AI's quantified impact on the finance function

For chief financial officers (CFOs) and finance professionals, the expectation to be guardians of stability and agents of transformation has elevated both what’s at stake and opportunity. To tackle this paradox of responsibilities and drive value through the organization, finance executives need to leverage new approaches, new tools, new perspectives, new organizational constructs, and new skills—especially related to data and decision-making.

Finance leaders need new process approaches that generate quantifiable results—and AI can fit the bill.

Yet, finance leaders are ambiguous about how well their own finance departments fulfill their duties (see figure). In the IBV 2022 C-suite CFO Study, leaders state they are most effective at executing traditional finance tasks (transaction processing); still, two in five are not effective. Only 47% think they excel at measuring and managing performance—a task that has not seen improvement since 2013. And only 38% of respondents say they are effective in planning and executing strategy, a dramatic 25% drop over the same period. Control and risk management effectiveness has declined even more: 31% since 2013.

Finance effectiveness shifting
A decline in strategy and control effeciveness over time

Finance leaders report much room for improvement in their processes, and many are turning to AI for measurable results.

Artificial intelligence as a key enabler to the finance function

Artificial intelligence can change and improve finance processes, driving quantifiable business outcomes and optimizing operational costs. It can be applied to improve transactional activities and decision support. And replacing manual work with AI automation and machine learning can help streamline financial processes while also enhancing business partnerships through better-informed decision-making.

In the record-to-report (R2R) general accounting and reporting area, AI-powered workflow and data models could include a reconciliation module that aggregates subledger transactions and performs risk-based reconciliations and cognitive forecasting. Automating procure to pay (P2P) with AI has been shown to increase productivity and permit finance to detect more fraudulent invoices. AI-driven innovations in order to cash (O2C) help with credit scoring, pricing decisions, and the prevention of payment frauds. AI technology and advanced analytics rank as key components of the financial planning and analysis (FP&A) process, galvanizing and orchestrating planning and performance management.

The future of finance transformation

Given this immense opportunity for finance, the IBM Institute for Business Value (IBV), in partnership with the American Productivity & Quality Center (APQC), surveyed 1,000 senior finance department personnel. The research covered their AI adoption in four key finance areas (R2R, P2P, O2C, FP&A) and finance organization performance. This survey was conducted in 2021 with the goal of quantifying the impact of AI on operational level metrics. AI adopters, defined as those piloting, implementing, operating, or optimizing AI in any of the four finance areas, provided estimations of how AI influenced their scores on common finance metrics.

Across respondents, roughly half report adopting AI in each area, with only one-fifth operating or optimizing AI (see figure). For more than four in five of AI adopters, AI has been incorporated into business-as-usual environments for less than two years.

AI adoption by finance area
Roughly half of organizations report adopting AI in each function

Finance executives who have incorporated AI into processes demonstrated measurable results. Read this report to learn how these senior finance leaders use AI as a key enabler to the finance function, changing the way work gets done and driving quantifiable improvements.