Just over two years ago, Generative AI burst onto the scene with the debut of OpenAI’s ChatGPT tool. The company later reported that within 60 days, the product had reached 100 million users.
But how many of those users were simply in entertainment mode without much thought as to practical applications? Most likely a majority of them, considering that businesses were not in nearly as big a rush to plug in GenAI tools — of which there are now many — as the general public initially was.
Indeed, among 900-plus finance and accounting analysts, managers, directors, controllers and CFOs surveyed earlier this year by Deloitte and the Institute of Management Accountants (IMA), only 9% said they are currently using GenAI, while 8% were in an early phase of adoption.
Three-quarters of the respondents said they were at least a year away from adoption. Three-fifths (60%) said any adoption was at least two years away, including the rather startling 38% who said they had no plans to ever adopt GenAI.
“While the interest in [both] traditional AI and GenAI is reaching new heights, organizations are adopting AI tools at a lower rate than many may have expected,” Deloitte wrote in its survey report. Finance departments “seem to be waiting for more niche tools to enter the market or more advanced out-of-the-box technologies to emerge with practical applications.”
The top perceived challenge with implementing GenAI tools was integration with existing systems. Among survey participants, 19% cited it as having been a challenge with past AI implementations. Next on the list of challenges were security concerns, data governance and lack of skilled labor.
When asked about future challenges, integration with existing systems remained in the top spot, although data governance and lack of skilled labor ticked up in importance.
The survey report noted that specific integration challenges vary from one organization to another. However, a common one is the alignment of system architecture, which ties in with data governance. “This relates to the noted challenges around data inconsistencies across applications,” the report said. “Inconsistent data governance across the organization leads to challenges in implementing integrated solutions.”
As to the benefits of GenAI for finance teams, the top responses among those surveyed were increased automation enablement, a reduction of monotonous responsibilities and easier data analysis.
As such, companies’ perhaps unexpectedly timid usage of GenAI to date could prove unwise, the report suggested: “GenAI can increase the power of predictive analytics. With GenAI, the model can offer a prediction with the additional benefit of context and explanations around that prediction.”
Deloitte called GenAI “rocket fuel for operations” that can allow a workforce to use technologies to guide decision-making and focus on more critical or strategic tasks.
The report stated, GenAI could create “a more profound relationship between humans and technology.” Finance leaders can use it to run intelligent searches of databases, standard operating procedures and regulatory documents; to generate control compliance reports to provide domain-specific expertise to business decisions; and to monitor compliance, ethics and control across the business.