AI in Procurement and Supply Chain: Are You Building on the Right Foundations?

The conversation around AI in procurement has shifted. It's no longer about whether the technology will change how supply chains operate, it already is. The question now is whether your organisation has the foundations in place to make it work.

The data reflects both the opportunity and the gap. According to EY's 2025 Global CPO Survey, 80% of procurement leaders plan to deploy generative AI within three years. Yet only 36% have meaningful implementations today, and a separate analysis found that just 4% of teams have moved beyond pilots to production-scale deployment.

That gap between ambition and execution is where most of the risk sits. And for many organisations, it's widening.

The data problem no one wants to talk about

Most procurement and supply chain functions weren't built with AI in mind. Data sits across multiple ERPs, spreadsheets and disconnected systems. Supplier records are inconsistent. Spend visibility is partial. Reporting relies on manual reconciliation.

This matters because AI is only as reliable as what sits underneath it. As one recent industry analysis put it plainly: fragmented data is the primary barrier to scaling AI in procurement. Without harmonised, contextual data across sourcing, contracting and purchasing systems, AI outputs remain narrow, untrusted and difficult to act on.

The organisations seeing the most value from AI aren't necessarily spending the most on technology. They're the ones that have invested in data governance, system discipline and reporting integrity first, and are now using AI to accelerate what already works.

If your organisation is exploring AI adoption without addressing underlying data quality, the risk isn't just poor outputs. It's governance exposure, compliance gaps and reduced confidence from the people who need to trust the results.

Capability is the other side of the equation

Technology investment alone won't close the gap. Workforce capability is increasingly what separates organisations that extract value from AI and those that don't.

Procurement and supply chain roles are changing rapidly. Traditional transactional work is being automated. The expectation now is that teams contribute through supplier risk analysis, commercial decision-making, data interpretation and operational improvement, areas where AI can assist, but where human judgment remains essential.

Research from Accenture found that 43% of employees identify clear, comprehensive training as the single most effective factor in building their confidence using AI tools. Yet many organisations are still treating AI adoption as a technology rollout rather than an organisational capability shift.

The businesses investing early in structured capability development, through education, controlled experimentation and cross-functional collaboration are building an advantage that compounds over time. Those waiting for the technology to mature before addressing the people side are likely to find adoption slower, more expensive and less effective when they do move.

Governance is non-negotiable

One of the more significant risks in AI adoption isn't the technology itself , it's the absence of governance around how it's being used.

In many organisations, employees are already using publicly available AI tools without clear policies, approved platforms or any oversight. Supplier data, contract terms, pricing strategies and procurement intelligence are being fed into consumer-grade tools with no controls around storage, confidentiality or outputs.

The organisations managing this well aren't restricting AI use, they're channelling it. They're defining approved platforms, establishing clear usage policies, and creating structured opportunities for teams to experiment with governance intact. This allows capability to develop without increasing exposure around commercially sensitive information.

Strong governance isn't a constraint on AI adoption. It's what makes adoption sustainable.

What this means for FY27 planning

For procurement and supply chain leaders, AI should be part of a broader operational strategy, not a standalone technology initiative. That means FY27 planning needs to include an honest assessment of:

• Data quality, governance and system integration maturity

• Workforce capability and readiness for AI-enabled ways of working

• Technology decisions that account for AI roadmaps and long-term scalability

• Governance frameworks that enable experimentation without increasing risk

• Practical use cases with clear business cases, rather than AI for its own sake

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Gartner has warned that 60% of supply chain digital adoption efforts will fail to deliver promised value by 2028, largely due to insufficient investment in change management. The organisations that get this right will be those that treat AI as an organisational challenge, not a software upgrade.

August Consulting works with procurement and supply chain leaders to assess operational readiness, strengthen data and governance foundations, and build the capability needed to adopt AI in a practical and sustainable way. If you're planning your FY27 approach and want an independent perspective, we'd welcome the conversation.