Report: Enterprise use of AI to predict cash flow expected to increase 450%


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Enterprise deployment of AI and machine learning (ML) for cash flow forecasting is expected to increase 450% over the next two years, according to the recently released 2021 Cash Forecasting & Visibility Survey from GTreasury and Strategic Treasurer. The survey of nearly 250 enterprises across industries highlights a growing appetite for AI/ML modernization among finance and treasury teams seeking more accurate and more immediate cash flow forecasts.

To sharpen forecasting capabilities (which are critical for determining business direction and priorities), today’s enterprises are embracing new technology strategies and refining methods to introduce greater automation and efficiency. While just 6% of respondents currently use AI/ML technology to predict and understand their cash forecasting, enterprises’ reported plans indicate that, within two years, that number will reach 27%.

Respondents also indicate a similarly bright trajectory for regression analysis: 12% use it currently, but projected usage will grow to 29% in two years, and 43% use or expect to use it at some point in the future.

Graphic. Title: Rise of AI/ML in the near future. 6% of people are using AI/ML and 12% are using regression analysis. 21% of respondents plan to use AI/ML and 17% plan to use regression analysis in the next two years. 24% plan to use AI/ML and 14% plan to use regression analysis in over two years.

The vast majority of enterprises still rely on traditional manual methods for cash forecasting — 91% of survey respondents report using Excel spreadsheets as one of their forecasting tools. In comparison, 25% have a more modern digital treasury platform in place, and 28% use ERP systems. Fifteen percent use financial reporting and analysis (FR&A) or budgeting tools to assist in their forecasts, and just 5% use a dedicated forecasting platform.

Variance analysis is another task requiring heavy manual effort from enterprises: 57% of respondents say that their variance analysis activities are fully manual, and another 19% report significant manual activities. One-fifth of companies avoid this manual effort only by performing no variance analysis whatsoever. The remaining 5% of respondents do utilize variance analysis that’s backed by fully automated processes.

The survey’s findings are beads strung along a common thread: Enterprises recognize and demand the benefits of more efficient and effective cash forecasting. With investments in AI/ML and other advanced capabilities, many enterprises are already pursuing new strategies and spending what it takes to place the tools and technologies they require at their command.

Read the full report from GTreasury and Strategic Treasurer.


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