David Schmidt, Editor in Chief & Co-Founder at Trade Credit & Liquidity Management and Partner at Quote to Cash Solutions LLC
30 January, 2026
Artificial Intelligence (AI) is rapidly transforming the landscape of treasury and finance, emerging as one of the most critical topics for treasury, credit, and other finance leaders today. Far beyond hype, the adoption and integration of AI technologies are swiftly advancing within corporate treasury and finance teams, signaling a fundamental shift in how these functions operate and deliver value.
Staying ahead in this evolving landscape requires understanding these trends, investing in AI capabilities, and shaping teams to work effectively alongside these technologies. The 2025 AI in Treasury Survey Report from Strategic Treasurer provides a comprehensive, evidence-based roadmap to navigate this dynamic journey.
For treasury, credit, and other finance executives, this report offers critical insights into the accelerating AI transformation in treasury. Embracing AI is not simply about automation; it is about harnessing powerful, intelligent tools to optimize cash flow forecasting, risk evaluation, reconciliation, and strategic financial decisions that underpin growth and resilience.
Key Highlights
- Strong Momentum in AI Adoption: A significant 22% of companies are already deploying Agentic AI within their finance or treasury departments, marking early movement beyond experimentation to active operational use. Additionally, nearly 70% of respondents personally use AI, with half now leveraging it for work-related treasury functions.
- Widespread Growth Expectations: An overwhelming majority (86% to 87%) of AI users anticipate expanding their usage over the next year, underscoring broad confidence in AI’s growing role across financial decision-making and operational tasks.
- Transformative Impact Ahead: More than three-quarters of finance professionals foresee AI becoming either a transformative driver or a significant enabler in treasury within three to five years. This expectation highlights AI’s potential to streamline workflows, enhance accuracy, and uncover new strategic insights.
- Key Operational Benefits: AI adoption is particularly favored for solving complex treasury challenges. Cash forecasting accuracy jumps from 65% to 76% expectation of AI support year-over-year, and manual reconciliation task automation climbs from 55% to 62%. Risk management and strategic analysis are also areas of rising AI application.
- AI Embedded in Core Systems: Use and planned adoption of AI tools within treasury aggregators, cash management platforms, ERPs, and treasury management systems are rapidly increasing, pointing to AI’s growing embedment within daily financial processes.
- Workforce Implications: Nearly half of respondents anticipate AI will reduce staffing levels in non-treasury finance roles, while about 31% expect decreases within treasury teams, indicating operational efficiencies may alter team structures.
Leading Opportunities for AI Applications
The Report identifies several AI applications that are most effective in treasury management based on survey findings. The top AI uses in treasury include:
- Cash Forecasting Accuracy: AI applications supporting improved cash forecasting have seen increased expectation and adoption, rising from 65% in 2024 to 76% in 2025. AI helps analyze vast data sets and predict liquidity needs more precisely.
- Payment Security and Fraud Prevention: AI enhances detection of fraudulent activity and payment security through pattern recognition and anomaly detection.
- Aggregation and Normalization of Data: AI systems are effective at consolidating and normalizing data from multiple sources, aiding visibility and decision-making.
- Risk Management: AI aids in identifying, evaluating, and managing treasury-related risks, helping to improve strategic decision-making under uncertainty.
- Workflow Automation: Newer AI uses include running intelligent agents to support workflows across multiple systems, increasing treasury operational efficiency.
- Manual Reconciliation Tasks: AI is increasingly applied to automate manual reconciliation processes, with expectations rising from 55% to 62%. This reduces errors and frees staff for higher-value tasks.
- Draft Report Creation: AI tools assist in generating initial drafts for internal treasury reports, streamlining workflow and improving efficiency.
Overall, these AI applications address critical treasury challenges, enabling better forecasting, reducing manual, error-prone tasks, enhancing security, and supporting analytics-driven decision-making, thereby transforming treasury management practices.
Editor’s Note: This article originally appeared for the online publication Strategic Trader. You can find more at https://tradecredit.substack.com/ and https://strategictreasurer.com/. David is also a contributor to Emagia’s 2005-2006 executive white paper series – you may find his work on Deductions, Collections, and E-Invoicing at https://www.emagia.com/resources/white-papers/.
