Why Procurement Teams Must Fix Broken Processes Before Automating

Automation magnifies what's already there

Procurement automation promises speed, efficiency, and strategic elevation—but only when applied to processes that already work. Technology leaders are warning that automating broken workflows simply creates faster failure, not better outcomes.

Michelle Lau, Managing Director at Alibaba.com, frames the challenge clearly: technology cannot fix a process if the underlying logic is unclear. Organizations must first establish what good procurement looks like and define their strategic goals before deploying AI agents to execute tasks. Without that foundation, automated systems will surface options that miss the mark entirely.

The warning comes as procurement undergoes a fundamental transformation. For decades, the function has been trapped in manual, operational work—supplier searches, quote comparisons, repetitive administration—despite making commercially critical decisions. New tools including autonomous AI agents and agentic AI are now redesigning B2B sourcing around business realities, but their effectiveness depends entirely on the quality of the processes they automate.

Why it matters

Procurement teams face mounting pressure to adopt automation as competitors move up the maturity curve. According to McKinsey research cited in the original reporting, procurement's spending managed per full-time equivalent has already increased 50% over five years, and AI agents could drive another 25-40% efficiency gain. But organizations that automate without fixing underlying process flaws risk embedding those problems at scale—creating compliance gaps, security vulnerabilities, and strategic blind spots that move faster than humans can catch them.

Where automation creates the most value

Supplier onboarding illustrates both the opportunity and the risk. Organizations collect high volumes of sensitive data—financials, ownership structures, compliance records—often through fragmented systems and manual workflows. That combination creates exposure through inconsistent data, limited visibility, and insecure transfers.

Alicia Heavisides, Global Product Strategy Lead for Value Chain Solutions at Dun & Bradstreet, explains that the most effective approach embeds risk and compliance into the onboarding flow itself, rather than treating it as a linear workflow where data collection precedes risk assessment. Automation works when validation, screening, and risk scoring happen in near real-time, with tiered models that route high-risk suppliers to deeper due diligence while low-risk cases move quickly through standardized checks.

The goal, Heavisides emphasizes, is not faster decisions but more confident decisions made fast, without compromising compliance rigor. Organizations that embed trusted, verified data into automated workflows reduce manual effort while accelerating decision-making.

The boundary between machine and human judgment

Ben Allen, Vice President of Public Sector Solutions at Appian, draws a clear line: AI excels at repetitive, data-intensive work—analyzing information, generating documents, surfacing insights, recommending next steps. But procurement decisions involving ethics, risk, supplier relationships, and mission priorities require human judgment.

The US Forest Service example demonstrates the impact. Managing more than 20,000 procurement actions during peak wildfire season, the agency integrated procurement, dispatch, and payment processes into a single platform, gaining the visibility and agility to mobilize critical resources faster during emergencies.

Yet even in highly automated environments, humans remain accountable for outcomes. AI can present supplier lists with cost options, but selecting critical suppliers stays human-led. Success in agentic procurement relies on intelligent delegation—AI executes workflows while people provide direction, quality control, and accountability.

The skills that matter now

As automation absorbs repetitive tasks, required skills are moving up the value chain. The next generation of procurement professionals needs commercial curiosity, analytical strength, and confidence working with AI as part of daily decision-making. They must know how to brief AI agents properly, challenge outputs, spot gaps, and apply judgment.

Lau notes that AI gathers information quickly but cannot fully understand every nuance of supplier relationships, brand promises, customer expectations, or long-term commercial trade-offs. The best procurement professionals will combine technology with commercial instinct, supplier knowledge, and strategic vision.

According to data cited in the original reporting, 78% of procurement professionals already use AI, with 47% stating the technology is embedded in daily workflows. Organizations implementing AI-driven automated workflows report 30% reductions in procurement cycle times. Meanwhile, 85% of chief procurement officers now prioritize user experience as a top-three KPI for digital transformation programs, up from 40% in 2022.

The question for procurement leaders is no longer whether to automate, but how quickly they can move up the maturity curve—after ensuring their processes are worth automating in the first place.

These details were first reported by Procurement Magazine.