AI Skills: Must-Haves for Finance Roles & How a DOL Rule Can Help Everyone Gain Them

AI skills aren’t just nice-to-haves anymore. Finance leaders and the U.S. Department of Labor can agree on that much.

Nearly a third of finance job postings now explicitly reference AI or machine learning capabilities, up from 25% a year ago, according to research from Datarails.

When it comes to job postings for accountants, 67% specifically mention AI skills. AI demands seem to be steepest where analysis meets strategy: 43% of the postings for financial planning and analysis pros now require AI or machine learning, up from 33% a year earlier.

“The finance professionals who will thrive are those who combine AI fluency with strategic thinking and the ability to tell a compelling story with data,” says Didi Gurfinkel, CEO of Datarails.

The DOL’s Directive on AI Skills Learning

The timing couldn’t be better for the DOL to release the Artificial Intelligence Literacy Framework. With that, the DOL has essentially declared that AI skills and literacy are foundational workforce competencies.

Finance pros say they want them. The DOL says everyone needs them.

The framework outlines five skill areas employers will want employees to master: 

• Understanding AI principles 
• Applying AI in real-world contexts
• Directing AI tools effectively through promotion and iteration 
• Critically evaluating AI outputs, and
• Using AI responsibly and ethically.

“The framework recognizes that AI literacy is becoming a baseline workforce skill and no longer just one that’s ‘nice to have’,” says Mark Quinn, Senior Director of AI Operations at Pearl. “Engineers and developers aren’t the only ones who need AI skills. Workers across all professional industries, and especially within high-stakes industries, like law, finance, and healthcare, need to understand not only how to use AI, but how to use it effectively, safely, and compliantly.”

That’s partly why the guidance also stresses that how employees are trained is as important as the training itself. Training programs should be:

• Experiential and contextualized to industry needs
• Agile in design, and
• Aligned with labor market demands.

Finance Training for AI Literacy

The good news: The DOL issued a framework for literacy and skills. These didn’t issue mandates on exactly what people need to know or do. You have guidance on how to help your finance team adopt and master AI responsibly and effectively.

And a starting point should likely be this: AI is a strategic function — not just an IT function — with finance playing an important role.

Here are five early best practices on building AI literacy and skills:

1. Create and Communicate Balance

The DOL guidance helps organizations create governance around usage, security and safety policies from the moment you introduce AI to your finance operations.

“There must be clear communication and a balance of ensuring safety without being overly restrictive, because employees may use AI secretively out of concern that its usage is wrong,” says Quinn.

2. Integrate Rather Than Initiate

“Build AI … into how people are already working, rather than treating it as a separate initiative that feels mandatory and generates unnecessary fear,” says Quinn.

In fact, at some bigger companies that adopted AI early, AI skills and literacy has been embedded into performance reviews, where employees are rewarded not for whether they are using AI, but for how they are applying it to their workflows.

3. Focus on Accuracy

Going back to two of the five key points in the AI literacy framework — 1) critically evaluating AI outputs, and 2) using AI responsibly and ethically — organizations will want to focus on accuracy early and often. That couldn’t be more critical for any area within an organization than Finance.

As an example, Pearl already holds mandatory AI training for accuracy: “These measures ensure that the fundamental understanding of AI’s shortcomings and the need for verification from a human expert is baked into every employee’s daily approach to their work,” says Quinn.

4. Find a Champion

AI learning and development can be exciting and intimidating. Again, with AI skills and literacy guidance, you have the room to teach and build in ways that work best for your team or within your organization.

While you might take the lead on IT learning, you might find champions of the effort in one or a few other finance employees. Employees tend to embrace AI and its possibilities when their colleagues do.

When possible, step aside and let employees learn from each other.

5. Incentive AI Skills, Literacy

People fear AI will take their jobs. So they might run or hide in fear. But they’ll probably jump at the chance to embrace AI if they’re incentivized!

Even better, Quinn suggests, “Management can offer these payouts to employees at all levels and can pull funding for them from the AI-driven cost savings employees discover and implement.”

But really, you know if that’s possible.

Still, it doesn’t just have to be about money. You might want to focus on non-monetary incentives such as career growth, improved workflows, public successes or leadership roles on AI projects.

“A McKinsey study shows that the most effective driver of AI adoption for employees is formal training and skill development,” Quinn points out.

And the 1 Skill AI Won’t Replace, But Every Accountant Wants It To …

Now, for a lighter look at AI and what it doesn’t do … count things auditors still have to.

That’s the complaint of many junior auditors, who are often tasked with traveling to less-than-ideal locations in less-than-ideal conditions to take inventory of less-than-ideal items: rocks in a quarry, traffic lights in a municipality or corn in grain bins.

“At a pet hospital, I had to count individual pills, but there were two types of pills mixed,” Billy, a 28-year-old ex-Big 4 accountant, who left the industry for said reasons, tells me. “You needed a microscope to see. The room had to be kept at freezing temps, and the lights were low. So you needed to use a flashlight and a handheld microscope, and then separate pills that look identical, based on a small serial number in a freezing room.”

Another one: My husband often complains of counting rock salt (and accounting for some that was allegedly stolen) from an — alas! — rock salt pile.

So, why won’t AI take over auditing anytime soon? U.S. auditing rules haven’t exactly kept pace with technology. Of course, they require that a person physically verify inventory. The rules barely mention AI and just recently pulled mention of fax machines!