Corporate treasury has evolved from a back-office function into a strategic command centre, and AI is accelerating this transformation by shifting cash management from reactive forecasting to proactive orchestration.

Treasurers today are expected to manage liquidity with precision, forecast cashflows accurately, and respond to market disruptions in real time. Yet, many are held back by fragmented banking relationships, legacy systems, and manual processes. Forecast variances exceeding 20%1 and excessive liquidity buffers of 15–20%2 are symptoms of outdated tools. According to Capgemini’s World Payments Report, over 60%3 of banks fail to offer real-time cash forecasting, and more than half still rely on manual reconciliation. Clearly, a new paradigm is needed – one powered by AI.

Treasury teams face mounting challenges:

  • Global volatility: Geopolitical tensions, supply chain disruptions, and interest rate swings strain forecasting models.
  • Manual workflows: Spreadsheets and siloed systems slow down decision making and increase errors.
  • Fragmented tech ecosystems: Poor integration across banks and Enterprise Resource Planning (ERP) delays reconciliation and reporting.
  • Limited instant payments: Many corporates still rely on batch processing, missing out on real-time liquidity optimization.

These inefficiencies trap capital and reduce agility – at a time when every basis point matters.

AI: The game-changer for treasury

With AI, treasury functions can become self-driving, delivering up to 90% forecast accuracy through real-time data and predictive analytics.

Fixing the fundamentals with GenAI

GenAI can help address foundational treasury challenges.

  • Data aggregation: Automates extraction and normalization across banks and ERPs, offering a unified view of cash positions.
  • Invoice parsing: Reads and reconciles invoices and payment confirmations, reducing errors in multi-currency environments.
  • Instant payment adoption: Analyzes liquidity trends to recommend optimal disbursement timing, leveraging instant payment infrastructure.

Forecasting reimagined

AI transforms forecasting into a strategic asset.

  • High-accuracy predictions: AI models like neural networks analyze vast datasets to detect patterns beyond human capability. A leading global financial institution’s new tool4 has been instrumental in helping corporate customers such as Domino’s Pizza reduce manual work by almost 90%, using AI to analyze and forecast cashflows.
  • Adaptive pattern recognition: Machine learning (ML) adjusts forecasts instantly based on internal and external signals. A large global bank cash management solution5 enables firms to control risks through automated hedging with real-time monitoring, while interest tools offer scenarios for proactive exposure management.
  • Scenario analysis: AI enables stress testing with thousands of simulations, supporting contingency planning for currency shocks or supply chain disruptions. A leading cash management platform5 connects human judgement and machine learning, letting users create scenarios on top of a base forecast by overriding forecast parameters.

GenAI copilots further empower treasurers to interact with data using natural language – asking questions like, “How have my FX exposures changed?” and receiving instant insights.

What’s next: The future of treasury innovation

The convergence of AI, blockchain, and open banking is redefining treasury operations:

  • AI + blockchain: Combines transparency and speed with decentralized, tamper-proof data flows. One of the largest financial institutions has a platform6 that uses blockchain to create a transparent network – one that enables real-time settlement and programmable money flows to streamline its treasury operations.
  • Open banking APIs: Enable real-time connectivity and treasury optimization. A top global French bank offers API-driven treasury platform7 that enables clients to access APIs for various services.
  • Agentic AI: Introduces intelligent digital collaborators capable of reasoning and proactive decision making.

Autonomous treasury management powered by agentic AI will transform cash operations into dynamic, data-driven processes with minimal manual intervention. To defend market share and meet evolving treasurers’ needs, banks need to evolve their cash management solution. To embark on this journey of unlocking agility, accuracy, foresight, and efficiency in the corporate treasury, banks and payment firms have to focus their offering on paving a three-stage pathway for the corporates – with the goal of reaching treasury capabilities that are truly next-gen, cutting-edge, and intelligent.

3 steps to an intelligent, next-gen corporate treasury

  1. Fix: the fundamentals of data, integration, and visibility
    • Centralize data across banks, ERPs, and payment systems.
    • Automate reconciliation and invoice processing.
    • Improve data quality and real-time visibility.
  2. Embed AI to automate, predict, and prescribe
    • Deploy AI/ML models for forecasting and anomaly detection.
    • Use GenAI copilots for data queries, reporting, and insights.
    • Enable predictive liquidity planning and risk modelling.
  3. Unlock autonomous treasury and strategic foresight
    • Move towards self-driving treasury functions.
    • Automate investment decisions, FX hedging, and working capital optimization.