AI Use Cases in Procurement: Mid-Market Lessons From 3 Real Rollouts

Three mid-market leaders, Alex Costa of PSC Group, Damon Norris of BASIS Ed, and Elizabeth Parish of Questrade, have each rolled out AI in procurement and finance operations. Their experiences point to the same conclusion: AI readiness isn’t about having the most advanced technology. It’s about having the right foundation, and being willing to learn as you go.

Rallying around the specific problem you’re trying to solve matters more than the sophistication of the tool. Testing, learning, and iterating toward a workable process is what actually gets a team to scale. Teams that trust their data, streamline how work moves, and free people to focus on higher-value judgment are already seeing results. The lessons below, drawn from a panel discussion Procurify hosted with all three leaders, are worth borrowing before you build your own AI roadmap.

Start with one use case, not a platform rollout

For Alex Costa, Senior VP of IT and Security at PSC Group, AI adoption wasn’t about chasing a trend. It was about solving a problem.

“Instead of just adopting AI, we identified a use case and asked, ‘Okay, how can we leverage AI to address a specific need or this specific gap?’” Costa said.

With a small IT team and growing workloads, PSC began by automating infrastructure monitoring. The result was more uptime, faster response times, and less manual effort. From there, the door opened to explore AI in finance and operations.

The pressure to scale was just as real for Damon Norris, VP Finance at BASIS Ed: education funding is fixed, but expectations keep rising.

“We started trying to figure out how to get teams to manage agents and use the AI to help do some of the work—as the old adage goes, ‘work smarter, not harder’—to really optimize our teams so they can get more work done,” Norris said. “This may mean they’re not touching every invoice, for example, if it can flow through, and figuring out when to add the human interaction.”

That’s a specific instance of AI-powered AP automation: letting routine invoices flow through untouched while a person only reviews the exceptions.

By automating purchase approval workflows and spend reviews, his team reclaimed time for strategic planning and analysis. The change meant freeing people from manual tasks to focus on value-add work.

The real AI adoption challenge is trust

Trust came up repeatedly, and for good reason. Norris admitted his finance team was initially hesitant to rely on AI, a hesitation that’s familiar to most organizations early in an AI adoption journey.

“We’re a team of control freaks,” Norris laughed. “We want to make sure everything’s right so getting people to trust the AI is always the key. But every day is a step forward as we look to turn on more AI power.”

Norris’s team isn’t the outlier here. Trust in AI’s outputs is one of the top-cited barriers to broader adoption, named by 35% of respondents in Procurify’s 2026 AI Readiness in Finance Report.

He also advised against treating AI adoption as a top-down mandate. It works better as a company-wide approach where people buy in precisely because they have a voice, feel empowered to share feedback, and feel genuinely informed.

Small, visible wins, faster approvals, fewer invoice errors, helped his team see the value firsthand. Over time, trust turned into habit, and habit into readiness.

Visibility turns bottlenecks into fixable problems

At Questrade, instant, automatic visibility was the turning point. Elizabeth Parish, Director of Vendor Management, described how real-time insight into approvals and spend transformed efficiency.

“We’ve been looking for anywhere that we can create efficiencies and be an expansion of someone’s role,” Parish said. “When it comes to procurement, it’s the sheer volume and being able to leverage a tool like Spend Insights to automate or find information without needing to ask someone to export data, really saves time, and you can be assured that it’s accurate data.”

Visibility into time-to-approve trends was another turning point for Parish’s team. Bottlenecks that used to take days of manual data gathering to even identify became immediately visible, freeing up time to actually fix them instead of just finding them. That confidence in the data, and in the system producing it, is what moves teams from AI experimentation to everyday use.

Guardrails are what let you move faster

Costa’s perspective as a security leader was especially instructive on governance as an accelerator, not a barrier.

While rolling out new AI tools, PSC Group trained employees on data handling and put clear safeguards in place to make sure people understood how to use the technology properly.

“We implemented the technology that’s required to keep things secure, but we’re also pushing different training and education to our folks to make sure that they’re using the technology properly,” Costa said. “You have to train them and give them the proper tools and the right procedure.”

“With the right guardrails, you actually move faster,” he said. “Everyone knows what’s safe, what’s not, and how to experiment responsibly.”

That structure lets teams innovate with confidence instead of hesitation. It also lets other functional units see IT as a partner balancing safety with agility, rather than the default perception of IT as a blocker.

“IT kind of gets the bad rap for slowing stuff down. Well, procurement also does,” Norris said. “And now we’re standing shoulder-to-shoulder with IT, and we know the questions before they’re even asked, because we’ve worked on these things before.”

AI ROI should be measured in time and cost savings

When the conversation turned to ROI, two things dominated: time and focus.

For Parish, every minute saved on manual approvals is time reinvested in strategic vendor relationships. For Norris, automation has meant redistributing employee capacity toward higher-skilled work.

“As we look at AP, and as we adopt more and more of the automation process and the AI that comes with Procurify that can simplify that track, it’s going to free up hours of time for our staff,” Norris said. “That means potentially either promoting them out of an entry-level job, retraining them or offering something better for their career.”

The return on AI investment isn’t only financial. It’s cultural: empowering people to do better work with the same resources.

The road ahead is autonomous

All three leaders agreed the future of AI in procurement is autonomous, but not impersonal. That shift toward systems that act on their own within clear boundaries is what’s now commonly called agentic procurement.

“AI should be an extension of the team,” Parish clarified. “We don’t want any resources to think that this is going to replace their jobs. When it’s working, it’s about, ‘Can I have this running, doing redundant, mundane tasks while I do this other thing?’ So you’re not replacing a resource, but maybe you don’t need to add five new resources that year.”

That vision starts with readiness: the groundwork that lets AI tools drive consistent value at scale, rather than sitting unused after a rushed rollout.

AI Readiness Checklist

• Your team trusts the data they see every day.
• You’ve identified at least one manual process to automate.
• You’ve built guardrails for governance and compliance.
• Your team is curious, not fearful, about AI’s role in their work.

This checklist is a starting point, not a gate, so don’t wait until every box is checked to begin. As your team checks more of them off, the real test becomes whether you can prove the investment is actually paying off, not just that AI is in use.

See AI readiness in action

Organizations like PSC Group, BASIS Ed, and Questrade are using Procurify to connect data, automate approvals, and uncover insights in real time.

If your team is ready to operationalize AI in procurement, now’s the time to take these lessons and turn them into action at your own organization.