AI in Procurement Won’t Replace Your Team But Redefine Their Role
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Procurement hasn’t always been front and center. For a long time, it sat behind the scenes — focused on compliance, cost savings, and vendor paperwork. But in the past few years, that’s changed. Supply chain disruptions, rising vendor costs, and expanding SaaS portfolios have made procurement a core lever for business stability and growth. CFOs are paying attention. So are boards.
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In response, teams are turning to technology. According to the MHI Annual Industry Report with Deloitte, 74% of global supply chain leaders are increasing their investment in technology and innovation — AI, automation, and data-led platforms, among them. AI in procurement is a natural next step. 
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You may already be using copilots to draft emails or workflow tools to speed up intake and approvals. There’s promise here — but also pressure. If automation handles more of the repetitive work, what’s left for your team?
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The answer isn’t fewer people. It’s a shift in how they create value.

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The Problem: You Can Automate Tasks, Not Judgment

AI is already reshaping procurement. I’ve seen tools that pull key terms from contracts in seconds, benchmark pricing across categories, even write a first draft of a vendor comms email. These are big wins. But there’s a hard line that AI can’t cross: judgment.
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AI can give me insights and inputs on what levers I can use. But AI can't watch the body language of the person I’m talking to and see when they squirm. It doesn’t know that if we make this deal, I’m also churning 10% of my staff.
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Strategic procurement is built on nuance. It’s informed by context. It depends on human perspective — something automation can’t replicate.
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1. Over-Automation: Trusting AI Too Early

In the race to modernize, it’s tempting to hand off as much as possible to AI. But I’ve seen teams push AI too far, too fast. A model might be able to rank vendors. Doesn’t mean it should choose them. It might summarize a contract well. Doesn’t mean it should handle the negotiation.
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The risk isn’t that AI gives you the wrong data — it’s that it gives you the right data at the wrong time, with no understanding of why it matters.

It’s a challenge across industries. A recent BCG survey found that over two-thirds of leaders are either ambivalent or dissatisfied with their AI progress. The gap isn’t capability. It’s alignment. Aligning tools to decision-making is still hard.

2. Under-Leverage: Keeping Talent in the Weeds

While some teams automate too much, others fail to automate enough. Skilled procurement professionals are still buried in intake reviews, vendor comparisons, and spreadsheet clean-ups — work that no longer requires a human touch.
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The result? Talent is stuck at low leverage. According to Accenture, 60% of routine tasks in procurement can already be supported by generative AI in procurement. That’s time and energy your team could be spending on supplier strategy, stakeholder alignment, or value-based negotiations.
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The cost of not automating is also measurable. According to Gartner, human error leads to over 25,000 hours of rework annually in finance teams — costing $800,000 a year. The solution isn’t more headcount — it’s smarter deployment of your existing team.
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I’ve said this before, and I’ll say it again: I don’t want five more people doing transactional work. I want one strategic operator, backed by automation, who can lead outcomes.
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When you automate too much, you lose judgment. When you automate too little, you limit your people. Either way, you cap what procurement can become. The path forward isn’t about choosing between humans or AI — it’s about building the right relationship between the two. That’s where the Procurement Engineer comes in.
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The Solution: Elevating People Through AI — Not Replacing Them
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The Procurement Engineer is a mindset and a function that blends strategic thinking with AI in procurement orchestration. This role isn’t defined by chasing approvals or tracking spreadsheets. It’s about enabling scale, embedding intelligence, and making the most of human judgment.
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Even if I had a buyer team, I’m still taking those negotiations myself. 
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There’s still something about understanding your counterpart, what’s going on with your business, and having empathy for the human element. Because we’ve moved into a world of relational procurement — and AI can’t replicate that.
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That’s where the co-pilot model comes in.
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1. AI Structures Data and Identifies Gaps

Procurement teams sit on an enormous volume of data. But the challenge has never been access — it’s organization. Critical insights are often buried in PDF contracts, hidden in scattered email threads, or siloed within department-specific tools. Information about renewal dates, license utilization, vendor commitments, and commercial terms rarely live in one place — let alone in a format that’s easy to analyze.
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At Spendflo, we use natural language processing and data classification algorithms to automatically extract key terms and details from unstructured sources. Whether it’s a contract buried in email attachments, a usage report from your billing system, or a renewal notice forwarded last minute — the AI reads it, structures it, and connects it to the right record in the system.
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For instance, let’s take a look at our recent AI in procurement example: streamlining contract data and renewal risks for Wodify. We replaced guesswork with visibility, enabling faster, sharper decisions.
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This kind of transformation is only possible when data is structured, not just stored. And structuring it manually is neither scalable nor reliable. That’s why AI becomes the starting point. It lays the foundation for every strategic procurement decision that follows.
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2. Agents handle repeatable intake, triage, and vendor discovery.

Manual intake and triage drain time and morale. When every request needs a form, follow-up, review, and escalation, procurement turns into a helpdesk. This is where AI agents in sourcing and procurement shine. They classify requests, flag missing data, route them to the right stakeholder, and recommend preferred vendors — all while enforcing policy in the background.
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I firmly believe that AI can scrape across workflows and tell you what’s repeatable — what’s common. It learns and optimizes your intake without you having to manage it step by step.
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Tabby is a great example. As a high-growth company, they were adding vendors and tools frequently. But their intake process couldn’t keep up — requests came through Slack, email, even verbally. 
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Nothing was standardized, and procurement was overwhelmed. With Spendflo’s intake and triage workflows in place, requests are now automatically assessed, prioritized, and routed. Approvals are routed based on the spend and stakeholder, and vendor options are surfaced instantly.
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The result? Cycle times dropped, and procurement regained control without needing to scale the team. Automation didn’t just improve speed — it restored consistency.
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3. Procurement leaders focus on decisions, relationships, and high-leverage judgment.

Once data is structured and admin is handled, procurement gets the time — and context — to focus on what matters: managing risk, navigating trade-offs, and driving alignment between functions. This is where humans outperform AI in procurement. 
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AI still can’t read the room. It doesn’t know why a deal might need to wait, or how a team is feeling about a tool. That’s still a human call.
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Ripcord’s team faced this exact challenge. Leadership wanted tighter software control, but procurement was spending most of its time on admin — hunting down contracts, chasing renewals, and managing emails. 
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With Spendflo, much of that backend was automated. Their team shifted focus to vendor relationships and strategic negotiations — identifying licensing overlaps, negotiating better terms, and aligning with finance on real usage.
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The outcome? A 20% reduction in SaaS spend — not through blanket cuts, but better calls made by a team finally free to think strategically.
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This is what the Procurement Engineer model unlocks.
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When AI takes on structure and scale, people bring judgment and direction. Together, they redefine what procurement can contribute — faster decisions, smarter sourcing, and real ROI.
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The Path Forward
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At the end of the day, this isn’t about how many emails you send or contracts you chase. It’s about how well they orchestrate systems and steer outcomes. Use of AI in procurement is powerful, but it doesn’t know your vendor relationships, your internal blockers, or the risk appetite of your leadership. That’s still human territory.
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The shift underway is subtle but decisive — from transactional gatekeeping to intelligent enablement. With the right AI layer, procurement becomes embedded earlier in the buying process, steers strategic trade-offs, and anticipates risk before it’s visible on paper.
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But that shift won’t happen on its own. It needs tools purpose-built for your context, and partners who understand the stakes.
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For teams willing to make that shift, the opportunity isn’t just efficiency — it’s influence. It’s time to build for that.