How AI and Orchestration Bridge Procurement–Supply Chain Divide
Executives increasingly talk about resilience, quality compliance and sustainability as the new standards for success.
Procurement chiefs and supply chain leaders are, for once, pursuing the same targets. Yet, the daily work of meeting those goals tells a different story.
A new study from North Carolina State University (NCSU) and GEP, based on insights from 250 senior leaders across North America, Europe and Asia-Pacific, reveals a troubling pattern: Shared strategy often collapses when it comes to execution.
Where Misalignment Hurts
On paper, the functions converge. In practice, their workflows often pull apart. Contracting lags, suppliers pass along costs that aren’t always justified, and risk assessments arrive late in the cycle. Leaders in the study called out workflow inefficiency as the clearest red flag; 67.8% of respondents flagged it as a top concern.
Each delay slows the business down, adding costs and undermining resilience at the moment organizations say it matters most.
This isn’t only about wasted time. Misalignment creates vulnerabilities that ripple across the enterprise.
Procurement negotiates in one lane while supply chain adjusts inventory in another, with neither working from the same set of numbers. The result is inconsistent decisions, fractured risk responses, and weakened supplier relationships.
What Orchestration Delivers
Orchestration addresses this problem at the root. Orchestration addresses this problem at the root by unifying planning and execution.
When procurement and supply chain are orchestrated, sourcing decisions, supplier actions, logistics flows, and risk signals all feed into one operating model.
Leaders who have begun adopting orchestration report benefits in three areas: faster workflows, stronger resilience, and measurable cost control.
Consider how this looks in practice. Supplier contracts close faster when both functions share the same data. Risk alerts travel further, reaching procurement and supply chain teams simultaneously. Inventory decisions are made with a full view of financial impact.
Each link strengthens the next, reducing waste and reinforcing resilience across the value chain.
Why AI Is Critical
The study highlights how executives increasingly see AI as the top enabler for integration between procurement and supply chain. It can sift through vast data sets, spot patterns, and surface risks long before they escalate. It also models scenarios and suggests responses in real time, keeping teams coordinated even as conditions change.
Adoption is advancing fastest in areas where complexity overwhelms traditional processes: supplier management, risk forecasting, and demand planning.
Here, AI cuts through noise and gives leaders a shared, fact-based view . That common view is what enables orchestration to shift from coordination to integration.
Data Spotlight
Survey findings show where CPOs and CSCOs align most strongly:
These numbers reveal a clear shift. Traditional cost-first thinking is giving way to priorities that emphasize resilience, quality, and continuity.
A Practical Roadmap
The NCSU–GEP study offers three steps that organizations can use to close these divides and scale orchestration:
Taken together, these steps can embed orchestration into daily operations, replacing fragmented efforts with coordinated execution and making resilience measurable.
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Sales & Business Development Leader | ₹500 Million+ Revenue | 100+ Logos | Client Retention Champion | Cross-Sell | Upsell | Growth Strategist
3dGreat read…Interesting to see AI moving from just efficiency to real decision-making support. Curious to see how these insights can be applied to transportation and logistics services enablement’s ..
The divide between procurement and supply chain isn’t just operational, it’s architectural. Too often, strategy is shared at the top, but execution fractures downstream. That’s why orchestration powered by AI matters. It doesn’t just speed up workflows, it creates a shared reality where procurement and supply chain operate from the same numbers, same risk signals and same priorities. At Dextra Labs, we’re seeing the biggest wins come when enterprises build: ✅ A joint decision architecture that keeps AI outputs explainable ✅ A unified KPI layer that blends cost + resilience + compliance ✅ Governance loops so automation earns trust, not resistance Orchestration is no longer optional. In a volatile world, it’s the only way to align resilience with cost discipline. Curious- which is the bigger challenge you see in your org: - Unifying data & KPIs, or - Embedding governance into AI workflows?