Industry challenges highlighted by respondents include increasing regulatory complexity, sourcing volatility and lack of data integration across key supply chain functions
Inspectorio, provider of the leading AI-powered platform for quality, compliance, sustainability, and traceability, announced the release of its State of Supply Chain Report 2026, which details the impact of AI across the supply chain and the gaps that hinder many brands and retailers from realizing its full potential.
The survey results, based on responses from nearly 200 retailer and brand professionals across the global supply chain and augmented by research interviews with industry executives, highlighted challenges and opportunities in traceability, sustainability, product integrity and compliance. Several of the many key findings are highlighted below.
Stress of managing compliance ranks as 4 on a 5-point scale
Regulatory compliance is creating unprecedented organizational stress; more than half of respondents ranked the strain of executing on compliance requirements as “4” on a 5-point scale. Making matters worse, compliance budgets have plateaued, even as regulatory requirements continue to grow. Only 50% of survey respondents reported that their 2026 compliance budgets increased, compared to 75% in 2025. In addition:
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- Audit fatigue is straining strategic relationships. Suppliers are managing overlapping, inconsistent audit requirements from multiple customers and regulators simultaneously. Without a multi-tiered, interdisciplinary approach to compliance, supplier goodwill and capacity are being consumed by duplicate effort.
- Measurement systems aren’t built for product-level proof. Emerging regulations, particularly the EU Digital Product Passport (DPP), require that data is traceable to specific products, materials and transactions. The gap between how data is currently structured and what regulators will require is significant — and most organizations have not yet closed it.
AI faces organizational hurdles, but best-in-class brands are seeing strong ROI
The primary obstacles to effective AI adoption are insufficient data quality, change management gaps and lack of cross-functional integration. Organizations are deploying AI onto fragmented data environments and expecting transformative results. The research shows this consistently does not work.
The organizations reporting the strongest AI outcomes share a common characteristic: they are unifying their production chain data — quality, compliance, sourcing and sustainability — before scaling AI applications on top of it. Examples include:
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- A global manufacturer reduced corrective-action administrative burden by roughly 60%, avoiding an estimated $2.46M per year in handling effort, while faster closure reduced open-issue exposure by approximately $1.96M per year.
- A Factory Risk Prediction deployment also enabled lower-risk suppliers to shift toward self-inspection, saving $4.8M through reduced third-party inspection bookings.
Sourcing diversification erodes progress in sustainability
37% of respondents shifted sourcing to new countries or regions in response to tariffs. The survey also revealed that 37% of respondents added secondary suppliers for critical products and 33% renegotiated supplier pricing or terms.
However, every time production moves to a new supplier, the sustainability infrastructure built at the prior location — supplier assessments, environmental audits, chemical compliance history, labor certifications — is left behind. Organizations are making sourcing decisions based on trade economics without accounting for the compliance cost of starting over in a new geography, with significant negative impact.
Traceability is seen as a regulatory requirement, not a competitive advantage
Only 21% of organizations have a multi-tier strategy for traceability; 79% are reactive to regulatory requirements. The majority of respondents allow their traceability strategy to be driven by regional directives, meaning traceability programs are scoped to what is currently required rather than taking a proactive approach with potential supplementary benefits related to supply chain visibility and resilience.
“AI investment is only productive if the underlying production chain data is reliable, structured and unified,” said Chirag Patel, CEO, Inspectorio. “Inspectorio’s latest research underscores the challenges that brands and retailers face across key supply chain disciplines. It also displays a path forward by showcasing how leading companies are utilizing best-in-class strategies and technology to reap the benefits of AI in product integrity, sustainability, traceability and compliance.”
