Why AI prompt writing is the next core skill for finance

Good morning. Writing effective prompts for generative AI models is becoming a fundamental skill in finance that employers increasingly value.

In the past, finance and accounting resumes focused on CPA credentials, analytics, and technical experience, said Sundeep Reddy, EVP and chief accounting officer at Salesforce, during a panel session at Workday Rising in San Francisco on Wednesday. “Now, it’s shifting to: How have you used AI? What are your prompting skills? Have you written prompt scripts for agentic AI?” he said.

Salesforce employees are being trained not just to adopt AI agents, but also to write precise prompts. “You’re not coding—you’re writing plain English instructions,” Reddy said. “It takes trial and error to find the right level of detail for querying.”

Reddy, a former auditor, emphasized the importance of controls and validation: “Is this grounded? Is this auditable?” He recommended a “gut check” when reviewing AI outputs, and he encouraged iterative prompt refinement for accuracy and reliability.

A recent study, “As Generative Models Improve, People Adapt Their Prompts,” describes a large-scale experiment with 1,893 participants. The research found that only half of the performance gains achieved by switching to a more advanced AI model were due to the model itself; the other half came from users adapting their prompts to take advantage of its capabilities.

Prompt engineering is foundational, Tommy Schroeder, managing director at Accenture, said during the panel session led by Julie Gonzalez, SVP of finance at Workday (a CFO Daily sponsor). Embedding critical thinking into prompt writing is essential to maximize AI’s value, Schroeder said.

Critical thinking remains key in finance as professionals work with both people and AI agents, said Justin Junkel, EVP of global technology, operations and finance at Pinnacle Group. He sees this as an extension of the skill evolution that began with early AI technologies like machine learning and RPA, but managing agentic AI introduces new challenges.

Schroeder highlighted the importance of understanding AI frameworks in finance, which accelerates prototyping, experimentation, and ongoing improvement.

“Encouraging experimentation is something we’re driving in our organization,” Reddy added, “and I want to see those skills in new hires.”

Sheryl Estrada
moc.enutrofobfsctd-2bfb95@adartse.lyrehs

This story was originally featured on Fortune.com