There’s been a lot of discussion on the use of artificial intelligence and the future of work. Will it replace workers? Will human creativity be usurped by bots? How will A.I. be incorporated into the finance function? These are just some of the questions organizations will face. 

I asked Sayan Chakraborty, copresident at Workday (sponsor of CFO Daily), who also leads the product and technology organization, for his perspective on a balance between tech and human capabilities. 

“Workday’s approach to A.I. and machine learning (ML) is to enhance people, not replace them,” Chakraborty tells me. “Our approach ensures humans can effectively harness A.I. by intelligently applying automation and providing supporting information and recommendations—while keeping humans in control of all decisions. He continues, “We believe that technology and people, working together, can allow businesses to strengthen competitive advantage, be more responsive to customers, deliver greater economic and social value, and generate more meaning and purpose for individuals in their work.”

Workday, a provider of enterprise cloud applications for finance and HR, has been building and delivering A.I. and ML to customers for nearly a decade, according to Chakraborty. He holds a seat on the National Artificial Intelligence Advisory Committee (NAIAC), which advises the White House on policy issues related to A.I. (And as much as I pressed, Chakraborty is not at liberty to discuss NAIAC efforts or speak for the committee, he says.) But he did share that generative A.I. “continues to be a growing part of policy discussions both in the U.S. and in Europe, which has embraced a risk-based approach to A.I. governance.”   

Tech’s future in finance

Consulting firm Gartner recently made three predictions on financial planning and analysis (FP&A) and controller functions and the use of technology: 

– By 2025, 70% of organizations will use data-lineage-enabling technologies including graph analytics, ML, A.I., and blockchain as critical components of their semantic modeling.

– By 2027, 90% of descriptive and diagnostic analytics in finance will be fully automated.

Workday thinks about and implements A.I. and ML differently than other enterprise software companies, Wampler says. I asked him to explain. Enterprise resource planning (ERP) is a type of software that companies use to manage day-to-day business activities like accounting and procurement. What makes Workday’s ERP for finance and HR different is A.I. and ML are embedded into the platform, he says. So, it’s not like the ERP is just using an A.I. or ML program. It is actually an A.I. and ML construct. And having ML built into the foundation of the system means there’s a quicker adaptation of new ML applications when they’re added. For example, Workday Financial Management allows for faster automation of high-volume transactions, he says.

ML gets better the more you use it, and Workday has over 60 million users representing about 442 billion transactions a year, according to the company. So ML improves at a faster rate. The platform also allows you to use A.I. predictively. Let’s say an FP&A team has its budget for the year. Using ML, they predictively identify reasons why they would meet that budget, he says. And Workday works on a single cloud-based database for both HR and financials. You have all the information in one place. For quite some time, the company has been using large language models, the technology that has enabled generative A.I., Wampler says. Workday will continue to look into use cases where generative A.I. can add value, he says.

It will definitely be interesting to have a front-row seat as technology in the finance function continues to evolve over the next decade.

LeackStat 2023