Autonomous technology in finance will impact FP&A and controllership in three ways, as acceptance of these technologies among finance leaders is more prevalent, said Gartner recently.
“80% of CFOs we surveyed in 2022 expected to spend more in AI in the coming two years, for example,” said Matthew Mowrey, senior director analyst, research in the Gartner Finance practice.
In addition, around two-third of finance leaders Gartner surveyed think their function will reach an autonomous state within six years, he noted.
To make autonomous finance a reality, organisations, in broad terms, need to move beyond investment priorities and rethink three aspects of their operations, Gartner pointed out.
In particular, organisations need to consider the followings, the research firm said.
- how functions can strengthen semantic models to improve data quality and transparency
- how can technology expand the number of teams performing judgment-based activities versus manual activities
- how autonomous technology in finance can improve business performance by minimising the burden of data analysis and decision making.
Autonomous finance: Three predictions through 2028
To help FP&A and controllership leaders plan out this future, Gartner said it has three predictions for the impact of autonomous technology in finance through 2028.
By 2025, 70% of organisations will use data-lineage-enabling technologies such as graph analytics, machine learning (ML), artificial intelligence (AI) and blockchain as critical components of their semantic modeling, the firm predicted.
FP&A teams build reports and analysis using data from multiple — and often disconnected — systems, the firm said.
End users don’t always have clear visibility into these transformations and can end up not trusting or misusing finance data while making decisions, Gartner added.
“When poorly understood data is used, and FP&A can’t explain its treatment, decision makers often revert to instinct or gut feel,” said Mowrey. “Data lineage solutions promise to better explain data’s treatment and improve its transparency for decision makers.”
An increasingly regulated data environment alongside a growing volume of data and decision support demands is pushing organisations to pursue more ambitious solutions to this problem, Gartner observed.
FP&A teams have tended to perceive this as an IT initiative because it is linked to enterprise data and analytics architecture, the firm said.
However, FP&A teams have the right skills and capabilities to drive it within the organisation, Gartner noted.
By 2027, 90% of descriptive (“what happened”) and diagnostic (“how or why it happened”) analytics in finance will be fully automated, according to the advisory firm.
“There is a recent trend of analytics and business intelligence (A&BI) tool vendors acquiring data science and machine learning providers which indicates a desire to leverage these capabilities to automate descriptive and diagnostic insight generation,” said Mowrey. “Today’s A&BI platforms are shifting emphasis from the analyst as a consumer to the decision maker as a consumer.”
Although automated or augmented A&BI descriptive and diagnostic insights may minimise the analytical skills barrier, decision makers must still understand and act upon them appropriately, Gartner advised.
FP&A leaders must help establish continuous and evolving literacy programs for all employees — including senior executives — to remain relevant and competitive, the firm added.
By 2028, 50% of organisations will have replaced time-consuming bottom-up forecasting approaches with AI, resulting in autonomous operational, demand and other types of planning, Gartner forecast.
“AI-supported decision making is just emerging as a practical, off-the-shelf innovation, and is expected to mature within the next five years, said Mowrey. “Although it is available in many financial planning applications, it just isn’t used that widely, but we expect that to change significantly in the next few years.”
Organisations should pilot solutions in pockets where current decision management approaches leave decision makers wanting, so users will become more comfortable with AI in the decision-making process, Gartner advised.
Greater comfort with AI episodes will lead to more serial acceptance and an organisation momentum to drive further adoption, the firm added.