I’m the chief financial officer of a shipping logistics company that brings in tens of millions of dollars in annual revenue. I have more than a decade of experience in finance, I’ve earned a master’s in accounting and I’m a certified public accountant.

In contrast, several members of my finance team were hired with only a few college courses under their belt and limited real-world finance experience. That’s because the bulk of our finance functions — including critical roles like accounts payable manager — are handled by college interns.

And we’re not embarrassed by it.

On the contrary, at my company, FirstMile, we’re proud of the fact that we’ve been able to achieve success without requiring all of our team members to obtain extensive, and expensive, credentials or experience before they begin working with us. Our approach allows bright young people interested in finance careers to learn by doing, helping to launch them quickly on a career trajectory that might otherwise require years to develop.

The key to all of this is our ability to use technology that lowers the barrier of entry to careers in the shipping and logistics industry. When you have the right technology in place, including AI-enabled finance tools in the case of my department, you can open the door for young professionals to work effectively and efficiently, regardless of how much coursework they’ve completed or which certifications they hold.

Here’s how we’ve embraced AI financial management technology to power an innovative workforce model, and what we’ve learned along the way.

3 Statistics About AI in Finance

  • In 2024, AI could increase financial services revenues by 34 percent and economic growth by 26 percent.
  • Almost half of financial services executives, at 41 percent, feel that AI chatbots will have the biggest influence on their industry by 2025.
  • Over 87 percent of industry leaders are adopting AI for fraud detection and anti-money laundering, making cybersecurity the top AI use case for financial services.

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Why We Place Our Finances in the Hands of Interns

At my company, we realized early on that it’s important to innovate business practices. That’s why we’ve embraced a workforce strategy for the finance team that centers on hiring interns by finding young professionals who possess the skills and exceptional promise necessary to evolve into long-term contributors to the company.

And to be clear, these are not stereotypical interns who fetch coffee while “real” accountants handle the books. On the contrary, we staff key roles that at most companies would go to someone with years of experience with college students.

We see this model as a win-win for our staff and our business. The interns we hire get a level of hands-on finance experience that just isn’t reproducible inside a classroom, and many transition into long-term positions with our company. Meanwhile, the business enjoys the benefit of reduced payroll costs, since our hiring strategy allows us to obtain the talent we need at as little as one-third the compensation levels normally associated with these roles.

For the record, I should note that we have talented employees on staff who aren’t working for us as interns, as well. But approximately half of our finance team consists of students who you might not expect to see playing critical finance roles.

 

The Technology That Makes It Possible? AI.

You might assume that you get what you pay for when it comes to staffing, and that relying on college students to power key finance functions comes at the cost of efficiency or accuracy. But actually, the opposite is true.

Despite our interns’ limited experience, and the fact that there is somewhat higher turnover because not all of our interns move into full-time roles, we’ve been able to maintain highly productive, reliable and consistent financial processes. The secret to this success was our adoption of AI-enabled financial management software. With AI, much of the work that would traditionally require experience to carry out well can be automated by software.

For example, we rely on AI capabilities from Stampli to code our invoices and route them through the approval process. The tool automatically detects the codes we use by analyzing existing invoices, then codes incoming invoices on its own. Our team verifies the results just to check for the rare coding errors that sometimes occur, but the bulk of the work is automated.

As a result, we’ve reduced the time it takes to process each invoice from an average of about five minutes to less than one. And the accuracy rate is very high; it’s quite rare that we have to recode an invoice manually to correct mistakes made by AI.

 

From Automation to ‘Real’ AI

Previously, we relied on AP software that provided some automation features but that didn’t rely on real AI. Instead, it automatically coded invoices based on rules that we configured to govern which invoices should receive which codes. That approach saved some time, but we still had to set up the rules and update them whenever we modified our codes — tasks that were difficult for inexperienced staff to handle.

But when we migrated to Stampli about a year ago, this challenge disappeared. We no longer have to manage invoicing rules, because our AI tool detects invoice coding patterns on its own. Whenever our codes change, it adapts automatically.

I make this point to underscore that AI can enable automation, but automation is not the same thing as AI. Settling for an approach that automates some financial processes, but that lacks the intelligence and adaptability of AI-powered solutions, means missing out on opportunities to optimize the way finance teams work.

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An AI-Centric Future

In addition to being excited about the ways that AI-powered finance tools have enabled innovation for my department’s hiring strategy and operations, I view our accomplishments as a critical proof-of-concept that opens the door toward similar innovations in other business domains.

Virtually any business function that depends on manual data entry and processing can benefit from AI. AI-based finance automation solutions like the one we’ve adopted are notable because they’re not just using AI experimentally; they’ve made it a core capability. But at my company, we’ve already begun embracing AI in other parts of the business, such as sales and marketing, and I expect to see future innovation in this realm as more solutions with mature AI functionality become available.

In short, what we’ve done in the finance department is only the beginning of what is poised to become a much bigger trend, through which novel AI capabilities allow businesses to rethink old assumptions, like how much experience key employees need, in fundamental ways.

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