Artificial intelligence has received a mixed welcome from corporates exploring how the technology could disrupt their operations. While AI can deliver time and cost savings, automation and actionable insights, executives are also concerned that the tool will displace professionals like accountants and procurement officials.
New research suggests, however, that the technology is finding harmony in these two areas of the enterprise.
Small business accounting firm Xero and spend management company Ivalua each released new research this week analyzing how artificial intelligence has impacted their perspective arenas.
“The accounting industry is frequently held up as one of the industries most likely to be negatively impacted by AI and automation,” Xero said in its announcement on Wednesday (June 6) of new research on the impact of AI on small business accounting. The company cited McKinsey research, which concluded that up to 800 million jobs could be lost to automated technologies by 2030. Accounting could be among the hardest hit industries.
Despite this fear, Xero’s report concluded that as artificial intelligence heightens its presence in the accounting department, the technology is coinciding with human accountants, not replacing them. Indeed, accountants can act as a guide to enable small businesses to more easily implement disruptive technologies like AI, Xero noted.
Nearly three-quarters of the 512 small businesses surveyed agreed they would continue to use a human accountant even if they had deployed an artificial intelligence app that automates accounting processes.
“We are at an inflection point – advances in tech are profoundly altering the economic and social order,” said Xero Americas president Keri Gohman in a statement. “This presents both positive opportunities and potential pitfalls.”
She added that Xero itself is integrating artificial intelligence into its own solutions in an effort to automate accounting tasks and free up accountants’ time for more strategic services with their small business customers.
“This data shows that advances in AI and automation are not the doomsday scenario for the accounting industry that is commonly portrayed,” said Gohman. “Instead, this is a massive opportunity for accountants to play an even bigger role in helping their small business clients succeed. Technology alone will never be the solution; technology combined with people will be.”
Separately, Ivalua similarly found rising interest in artificial intelligence within corporates’ procurement and supply chain management operations.
The firm published its own report on Tuesday (June 5), surveying more than 400 finance, procurement and supply chain executives in the U.S., U.K., France and Germany.
The results revealed that most (55 percent) plan to make a significant investment in artificial intelligence technology in the next two years; an additional 25 percent said they would make at least a minor investment in AI to explore its potential ROI.
“There is clearly a huge appetite for AI, and this will only increase as more relevant applications and success stories come to light,” said Ivalua corporate CEO David Khuat-Duy in a statement.
While the procurement and supply chain management functions may not be as concerned as accounting professionals about the displacement of human experts as a result of AI adoption, these departments are facing their own challenges when it comes to implementation of the tool.
The largest barrier to AI, the survey respondents said, is a lack of quality data that can be used by AI-powered solutions to make informed, accurate and valuable decisions. This includes a lack of access to data, as well as a lack of normalization between data sets, inaccurate data, information overload and a lack of expertise to be able to make sense of the available data.
“When investing in AI, it’s important that organizations address challenges that will otherwise limit value,” Khuat-Duy continued. “Driving accurate insights from AI is reliant on having a solid data foundation from which to work, and the findings show that this remains a significant obstacle for most organizations. Success requires organizations to simultaneously address enterprise data problems when investing in AI.”
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