Can AI change the way we manage our relationships with suppliers?

Introduction

Artificial intelligence (AI) is rapidly becoming an engine of innovation in procurement and supply chain management.

As companies face increasingly complex global supply chains, AI is already transforming procurement into a proactive, data-driven function.

At the same time, the term “AI” has become a marketing buzzword, often used misleadingly to exaggerate or misrepresent actual capabilities.

What is Artificial Intelligence?

Artificial intelligence refers to systems that use machine learning, natural language processing, image recognition, and predictive analytics to perform tasks that normally require human intelligence:

• Machine learning algorithms learn from historical procurement data to generate accurate forecasts (e.g., predicting fluctuations in raw material prices or supplier performance).
• Natural language processing enables software to read and interpret contracts, supplier emails, and unstructured documents.
• Image recognition can analyze invoices or certificates, while predictive algorithms anticipate market trends.

The status quo is costly: why procurement must evolve

In an environment where supply chains are becoming more complex more suppliers, stricter regulatory requirements, a strong need for traceability, and increased cost pressure procurement teams are seeking greater visibility, control, and agility.

Yet many organizations still operate with:

• Decentralized and non-standardized procurement processes.
• Suppliers tracked in scattered Excel files.
• Contracts stored in shared folders… when they are not lost.
• Manual compliance management, prone to oversight.

This setup blocks innovation and prevents the adoption and deployment of new automation and intelligence technologies.
It directly impacts procurement performance:

• lack of global visibility,
• quality, delivery, or compliance risks,
• missed negotiation opportunities,
• inability to drive procurement performance.

Procurement software like siembra.io, which natively integrates AI, helps address these challenges and strengthen procurement performance.

The impact of AI-powered software on procurement

Next-generation procurement platforms that combine data centralization, automation, and artificial intelligence allow organizations to solve long-standing structural issues: fragmented data, lack of visibility, heavy document management, supplier risks, and missed renegotiations.

It is within this context that AI becomes a major driver of modernization. It is transforming several key stages of the procurement cycle:

1️⃣ Automated creation and maintenance of a structured supplier panel

A unified and enriched supplier panel is the foundation of any modern procurement function. It enables teams to:

• centralize all supplier information (profiles, contacts, documents, certifications, performance),
• automatically enrich data with external sources (trade registries, financial data, quality indicators, press releases),
• detect inconsistencies or missing data,
• speed up information searches using NLP.

A centralized panel typically allows organizations to:

• save up to 50% of the time spent searching for supplier information,
• reduce up to 85% of regulatory risk through proactive document detection and automated collection.

2️⃣ AI-powered comparison of quotes and RFPs

Quote analysis is traditionally tedious, especially when:

• formats vary,
• units differ,
• options change from one supplier to another.

AI integrated into Siembra now makes it possible to:

• automatically extract quote line items,
• standardize data,
• compare options fairly,
• propose optimization scenarios.

3️⃣ Proactive contract management: alerts and opportunities

Most companies still suffer from unwanted contract renewals. AI solves this issue and goes even further by identifying reliable negotiation opportunities.

Digitizing contracts and applying AI enables companies to positively impact their financial margin:

• companies renegotiate 3× more contracts after digitalization,
• and avoid 100% of missed deadlines.

4️⃣ Automated document compliance

In highly regulated industries, procurement teams must manage:

• compliance analyses,
• quality attestations,
• regulatory documents (KBIS equivalents, ISO9001, industry-specific certifications…).

With AI, these documents are recognized, classified, analyzed, and checked automatically: the models detect critical fields, identify inconsistencies, flag missing documents, and trigger alerts for non-compliance.
AI also anticipates expirations and maintains continuous compliance without manual effort.

This leads to tangible results:

• 100% of documents are automatically verified (OCR),
• regulatory risk is cut in half,

For sectors where quality and traceability are essential, this is a major shift.

5️⃣ Supplier risk detection

New generations of AI models can combine:

• geopolitical signals,
• logistics risks,
• raw material volatility,
• financial stability indicators,
• climate or ESG data,
• news and weak signals.

Procurement, supply chain, and logistics teams are thus moving from a reactive model to a proactive one, strengthening operational performance.

Conclusion

The arrival of AI in procurement marks a profound transformation: centralized information, better contract control, simplified compliance, and accelerated decision-making.

This new generation of tools is redefining industry standards. Those who choose to modernize now benefit not only from immediate operational and financial gains but also from a long-term competitive advantage in their market.