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Hermès, SentinelOne, Chubb Push Procurement Execution Forward with Agentic Tools

  • Writer: Charles Weber
    Charles Weber
  • 4 days ago
  • 3 min read

Procurement teams at manufacturers and large operators face mounting pressure from slow requisition cycles, sourcing delays and compliance complexity that inflate costs and tie up capital. These execution gaps have grown more acute as organizations scale spend management across fragmented systems and supplier networks.


Operational Bottlenecks in Spend Management

Visibility into transactions exists but often fails to translate into faster decisions at the point of execution. Dock scheduling, exception handling and supplier coordination remain pain points that agentic tools aim to address.


Leagh Turner, CEO of Coupa, replied to an inquiry from The Supply Chainer in writing. "The future of agentic trade is not individual assistants operating independently, but rather, as orchestrated systems of intelligence capable of supporting larger business processes. Compose is Coupa's answer to that agentic future. One of the biggest barriers to AI adoption is integration debt. By unifying enterprise-wide agentic AI into a single, unified architecture, Coupa is uniquely capable of taking that debt off our customers' plates by providing a single solution for all of their spend management needs. And we are helping them drive real AI value faster through Catalyst, a transformational services offering delivered by forward-deployed engineers that rapidly prototypes how organizations can move from AI potential to operational reality. This approach builds on Coupa's $10 trillion dataset and community network to deliver measurable outcomes such as up to 50% reduction in requisition cycle times."


AI Adoption Meets Real-World Friction

Early results from customers like Votorantim show agents closing deals with minimal touch. Yet broader challenges persist around data quality and integration at enterprise scale.

Leagh Turner of Coupa continued in the response to The Supply Chainer. "With Coupa's end-to-end platform today, organizations save an average of $30 million to $40 million per billion dollars in managed spend. Over the past 20 years, Coupa's platform has delivered customers more than $320B in savings. Now, with agentic AI orchestrated across the enterprise, Coupa expects organizations to potentially double those outcomes, likely achieving $60 million to $80 million in savings per billion of spend. During the first quarter, over $500B in total spend flowed through the platform, expanding Coupa's proprietary dataset. Collectively, its autonomous spend management platform generated $16 billion in cumulative lifetime savings for the Coupa community in Q1 alone."


Hermès bag. Luxury goods procurement streamlined through agentic AI on Coupa platform reducing sourcing cycle times
Hermès bag. Luxury goods procurement streamlined through agentic AI on Coupa platform reducing sourcing cycle times

Kristian O’Meara, Chief Commercial Officer at Pairsoft, provided a response to The Supply Chainer on related issues. "The next opportunity for AI in source-to-pay isn't just automation—it's decision support. Organizations are applying AI to supplier onboarding, visibility, and exception management, helping procurement teams identify risks and make faster decisions. With growing volumes of supplier and transaction data, AI can highlight compliance concerns before they become larger issues. As ESG requirements and cross-border regulations expand, manual processes simply don't scale."


Industry estimates from Coupa research indicate supply disruptions cost organizations an average of $16 million annually. Hermès, SentinelOne and Chubb are among organizations expanding use of these capabilities.


Savings Potential and Scale Challenges

The shift toward agentic systems reflects operators seeking to close execution gaps beyond basic visibility. Success depends on addressing foundational data issues and workflow friction that persist in many procurement operations. Forward-looking implications point to orchestration layers becoming central as AI moves deeper into daily spend decisions.


 
 
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