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Tools like machine learning algorithms can also help analyze payment patterns to improve cash flow forecasting giving cfos and treasurers a clear view of working capital. With ai financial reporting is no longer a static backward-looking process. Machine learning algorithms can synthesize data from multiple sources erp systems bank feeds and even external economic indicators to provide predictive insights. This empowers finance teams to move from reactive reporting to proactive strategy.

According to a pymnts intelligence report outlook : cfos sri lanka cell phone number list envision growing role for generative ai in finance cfos are also adopting generative ai in finance for strategic and financial tasks. More than of cfos reported using genai for creating data visualizations and reports to help improve the clarity and accessibility of complex financial data. Incorporating data into the money flow will provide significant improvements for businesses seamus smith executive vice president and group president at fis told pymnts.

Organizations that are early adopters and larger-scale consumers of new technology will accelerate ahead. Despite its promise the adoption of ai in the back office is not without challenges. Resistance often stems from two primary sources: cultural inertia and perceived complexity. Finance teams have traditionally been cautious about adopting new technologies often prioritizing reliability over innovation. Convincing stakeholders to invest in ai requires a clear articulation of the return on the investment.