Cash forecasting is entering a new era. Rising volatility, liquidity pressures, and unpredictable cash flows are pushing treasury teams to rethink the tools and data models they rely on. At the same time, AI is rapidly emerging as a powerful enabler—improving speed, visibility, and anomaly detection while exposing the underlying weaknesses that traditional forecasting often hides.
This EuroFinance Deep Dive (supported by TIS) combines market data, treasury surveys, and real-world perspectives from leading corporates to show how AI is reshaping cash forecasting today—and what foundations need to be in place to see meaningful results.
Key Learnings
1. The state of forecasting today
Forecast accuracy is harder to achieve as volatility, liquidity constraints, and funding costs intensify. Treasury teams increasingly rely on forecasts for short‑term decisions, yet data quality, consistency, and integration remain the biggest obstacles to accuracy.
2. What AI can—and cannot—solve
AI accelerates analysis, improves short‑term visibility, and identifies anomalies faster than traditional tools. But AI cannot compensate for fragmented systems, weak data governance, or inconsistent assumptions. Instead, it amplifies underlying issues.
3. How treasurers are using AI in practice
46% of treasurers are actively evaluating AI forecasting solutions, but adoption remains measured. AI is being used to enhance forecasting cadence, challenge assumptions, and improve insight—not to replace treasury judgement.
4. The organisational foundations required for AI forecasting
Treasurers emphasize the need for clean data, reliable system integration, defined workflows and scenario discipline. Without these fundamentals, AI is more likely to amplify errors than improve outcomes.
Why This Matters Now
As more corporates explore AI in forecasting, the report makes one theme unmistakably clear: AI strengthens the fundamentals of forecasting—it does not replace them.
Treasury leaders who succeed will be those who treat AI as a catalyst for better decision‑making and more robust data discipline, not as a shortcut. This Deep Dive Report gives you the clarity needed to understand where AI adds value and where foundational improvements must come first.
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