A great post on how AI in Supply Chain Management and Procurement becomes a competitive advantage:

AI automates, detects, calculates, predicts Humans judge, trust, sense, gauge, smell, taste There's a clear difference AI is already saving us loads of time And providing valuable insights But it... | Simon Frost | 30 comments

Note, Procurement teams are sitting on one of the most underutilized strategic assets in the enterprise: supplier RFQ cost breakdown data. Our recent research with 100 procurement and supply chain professionals revealed something fascinating:

📊 Most organizations are very good at collecting supplier cost data, but far fewer are turning that information into long-term cost intelligence.

Key findings from the research:
• 85% use cost breakdowns for negotiation and price validation
• 65% use them for benchmarking
• 45–50% use formal should-cost modeling
• Only 30% use them to drive broader strategic decisions

⚠️ In other words, procurement is still heavily tactical in many organizations.

What surprised me most was not the lack of effort, it was the lack of infrastructure. Many teams are still managing highly valuable supplier intelligence through:
• Disconnected (giant color-coded) excel spreadsheets
• PDFs
• Emails
• Manually maintained files

That makes it extremely difficult to:
• Reuse knowledge
• Scale insights
• Apply AI effectively

This is where the conversation around AI in procurement becomes very important.
🤖 AI absolutely has the potential to transform:
• Sourcing
• Cost modeling
• Supplier analysis
• Forecasting
• Risk management

But our research suggests something critical:
🚨 AI is the next multiplier, but data is the limiter.

Without:
• Structured data
• Connected systems
• Standardized workflows
• Centralized repositories

AI often amplifies inconsistency rather than intelligence.

The organizations making the biggest progress are the ones moving beyond one-time RFQs and toward integrated cost intelligence systems that connect:
• Supplier quotes
• ERP data
• Engineering inputs
• Contracts
• Analytics
…into a continuous decision-support capability.

📈 That shift, from tactical quoting to strategic cost intelligence, may become one of the defining procurement transformations of the next decade.

Our research:

One of the clearest findings from our RFQ Cost Intelligence Research is that procurement leaders are very optimistic about AI, but most orgs still need to build the foundation required to use it effectively. Over 70% of the 100+ pros we surveyed identified AI-driven cost analysis as the next major frontier. At the same time, they pointed to significant barriers including data fragmentation, lack of a central repository, poor system integration, and governance challenges. The message was clear: AI has tremendous potential, but it can only amplify what already exists. If supplier cost data is scattered across spreadsheets, PDFs, and email attachments (which was almost everyone), even the most sophisticated AI tools will struggle to deliver meaningful insights (hallucinations).

In short, AI is the next multiplier, but data is the limiter. AI does not replace the need for clean, structured, and connected data. Instead, it magnifies the value of the info & processes already in place. Orgs that build a strong data foundation will be able to use AI to accelerate cost analysis, improve negotiations, identify risks, & uncover new sourcing opportunities.

Warning: Without clean, structured, and connected cost data, AI will make mistakes.

From Visual Capitalist — The 10 Biggest Challenges Companies Face Right Now: https://lnkd.in/gwgJPJK2. At first glance, this looks like a general business leadership chart. But, almost every challenge listed is fundamentally a supply chain management problem. I will use it in class to show the students how SCM impacts everything & how SCM is impacted by everything. You could also say SCM actually owns most corporate problems. The one that stands out to me based on my current research is that AI will expose weak supply chains. Why?

Because AI depends on:
• clean data
• standardized workflows
• connected systems
• centralized repositories
• process discipline

Most supply chains still operate through fragmented spreadsheets, emails, tribal knowledge, disconnected ERP data, and inconsistent supplier information.

That creates a major problem: AI can automate bad processes just as fast as good ones. In procurement specifically, many organizations still treat RFQs and supplier cost breakdowns as one-time negotiation events instead of long-term strategic cost intelligence assets. Without strong SCM infrastructure, AI risks generating more noise than insight. The companies that fix their supply chain data foundations first will likely gain the biggest AI advantage.

In other words, many organizations recognize the potential of AI, but still need the underlying data foundation and infrastructure to use it effectively.

That is why I have decided to go through APD’s Advanced AI Certification Program myself. Back to school for me. They are also helping me develop this content for our students. Thank you APD!

I want to better understand how procurement teams can move beyond simply experimenting with AI and begin implementing practical, high-ROI applications in areas such as RFQ comparison, supplier discovery, negotiation support, and contract analysis.

The procurement profession is evolving quickly, and I believe those of us involved in teaching, research, and practice need to continue learning alongside industry.

AI may be the next multiplier, but data remains the limiter (for certain in the SCM space).

If you work in procurement or supply chain and are trying to understand where AI is headed, this looks like a very practical and timely program.

See you there:
https://lnkd.in/gWkKrEU2

Sime (Sheema) Curkovic, Ph.D.

Professor, Operations/Supply Chain | Lee Honors College Faculty Fellow

Western Michigan University | Haworth College of Business

Kalamazoo, MI 49008 | 269.267.3093 | Room 3246

sime.curkovic@wmich.edu | www.wmich.edu/supplychain

Because AI depends on:
• clean data
• standardized workflows
• connected systems
• centralized repositories
• process discipline

Most supply chains still operate through fragmented spreadsheets, emails, tribal knowledge, disconnected ERP data, and inconsistent supplier information.

That creates a major problem: AI can automate bad processes just as fast as good ones. In procurement specifically, many organizations still treat RFQs and supplier cost breakdowns as one-time negotiation events instead of long-term strategic cost intelligence assets. Without strong SCM infrastructure, AI risks generating more noise than insight. The companies that fix their supply chain data foundations first will likely gain the biggest AI advantage.

In our recent survey of 100 SCM pros, over 70% identified AI-driven cost analysis as the next major frontier. But the research also showed most organizations are not fully prepared to leverage AI effectively.

Common barriers included: • Data fragmentation across Excel files, PDFs, and emails (80%) • No central repository for supplier cost intelligence (65%) • Poor ERP/system integration (60%) • Governance and data quality challenges (40%)

In other words, AI may be the next multiplier, but data is still the limiter, especially in SCM.

Most firms are still very tactical: • 85% use RFQ cost breakdowns for negotiation • Only 30% use them for broader strategic decision-making

Also excited to be going through APD’s Advanced AI Certification Program myself as we continue building this content. If you work in procurement and want to better understand where AI is heading in sourcing and cost intelligence, this looks like a very practical program:
https://lnkd.in/gWkKrEU2

Our research:

More SCM talking points from the first list for my students:

• Changing customer expectations?
That means faster fulfillment, better forecasting, shorter lead times, and higher service levels.

• Transforming the business model?
That usually requires redesigning supplier networks, technology systems, procurement processes, logistics flows, and inventory strategies.

• Competition from new entrants?
Supply chain agility often determines who wins. Companies that move faster operationally can disrupt entire industries.

• Hybrid work?
This impacts global coordination, planning visibility, supplier collaboration, and operational communication.

• Accelerated growth?
Growth breaks weak supply chains very quickly. Scaling operations, suppliers, transportation, and production capacity is one of the hardest things companies do.

• International expansion?
That is literally global supply chain management, sourcing, trade compliance, tariffs, logistics, risk management, and localization.

• Talent acquisition and retention?
Supply chain is facing a massive demographic shift with experienced professionals retiring faster than replacements are entering the field.

• Market disruption?
Pandemics, tariffs, geopolitical risk, AI, commodity volatility, port strikes, and supplier instability are all supply chain issues.

• Post merger integration?
One of the biggest challenges after acquisitions is integrating ERP systems, supplier bases, inventory policies, procurement processes, and distribution networks.

Even “CEO transition” often becomes a supply chain challenge because leadership changes frequently reshape sourcing strategies, operational priorities, capital investments, and network footprints. In many organizations, supply chain is no longer just a support function. It is becoming the operating system of the business. The companies that manage supply chains strategically will likely outperform those that still view SCM as simply purchasing, shipping, and inventory control.

Buckle up.

Sime (Sheema) Curkovic, Ph.D.

Professor, Operations/Supply Chain | Lee Honors College Faculty Fellow

Western Michigan University | Haworth College of Business

Kalamazoo, MI 49008 | 269.267.3093 | Room 3246

sime.curkovic@wmich.edu | www.wmich.edu/supplychain