While coders, entrepreneurs and venture capitalists rush to unearth the newest, most promising artificial intelligence applications, CFOs can already yield the biggest, quickest payoffs from AI in the mundane — their companies’ back offices.
AI has streamlined and cut costs across a full range of tasks, trimming monthly close time, accelerating resolution of customer inquiries, and speeding data entry, invoice processing and onboarding time, according to several recent studies.
“It's all the back office stuff, where you get the real efficiencies,” Boe Hartman, co-founder and chief technology officer at Nomi Health, said at the recent Money20/20 fintech conference in Las Vegas.
“You can actually either make it faster, make it more transparent, or make it more automated,” Hartman said during a panel discussion, adding “I’m not seeing a lot of folks pushing a lot of the AI work to the front” office.
For example, accountants deploying generative artificial intelligence can upgrade the level of detail of financial reports by 12%, shift 8.5% of their time from routine, back-office processing to higher value tasks, and cut 7.5 days off the time needed to complete a monthly close, researchers said.
By using generative AI, accountants can devote more time toward analytical work, quality assurance and communicating with clients, researchers at the Massachusetts Institute of Technology Sloan School of Management and Stanford University Business School said in a study released in August.
Gains from AI are also measurable, validating expenditures across an AI landscape littered with big, untested promises of high value, and giving CTOs and CFOs data that helps build C-suite consensus behind new spending.
Back office applications of AI are “where savings and tangible results come from that are easy to document,” Shawnna DelHierro, chief information officer at SoundHound AI, said during the panel.
“They’re metric driven, they're repeatable and they're scalable,” she said.
“When you're talking internally and really trying to demonstrate the value of your technology and your automation and your transformations, organizations creating those score cards and articulating the value of some of those back-office automations are achieving easy wins,” she said.
“When you start to get into the more ambiguous use cases, it becomes a little bit more of a soft sell,” DelHierro said.
That said, companies sell AI software to a promising market. SoundHound found in a recent survey that in the financial services industry, 71% of executives believe AI investment is essential for remaining competitive, DelHierro said.
Signals of AI enthusiasm collide with a MIT survey that found 95% of organizations are generating no return from the technology even after $30 billion to $40 billion of investment.
“Just 5% of integrated AI pilots are extracting millions in value, while the vast majority remain stuck with no measurable P&L impact,” according to the MIT study.
The MIT survey is an inescapable spark for conversation, according to DelHierro.
“I don’t think I’ve gone a day in the past five weeks and someone hasn’t said, ‘So what do you think about that MIT report?’” DelHierro said, noting that SoundHound surveys and her own industry observations point to a higher AI success rate.
Hartman is also frequently buttonholed about the same MIT findings.
“Every time I turn around, someone is shoving that paper into my face,” Hartman said.
“I say, ‘interesting perspective right?’” he said.
