AI, Trust, and Strategy: Six Key Takeaways From Chad Gaydos on The Sourcing Hero Podcast

Procurement has spent years digitizing workflows. Now the question is what happens when AI allows for much more than simply recording them.

That’s the focus of Procurify CEO Chad Gaydos’ recent conversation with host Kelly Barner on The Sourcing Hero Podcast.

They unpack what’s changing as AI becomes more embedded in procurement, why trust is still lagging adoption, and what organizations need to get right if they want to take advantage of the opportunity. 

Drawing on nearly 30 years of deep expertise in the technology sector, Gaydos reflects on how procurement has evolved from manual processes to digital systems and has entered a phase in which software can do more than just capture activity.

It can help teams interpret spend, surface patterns, and support better decisions. It’s a shift that brings new opportunities, but also questions regarding governance, accountability, and the need for more agile strategies.

1. Procurement software is moving beyond record-keeping

One of the clearest themes of the episode is that procurement software is moving beyond simple record-keeping. For years, the goal was straightforward: get work out of spreadsheets and email, create a system of record, and make purchasing and AP processes easier to manage.

That baseline still matters, but the expectation is shifting. As Chad puts it, “Software is no longer just recording activity. It’s beginning to interpret and recommend actions.”

That is a meaningful change. A procurement system used to tell teams what was spent, where an invoice sat, or whether an approval happened. Increasingly, procurement leaders want software to help them understand patterns in spend, spot possible risks earlier, and support better decisions before issues grow.

That is part of what makes this moment different. The question is no longer how to digitize workflows but about turning systems that capture activity into systems that help teams make sense of it.

2. Why this matters deeply to the mid-market

While large enterprises have often had the benefit of bigger analytics teams, more specialized procurement headcount, and more internal resources to make sense of spend data across systems, AI unlocks a new level of access formid-market businesses

“[For] mid-market companies, it’s a really big shift because they typically don’t have large analytics teams,” said Gaydos. “They rely on insights that they can get through the system, but AI can effectively be a layer of intelligence that they just haven’t had before.” 

This is where AI in procurement represents a seismic shift. Not because it replaces expertise, but because it can help smaller teams access a level of support that’s historically been harder to build. The opportunity is not to remove human judgment but to make better analysis more available.

3. The trust gap is real

Procurify’s AI Readiness in Finance report found that 37% of organizations are using AI for spend visibility, but only 30% of those organizations actually trust the outputs.

This gap gets to the heart of the current moment. Adoption is moving quickly, but trust is not keeping up but for Gaydos, it’s not entirely surprising:“Trust always lags technology adoption. And if you think about it, organizations will experience AI, they’ll do it quickly because the potential value is so obvious and what we’re seeing occur right now in the market validates that. But trusting AI to influence financial decisions, that’s a whole different threshold.”

That is especially true in procurement and finance, where teams are accountable for accuracy, compliance, and auditability. It’s one thing to try a new automation tool or leverage predictive analytics and another to let that tool influence decisions tied to money, policy, approvals, suppliers, or reporting.

“Finance leaders, they’re accountable for accuracy,” said Gaydos. “They’re accountable for compliance and auditability. They can’t rely on a black box.”

That’s why trust is a central issue. As AI starts to play a bigger role in procurement, teams need more than speed. They need transparency, explainability, and confidence in how recommendations are formed.

4. Governance is what makes AI usable in the real world

For mid-market organizations, Gaydos says it’s important to build trust in AI by choosing narrow use cases with measurable outcomes and human oversight in placeMake sure there’s visibility into how the system reached its recommendation because, according to Gaydos, “AI should augment decision-making, not replace accountability.”

That matters because it keeps the conversation grounded. AI adoption is often framed as transformation, but in practice, it tends to work better as discipline. Teams build trust when they test a bounded use case, understand what the tool is doing, and stay clear on who owns the final decision.

That’s also why governance is such a vital part of the conversation. It’s what makes adoption real. Without it, AI remains a pilot or a talking point; with it, it becomes part of how work actually gets done.

5. AI will not fix broken processes 

There is often an assumption that better technology will smooth over messy data, unclear ownership, inconsistent workflows, or weak controls. In practice, it usually does the opposite:
“AI doesn’t magically fix broken processes. It’s going to amplify whatever system already exists.”

Suddenly, those weaknesses are impossible to ignore.

“AI doesn’t magically fix broken processes. It’s going to amplify whatever system already exists.”

This helps explain why some organizations get real value from AI while others stall out. The ones making progress are not always the ones moving fastest. They are the ones treating AI “as a capability, not as a feature.” They clean up data, tighten processes, and put guardrails in place before expecting AI to deliver results.

The takeaway is simple: if the foundation is weak, AI will expose it. If the foundation is strong, AI has something real to build on.

6. AI is getting budget. Strategy still has to catch up

Many leaders are feeling pressure from above to have a clear AI strategy, but Gaydos warns against jumping on the bandwagon without a plan: “IT budgets are growing 7% a year versus AI budgets that are growing 100% a year. They want to know how you’re using it. But the worst thing organizations can do is adopt AI as a buzzword.”

 AI has quickly become a leadership question, not just a technology one. While investments are shifting quickly, gatekeepers want to know what the plan is, how AI fits into the business, where it will be used, and what value it’s expected to create.

In procurement, there needs to be clarity and alignment about whether AI improves something the business already cares about, such as visibility, compliance, or cost control, because if it doesn’t, it’s more experiment than strategy.

That distinction matters. Pressure from leadership may push teams to move quickly, but speed doesn’t translate to results.