CFOs are gaining confidence about using artificial intelligence (AI) to optimize financial processes. Source-to-pay processes (S2P), which include both accounts payable (AP) and accounts receivable (AR), are areas of particular interest. Nearly two-thirds of CFOs (63%) experienced delays in the S2P cycle over the past year. Many identified payment execution and authorization as pain points. AI tools could seize this opportunity to streamline these processes and reduce delays.
AR is a particularly promising target for AI investment because CFOs would pay for improved AR functions. Notably, 55% of CFOs representing middle-market businesses would be willing to pay 3% of the invoice amount to accept payments using a solution that automates invoice approval and payment. This readiness to invest more than the current 2% market average for AR technology highlights CFOs’ commitment to these improvements.
AI Investment Grows Despite ROI Concerns
More CFOs have set aside their lingering skepticism about AI’s ROI aside and are pushing forward implementing the technology. Budgets are also growing. CFOs expect an average GenAI investment increase of nearly 10% next year, building on an existing average of $3.16 million. While middle-market firms reporting a very positive return on investment (ROI) for AI are increasing their investments by 19%, those with marginal ROI anticipate just a 6.2% increase. However, even this more modest uptick reflects a deepening commitment to integrating AI across operations. For many CFOs, this has meant focusing AI investments on medium-impact tasks like automating workflow management and generating financial reports.
Recent trends suggest that executives’ commitment to integrating GenAI deepens as they gain familiarity with the technology. PYMNTS Intelligence data analysis finds that in June, 78% of middle-market CFOs planned for bigger GenAI budgets next year. This represents a 47% increase from the share of CFOs who already anticipated greater GenAI investment only a few months earlier. While 82% of CFOs who mostly use GenAI for medium-impact tasks expect an increase in their budget, even more than the corresponding 77% of CFOs who use GenAI primarily for high-impact tasks.
Middle-market CFOs were 86% more likely to report that GenAI is important for financial reporting in June than in March. Overall, they believe it reduces friction and optimizes efficiency.
The momentum behind AI investment now outpaces ROI concerns for many CFOs. In March, 53% expressed a somewhat positive ROI and 80% a very or somewhat positive ROI. By June, 65% were reporting a somewhat positive ROI and 78% a very or somewhat positive ROI.
As CFOs continue to navigate an uncertain economic environment, they’re likely to expand their investment in AI. These technologies can deliver tangible operational benefits, even if the financial ROI is not immediately clear, spurring adoption. On this front, smaller firms have started to lead the way.
The Case for Leveraging AI in Accounts Receivable
AI technologies initially developed for AP are now being adapted to enhance AR processes. These adaptations are delivering some promising outcomes. For instance, Sage’s global expansion of its AP automation product has demonstrated that AI can reduce processing times and costs. But these same efficiencies can also be realized in accounts receivable.
While AI’s importance can vary among CFOs, those using more source-to-pay systems generally believe the technology is more critical. For example, only 17% of CFOs with just one S2P system view AI as extremely or very important. On the other hand, 38% of those with two to four and another 38% with five to six systems see AI as extremely or very important. This more-than-doubling suggests that the challenges associated with managing multiple S2P systems drives the perceived need for AI.
In turn, this could indicate that there is a kind of natural ceiling for AI adoption in the near term. CFOs with simpler S2P systems to tackle AP processes may not yet recognize AI’s full potential in also optimizing AR.
Automating invoice and payment approval processes — whether for payables or receivables — can improve cash flows and reduce financial friction. Currently, more than one-third of middle-market firms already leverage AI for at least half of their AP processes. These firms are 47% less likely to report high levels of uncertainty in their operations. This reduction in uncertainty is crucial for middle-market firms, as they often operate with tighter margins and higher sensitivity to cash flow disruptions than their enterprise counterparts.
How Much Firms are Willing to Invest in Accounts Receivable Solutions
Middle-market firms are often particularly attuned to the benefits of AI in AR contexts. PYMNTS Intelligence data reveals that 55% of these firms are willing to pay a 3% fee for solutions that automate invoice approvals and payments.
Middle-market firms process about 1,500 invoices monthly, meaning even small payment solution fees can significantly impact operations. For example, a 3% fee on a $1 million invoice costs a CFO’s firm $30,000. At scale, with, say, 1,500 invoices at $1 million each, that cost rises proportionally to $45 million.
Moreover, the average middle-market firm loses 3.1% of its revenue, about $14 million, due to payment collection uncertainties. Smaller middle-market firms face a higher impact, losing 3.3% (or $6 million) of their revenue. For middle-market CFOs, investments in AI-driven accounts receivable solutions reflect the need to reduce uncertainty and combat revenue losses.
AI tools are cutting middle-market firms’ costs — and their success highlights the growing demand for solutions that quickly win. These wins chiefly come in the form of efficiency and cost reduction.
Additionally, firms with higher levels of AI-driven automation experience significantly lower levels of uncertainty. They also report greater satisfaction with the technology’s impact on financial workflows. This correlation, which links AI adoption to reduced operational uncertainty, can powerfully incentivize middle-market firms to continue investing. As these firms further seek to reduce inefficiencies, their investment focus on AR solutions that leverage AI will likely intensify.
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