Regulatory complexity tests the next phase of supply chain AI
Artificial intelligence is becoming an operational response to regulatory complexity in British supply chains. More than a quarter of UK supply chain professionals say the need to manage rules across global markets is the single biggest reason their organisations are accelerating AI use in supply chain decisions. IDC conducted the research for Kinaxis.
Only inflation ranks higher among the drivers identified in the UK. The regulatory share is well above the 16% global average and substantially higher than Germany’s 10%. The difference may be linked to the additional requirements that British companies have faced since the UK formally left the European Union in 2020.
From automation to adaptive operations
For industrial organisations, the attraction of AI is practical. Systems can help teams interpret changing requirements, assess alternatives and make decisions more quickly across planning, procurement and logistics. That capability may strengthen resilience when supply networks span jurisdictions with different rules. It does not, however, remove the need for skilled oversight: poor data or opaque recommendations can introduce new operational risk.
The global IDC InfoBrief “Making Supply Chain AI Accountable” surveyed more than 2,000 supply chain leaders in nine markets. It found that only 2% of organisations have no AI capabilities at all. Yet the maturity of adoption remains uneven. Just 12% of respondents call their organisation an AI leader, while only 12% say governance for AI-driven decisions is fully embedded.
Accountability must travel with autonomy
Trust is the main brake on wider adoption, cited by 52% of respondents worldwide. As organisations give software greater influence over purchasing, production or distribution decisions, explainability and auditability become part of resilience planning. Justin King, Field CTO at Kinaxis, said the key test is whether AI can deliver trusted, measurable and governed autonomy. He identified Maestro as an example of a platform intended to make recommendations explainable and auditable before they are acted upon.
The UK has also identified a confidence gap. Nearly 23% of British companies describe their AI maturity as early-stage or uncertain, compared with 16% in the United States and India. For Industry 5.0 strategies, the implication is clear: automation should augment accountable human decision-making rather than operate as an unexamined layer. Companies that combine AI with robust governance will be better placed to absorb regulatory change without sacrificing control.
