The rise of intelligent procurement
How AI is reshaping supplier selection, RFPs, and negotiation
Procurement is being asked to do more than ever.
Reduce costs. Protect continuity. Improve resilience. Move faster. Deliver better insight. Support growth. Manage risk.
And now, on top of all that, there’s another expectation: embrace artificial intelligence (AI).
The pressure is real. According to The Hackett Group’s 2026 Procurement Key Issues Study, procurement workloads are expected to rise by eight percent this year, even as headcount and operating budgets decline. At the same time, deploying AI-enabled technology has become one of procurement’s top strategic priorities.[1]
For leaders across pharmaceutical and regulated manufacturing supply chains, the question is no longer whether procurement will become more digital. It already has.
The real question is what intelligent procurement looks like in practice — and where human judgment still matters most.
When people talk about AI transforming procurement, it can sound like a sudden revolution. In reality, the shift has been happening for years.
World Courier has seen this evolution first-hand through hundreds of sourcing processes and customer tenders. One of the biggest changes has been the widespread adoption of online procurement platforms, replacing many of the email-based and manual tender processes that were once standard.
Around a decade ago, only an estimated 10 – 15 percent of tenders were managed through digital platforms. Most arrived by email and some remained entirely manual.
In one particularly traditional tender process, every document had to be printed, bound, and returned physically despite the digital tools already available. It serves as a reminder of how quickly procurement practices have evolved.
Today, an estimated 50 – 60 percent of tenders are managed through online procurement systems.
That matters because digital procurement creates the foundation for intelligent procurement.
Before AI can analyze suppliers, compare bids, or identify risk, procurement processes need structured data, consistent workflows, and systems capable of handling complexity at scale.[2]
The case for AI in procurement has moved beyond theory. It's now operational.
Modern sourcing teams are often managing vast amounts of information across multiple stakeholders, geographies, suppliers, and decision criteria. In highly regulated sectors, they may also need to review compliance documentation, legal terms, service levels, quality commitments, and audit requirements alongside pricing.
That creates a simple challenge: too much data for manual processes.
The scale of modern procurement illustrates why this change is important.
Because World Courier supports complex international logistics programs, some pricing templates contain around 2,000 shipment lanes or pricing lines. Reviewing submissions across multiple suppliers can therefore involve comparing tens of thousands of individual data points — exactly the kind of repetitive analysis that AI is well suited to support.
This is where AI and automation can create immediate value.
A well-designed system can compare thousands of data points in seconds, normalize inconsistent submissions, highlight outliers, rank options against agreed criteria, and give procurement teams a faster route to shortlist decisions.
The potential efficiency gains are significant, particularly when AI is used to automate repetitive analysis and accelerate evaluation.
The Hackett Group’s latest research supports that direction of travel. 80% of respondents said AI-enabled technology will have a transformational impact on procurement over the next five years.[3]
Deloitte’s survey of senior procurement leaders also found leading procurement teams are increasing investment in technology and digital capability to improve resilience, efficiency, and decision-making.[2]
This is where the conversation needs nuance.
There is a difference between using AI to support decisions and allowing AI to make them. In regulated supply chains, that distinction matters.
Price is only one part of supplier selection. Procurement leaders may also need to assess service reliability, compliance maturity, operational resilience, escalation capability, quality systems, data integrity, geographic coverage, and performance under pressure.
Those factors do not always fit neatly into a spreadsheet.
Experience across complex procurement programs suggests AI can strengthen evaluation without replacing accountability.
AI can make evaluation faster and more consistent, but final supplier decisions still require human judgment, particularly where compliance, resilience and operational risk are involved.
That view aligns with the regulatory direction of travel across Europe and other major markets, where expectations around governance, auditability, human oversight, and explainability are increasing for digital systems used in critical environments.[5]
The EU AI Act, for example, sets out requirements around risk management, documentation, transparency, human oversight, and system robustness for higher-risk use cases.[6]
In other words: procurement can automate analysis, but responsibility still sits with people.
One of the risks of over-automated procurement is false confidence.
If a system is weighted too heavily toward price, the cheapest option can appear to be the best option — even when the real commercial risk sits elsewhere.
This matters in logistics, where service failure can trigger delays, missed production schedules, compliance exposure, customer disruption, or product loss.
Every procurement team would like to secure premium service at the lowest possible cost. In practice, however, the cheapest option rarely represents the lowest overall commercial risk.
The strongest procurement teams understand that lowest price and best value are not the same thing.
Intelligent procurement should help organizations compare total value more effectively — not simply compress supplier choice into a race to the bottom.
There’s another reason human judgment remains essential: systems are only as good as their design.
Even sophisticated digital tools can create friction when data formats are inconsistent, workflows are rigid, or users are forced into processes that do not reflect reality.
During one complex global tender managed by World Courier, a pricing upload generated more than 6,600 errors because of hidden decimal-place formatting issues. The deadline had to be extended while the problem was investigated and corrected.
The experience is a useful reminder.
Software may enable procurement transformation. Lasting impact however comes from complementing it with practical processes, clean data structures, sensible controls, and user experiences that help people make better decisions.
Without that, digital complexity simply replaces manual complexity.
As many organizations are discovering, successful adoption depends as much on data quality, governance, and capability as it does on the technology itself.[7]
As automation takes on more repetitive work, procurement’s value should move upwards.
Less time spent cleansing spreadsheets or manually comparing bids. More time spent advising stakeholders, shaping sourcing strategies, managing supplier risk, and building resilient partner ecosystems.
That shift is already visible in industry priorities. The Hackett Group found that procurement teams increasingly see their role as strategic advisors to the business, while supply continuity, agility, analytics, and resilience remain central priorities.[1]
For procurement leaders, the opportunity is significant.
Used well, AI can free teams from low-value administration and give them better evidence for higher-value decisions.
Used badly, it can create faster mistakes.
Research from the Chartered Institute of Procurement & Supply found that while 78% of procurement professionals expect AI to enhance automation, only 30% feel professionally prepared for its impact — highlighting the importance of skills, governance, and change management alongside technology investment.[8]
The future of procurement is unlikely to be fully autonomous.
It is more likely to be intelligent, assisted, and accountable.
Algorithms will help surface options. Systems will reduce friction. Analytics will strengthen negotiation positions. Automation will accelerate cycle times.
But in complex, regulated supply chains, people will still be needed to challenge assumptions, interpret nuance, weigh risk, and make the final call.
That is not a limitation of AI.
It’s what good procurement looks like.
Reduce costs. Protect continuity. Improve resilience. Move faster. Deliver better insight. Support growth. Manage risk.
And now, on top of all that, there’s another expectation: embrace artificial intelligence (AI).
The pressure is real. According to The Hackett Group’s 2026 Procurement Key Issues Study, procurement workloads are expected to rise by eight percent this year, even as headcount and operating budgets decline. At the same time, deploying AI-enabled technology has become one of procurement’s top strategic priorities.[1]
For leaders across pharmaceutical and regulated manufacturing supply chains, the question is no longer whether procurement will become more digital. It already has.
The real question is what intelligent procurement looks like in practice — and where human judgment still matters most.
Procurement has already changed more than many realize
When people talk about AI transforming procurement, it can sound like a sudden revolution. In reality, the shift has been happening for years.
World Courier has seen this evolution first-hand through hundreds of sourcing processes and customer tenders. One of the biggest changes has been the widespread adoption of online procurement platforms, replacing many of the email-based and manual tender processes that were once standard.
Around a decade ago, only an estimated 10 – 15 percent of tenders were managed through digital platforms. Most arrived by email and some remained entirely manual.
In one particularly traditional tender process, every document had to be printed, bound, and returned physically despite the digital tools already available. It serves as a reminder of how quickly procurement practices have evolved.
Today, an estimated 50 – 60 percent of tenders are managed through online procurement systems.
That matters because digital procurement creates the foundation for intelligent procurement.
Before AI can analyze suppliers, compare bids, or identify risk, procurement processes need structured data, consistent workflows, and systems capable of handling complexity at scale.[2]
Why AI is arriving now
The case for AI in procurement has moved beyond theory. It's now operational.
Modern sourcing teams are often managing vast amounts of information across multiple stakeholders, geographies, suppliers, and decision criteria. In highly regulated sectors, they may also need to review compliance documentation, legal terms, service levels, quality commitments, and audit requirements alongside pricing.
That creates a simple challenge: too much data for manual processes.
The scale of modern procurement illustrates why this change is important.
Because World Courier supports complex international logistics programs, some pricing templates contain around 2,000 shipment lanes or pricing lines. Reviewing submissions across multiple suppliers can therefore involve comparing tens of thousands of individual data points — exactly the kind of repetitive analysis that AI is well suited to support.
This is where AI and automation can create immediate value.
A well-designed system can compare thousands of data points in seconds, normalize inconsistent submissions, highlight outliers, rank options against agreed criteria, and give procurement teams a faster route to shortlist decisions.
The potential efficiency gains are significant, particularly when AI is used to automate repetitive analysis and accelerate evaluation.
The Hackett Group’s latest research supports that direction of travel. 80% of respondents said AI-enabled technology will have a transformational impact on procurement over the next five years.[3]
Deloitte’s survey of senior procurement leaders also found leading procurement teams are increasing investment in technology and digital capability to improve resilience, efficiency, and decision-making.[2]
Where intelligent procurement is already showing up
In many organizations, intelligent procurement is not one big system replacing everything. It’s a series of targeted improvements across the sourcing lifecycle.
That can include:
- Automated supplier discovery and market scanning
- Bid-sheet comparison and scoring
- Contract review and clause analysis
- Spend analytics and forecasting
- Risk flagging and exception management
- Guided negotiation preparation
- Faster intake and triage of sourcing requests
Some procurement platforms now support live bidding environments, where suppliers can submit pricing, see how they rank against competitors in real time, and choose whether to improve their offer before the bidding window closes.
For buyers, that can accelerate competitive pricing events. For suppliers, it raises the bar for responsiveness, pricing discipline, and commercial strategy.
Large organizations are already embedding these processes into digital sourcing environments. For example, Novartis publicly states its sourcing platforms support RFIs, RFPs, and eAuctions through SAP Ariba.[4]
But procurement decisions cannot be fully automated
This is where the conversation needs nuance.
There is a difference between using AI to support decisions and allowing AI to make them. In regulated supply chains, that distinction matters.
Price is only one part of supplier selection. Procurement leaders may also need to assess service reliability, compliance maturity, operational resilience, escalation capability, quality systems, data integrity, geographic coverage, and performance under pressure.
Those factors do not always fit neatly into a spreadsheet.
Experience across complex procurement programs suggests AI can strengthen evaluation without replacing accountability.
AI can make evaluation faster and more consistent, but final supplier decisions still require human judgment, particularly where compliance, resilience and operational risk are involved.
That view aligns with the regulatory direction of travel across Europe and other major markets, where expectations around governance, auditability, human oversight, and explainability are increasing for digital systems used in critical environments.[5]
The EU AI Act, for example, sets out requirements around risk management, documentation, transparency, human oversight, and system robustness for higher-risk use cases.[6]
In other words: procurement can automate analysis, but responsibility still sits with people.
Why lowest price can become the highest cost
One of the risks of over-automated procurement is false confidence.
If a system is weighted too heavily toward price, the cheapest option can appear to be the best option — even when the real commercial risk sits elsewhere.
This matters in logistics, where service failure can trigger delays, missed production schedules, compliance exposure, customer disruption, or product loss.
Every procurement team would like to secure premium service at the lowest possible cost. In practice, however, the cheapest option rarely represents the lowest overall commercial risk.
The strongest procurement teams understand that lowest price and best value are not the same thing.
Intelligent procurement should help organizations compare total value more effectively — not simply compress supplier choice into a race to the bottom.
Technology still needs human design
There’s another reason human judgment remains essential: systems are only as good as their design.
Even sophisticated digital tools can create friction when data formats are inconsistent, workflows are rigid, or users are forced into processes that do not reflect reality.
During one complex global tender managed by World Courier, a pricing upload generated more than 6,600 errors because of hidden decimal-place formatting issues. The deadline had to be extended while the problem was investigated and corrected.
The experience is a useful reminder.
Software may enable procurement transformation. Lasting impact however comes from complementing it with practical processes, clean data structures, sensible controls, and user experiences that help people make better decisions.
Without that, digital complexity simply replaces manual complexity.
As many organizations are discovering, successful adoption depends as much on data quality, governance, and capability as it does on the technology itself.[7]
The future role of procurement becomes more strategic
As automation takes on more repetitive work, procurement’s value should move upwards.
Less time spent cleansing spreadsheets or manually comparing bids. More time spent advising stakeholders, shaping sourcing strategies, managing supplier risk, and building resilient partner ecosystems.
That shift is already visible in industry priorities. The Hackett Group found that procurement teams increasingly see their role as strategic advisors to the business, while supply continuity, agility, analytics, and resilience remain central priorities.[1]
For procurement leaders, the opportunity is significant.
Used well, AI can free teams from low-value administration and give them better evidence for higher-value decisions.
Used badly, it can create faster mistakes.
Research from the Chartered Institute of Procurement & Supply found that while 78% of procurement professionals expect AI to enhance automation, only 30% feel professionally prepared for its impact — highlighting the importance of skills, governance, and change management alongside technology investment.[8]
Smarter decisions, not absent decision-makers
The future of procurement is unlikely to be fully autonomous.
It is more likely to be intelligent, assisted, and accountable.
Algorithms will help surface options. Systems will reduce friction. Analytics will strengthen negotiation positions. Automation will accelerate cycle times.
But in complex, regulated supply chains, people will still be needed to challenge assumptions, interpret nuance, weigh risk, and make the final call.
That is not a limitation of AI.
It’s what good procurement looks like.
References
- The Hackett Group. 2026 Procurement Key Issues Study: The Agentic Enterprise – AI’s Real Progress in Procurement. January 2026.
- Deloitte. 2025 Global Chief Procurement Officer Survey. Procurement digitization, investment trends, and operating model evolution. https://www.deloitte.com/us/en/about/press-room/2025-chief-procurement-officer-survey.html
- The Hackett Group. Procurement trends with transformational impact. AI-enabled technology findings. https://www.thehackettgroup.com/the-hackett-group-procurement-leaders-say-ai-will-transform-their-jobs/
- Novartis. Supplier Portal: Sourcing and Procurement. Public sourcing platform example including RFIs, RFPs, and eAuctions. https://www.novartis.com/supplier-portal/sourcing-and-procurement
- European Commission. EU Guidelines on Good Distribution Practice of medicinal products for human use (2013); EU GMP Chapter 7; Annex 11 Computerised Systems. https://www.pharmagdp.com/wp-content/uploads/2022/06/EU-GDP-Guidelines-of-5-November-2013-on-Good-Distribution-Practice-of-medicinal-products-for-human-use-2013_C-343_01.pdf
- European Union. Regulation (EU) 2024/1689 (EU AI Act). Risk management, transparency, human oversight, and governance requirements. https://eur-lex.europa.eu/eli/reg/2024/1689/oj/eng
- McKinsey & Company; Deloitte; The Hackett Group. Research on adoption barriers including data quality, governance, and organizational readiness. https://www.mckinsey.com/capabilities/operations/our-insights/transforming-procurement-functions-for-an-ai-driven-world https://www.deloitte.com/us/en/about/press-room/2025-chief-procurement-officer-survey.html
https://www.thehackettgroup.com/the-hackett-group-procurement-leaders-say-ai-will-transform-their-jobs/ - Chartered Institute of Procurement & Supply (CIPS). AI in Procurement & Supply Report (2024). Skills readiness and automation expectations. https://dkf1ato8y5dsg.cloudfront.net/uploads/96/108/cips-special-report-ai-in-procurement-supply-2024.pdf