Artificial intelligence is gaining ground in procurement, supplier risk and sustainability management, but most organisations remain in the early stages of adoption, according to new sector-specific findings released by global supply chain risk and performance management company Achilles.
The findings form part of Achilles’ latest supply chain risk and sustainability survey, which collected responses from 2,805 organisations across Australia, Brazil, France, Germany, Italy, the Middle East, Norway, Spain, Sweden and the UK.
Among organisations responding to questions on AI adoption, 37% are already piloting, operationalising or widely deploying AI across procurement, supplier risk or sustainability activities. However, only 2% said AI is widely deployed or fully integrated across their organisation, highlighting the significant gap between experimentation and mature implementation.
The findings suggest that AI is moving from theory into practical applications, with organisations using the technology to improve efficiency, reduce manual workloads and strengthen decision-making. At the same time, adoption remains constrained by challenges around data quality, skills, systems integration and organisational readiness.
IT and Marine Transport Lead AI Adoption
AI adoption varies considerably across sectors. Among sectors with at least 25 respondents, Information Technology leads active adoption at 62%, 24 percentage points above the overall rate of 37%.
Marine Transport follows at 56%, while Ground Transport recorded the lowest adoption rate among the larger sectors at 26%. This represents a 36 percentage-point gap between the highest and lowest adopting sectors.
The most common applications are focused on practical operational needs, including process automation, virtual assistants and chatbots, supplier management and risk mitigation.
Organisations also report tangible operational benefits, particularly improved process efficiency, reduced repetitive work for employees and better decision-making based on data.
Skills and Data Remain Major Barriers
Despite growing interest, organisations continue to face significant barriers to scaling AI. These include shortages of internal AI and data science skills, difficulties integrating AI with legacy and ERP systems, poor or unclean data, and the fact that AI has not yet become a strategic priority for some organisations.
Overall sentiment towards AI remains positive. Forty-five percent of organisations have a favourable view of AI in procurement, compared with just 7% holding a negative view.
Adam Whitfield, Head of Global Compliance and ESG at Achilles, said the focus is increasingly shifting from whether organisations should adopt AI to how they can implement it effectively.
“AI is no longer a talking point in procurement; it is being put to work,” Whitfield said, noting that more than a third of surveyed organisations are already piloting or using AI in supplier risk and sustainability.
He cautioned that AI can only deliver meaningful value when supported by trusted data, clear governance and integration with existing procurement processes.
Data Quality Critical to AI Success
Achilles said increased AI adoption does not remove the need for fundamental supplier risk management practices. Reliable supplier data collection, validation and continuous monitoring remain essential to ensuring AI-generated insights are accurate and actionable.
While AI can analyse large volumes of information and identify potential risks, it cannot compensate for incomplete or inaccurate supplier data. Human expertise also remains necessary to interpret findings and investigate emerging risks.
The importance of these foundations is underscored by Achilles’ wider research, which found that only 6% of organisations have full visibility beyond their Tier 1 suppliers.
As companies seek to scale AI across procurement and supply chain functions, the quality of supplier data is therefore expected to become increasingly important. Applying AI to incomplete or inconsistent information could amplify existing blind spots rather than eliminate them.
Achilles said organisations that combine AI with robust supplier validation, reliable sustainability data and continuous monitoring will be better positioned to improve supply chain visibility, resilience and risk management.