diligence on all suppliers recommended by the algorithm, including modern slavery risk assessment.”

3. Due Diligence Processes and Effectiveness Measures

Describe how you assess modern slavery risk: do you conduct supplier questionnaires, audits, or interviews? How frequently? Do you engage workers directly or rely only on management responses? Do you use AI to automate or enhance assessment? How do you measure effectiveness: number of suppliers assessed, high-risk suppliers identified and remediated, incidents prevented? Provide numbers. “We assessed 600 of 800 suppliers using a machine learning-assisted questionnaire process, identified 47 high-risk suppliers, conducted on-site audits of the 12 highest-risk, and remediated 8 identified modern slavery indicators.” Numbers signal rigour.

4. Stakeholder Consultation and Grievance Mechanisms

How have you consulted with workers, unions, NGOs, and suppliers about modern slavery risk? Do workers have a mechanism to report exploitation without fear of retaliation? Do you publish grievance data—how many reports you received, how many you investigated, what remediation you provided? If you use AI to manage worker communications or grievances, describe it: does AI help identify patterns in grievance data, or could AI obscure worker concerns?

5. Transparency About Gaps and Future Action

Honest statements identify gaps: “We have visibility into Tier 1 suppliers but limited visibility into sub-suppliers. We’re implementing a blockchain-based supply chain tracking system to improve transparency.” Or: “We don’t currently assess modern slavery risk in our contingent workforce. We’re piloting an AI system to flag algorithmic management risks and will phase in modern slavery due diligence by Q2 2027.” Regulators prefer honesty and a roadmap over false certainty.

Frequently Asked Questions

Q1: Do I have to disclose AI-specific modern slavery risks in my statement?

Yes. The Modern Slavery Act requires you to describe actions you’ve taken to assess and address modern slavery risks. If you’ve deployed AI in supply chain management or labour management, you’ve created AI-specific risks. Your statement must describe those risks, how you’ve assessed them, and what mitigation you’ve implemented. Omitting AI risks is incomplete due diligence.

Q2: If a supplier is using biometric AI systems, am I responsible?

Responsibility is shared. The Act applies to your supply chains, not just your direct operations. If a supplier is using biometric systems that enable labour exploitation, you have a due diligence obligation to assess that risk and require the supplier to improve. Your due diligence process should include questions about supplier use of AI, data protection practices, and worker consent mechanisms. If a supplier refuses to disclose or improve, escalate the relationship.

Q3: What’s the difference between modern slavery risk assessment and broader supply chain compliance?

Modern slavery risk assessment is specific: it focuses on forced labour, human trafficking, child labour, and debt bondage. Broader supply chain compliance covers these but also labour law compliance, environmental standards, and ethical sourcing. For Modern Slavery Act reporting, focus narrowly on slavery-specific risks. But best practice addresses both: comprehensive due diligence improves compliance across all supply chain governance.

The Editorial View: Algorithmic Transparency as Modern Slavery Defence

Modern slavery thrives in opacity. Complex supply chains, informal labour markets, and unregulated intermediaries hide exploitation. AI can worsen this opacity—algorithmic complexity masking supply chain relationships and algorithmic management enabling labour exploitation. But AI also creates accountability: organisations deploying AI in supply chains must explain and justify algorithmic decisions, creating transparency and reducing hiding space for slavery. The organisations winning in supply chain compliance are those that use AI as a transparency tool, not an opacity layer. Build supply chain visibility first; deploy AI second to enhance it.

Take Action: Audit Your Modern Slavery and AI Risks

If your organisation is a Modern Slavery Act reporting entity, your 2025-26 statement is due in 12 months. Audit your current statement: does it assess AI-specific modern slavery risks? Does it describe your due diligence processes and effectiveness measures? Does it acknowledge gaps and outline improvement plans? If the answer is no, you have work to do.

Anitech helps Australian organisations build responsible modern slavery due diligence programs that integrate AI ethics, supply chain transparency, and regulatory compliance. We work with procurement, compliance, and supply chain teams to assess modern slavery and AI risks, design due diligence frameworks, implement detection systems, and prepare Modern Slavery Statements that demonstrate genuine commitment to remediation. Contact us to strengthen your modern slavery and AI supply chain governance.