AI to Boost Economic Growth, But Not Without Risk

In an era defined by the rapid evolution of artificial intelligence (AI), the profound impact of AI has become increasingly evident. Transformative AI technologies such as OpenAI’s ChatGPT have reshaped the business landscape by boosting productivity at the workplace. The use of generative AI in finance is expected to increase global GDP by 7%—nearly $7 trillion—and boost productivity growth by 1.5%, according to Goldman Sachs Research. AI has the potential to increase financial services revenues by 34% and economic growth by 26%, according to a report from Gitnux. Chatbots are also gaining popularity as “41% of financial services executives believe AI chatbots will have the largest impact on their industry by 2025,” the report reads.

The majority of productivity gains come from places you don’t expect. “It doesn’t come from doing existing tasks a little bit better, it comes from entirely new things,” Kevin Hebner, Ph.D., global investment strategist at Epoch Investment Partners, Inc. (New York, NY) said during FCIB’s Global Expert Briefing, who estimates that AI will increase productivity by 10-15% by 2040. “At least for mid-level writing, AI can increase productivity by 40%. If you’re coding, it increases productivity by 55%. Call center workers overall receive immediate improvement by about 44%. For new workers, AI increases productivity by about 40%.”

AI won’t necessarily replace people as there is still a need for people to analyze the data AI generates. But AI will replace people who don’t learn to use AI strategically. Workers with AI skills are particularly valuable and command salaries 21% higher than average, but potentially up to 40% higher—in part because these skills can be combined with other valuable skills, according to a study from researchers at the Oxford Internet Institute, and the Center for Social Data Science, University of Copenhagen.

Indeed’s data showed that searches for generative AI jobs jumped to 147 per million total jobs searched in May from virtually zero a year earlier and by the end of October, there were 20 times as many job postings mentioning generative AI-related keywords than when the year began. Its U.S. website showed generative AI job listings from companies such as Meta Platforms (META.O), Apple (AAPL.O), Tiktok, Pinterest (PINS.N) and Amazon.com (AMZN.O), according to a Reuters article.

Sherri Kratz, CCE, credit supervisor at Green Bay Packaging, Inc. (Green Bay, WI) says her team uses AI at a minimum as it is already built into some of the department’s existing software but is currently investigating and developing the skills for when they do get on board with more AI. “With the entire team involved, we can develop novel ideas or best practices that fit our needs and we can find ways to evaluate more data than we did before,” she said. “AI overall is something we’re exploring and excited to use more of.”

AI Risk Factors

The risks factors associated with AI have made some industries hesitant in implementing more AI at the workplace, including B2B credit management. An eNews poll in June revealed that over half of credit professionals are not likely to implement AI in their credit and collections process as opposed to the 6% already leveraging AI—and 19% said that they’re very likely to implement AI in 1-2 years, while 13% are still unclear on how AI would help the credit and collections process.

One major concern is the security risk as AI tools often use, hold and interact with significant volumes of sensitive information. This data could be exposed to unauthorized access and result in a costly data breach, according to JD Supra. “I’d love to experiment with ChatGPT to write a credit application but I’m worried about putting confidential information into it,” said Krystal Daugherty, CCE, order-to-cash manager at Acuren Inspection Inc. (La Porte, TX) who does not currently use ChatGPT in her credit department but plans to in the near future. “I’ve gotten positive feedback from friends who frequently use it and I agree with them that this is the next tool in business that can easily be expanded into department policies. My concerns are what does the terms of service say? How will this information be stored and used for other people?”

The shortcomings of AI associated with discriminatory, biased or inaccurate outcomes and decisions are another concern for credit professionals. “While AI is a helpful tool, we’re mindful of its limitations,” said Joshua Nolan, CCE, senior director of financial operations at PrePass (Phoenix, AZ) whose department uses ChatGPT for drafting, reading and analyzing emails as well as creating templates—making communication more efficient. “Sometimes, it might miss the context of certain details, so we ensure that human judgment is always in the loop. Regular checks are in place to review and adjust its output, ensuring accuracy. To maintain privacy, we follow protocols to ensure we are not placing sensitive data into the AI models.”

According to Axios, the most obvious risk from AI in financial markets is the AI-powered ‘black box’ trading algorithms run amok, and all end up selling the same thing at the same time, causing a market crash. “There simply are not that many people trained to build and manage these models, and they tend to have fairly similar backgrounds,” Gary Gensler, SEC chair said in an SSRN paper. “In addition, there are strong affinities among people who trained together: the so-called apprentice effect.”

Model homogeneity risk could also be created by regulations themselves. “If regulators exert control over what AIs can and can’t do, that increases the risk that they’ll all end up doing the same thing at the same time, and also increases the likelihood that firms will all choose to use AI-as-a-Service offerings from a small number of beyond-reproach large providers,” reads the Axios article. view the November 2023 report. CMI archives also may be viewed on NACM’s website.