The adoption of artificial intelligence in enterprise treasury management is accelerating, enabling businesses to replace manual spreadsheets with automated data pipelines as corporate finance teams confront mounting pressure from market volatility, regulatory complexity and the rapid digitisation of financial operations.
From spreadsheets to automated finance ecosystems
For decades, corporate treasuries have relied heavily on spreadsheets to manage cash positions, liquidity forecasts and risk exposure. While flexible, these tools have become increasingly inadequate in an environment defined by real-time markets and complex compliance requirements. AI-enabled platforms are now changing that model, offering continuous data integration across banks, ERP systems and trading platforms.
According to recent industry discussions, automation is no longer optional. Finance leaders are being pushed to modernise by tighter reporting standards, faster settlement cycles and growing expectations around transparency. AI-driven treasury systems consolidate fragmented data sources into unified dashboards, allowing teams to move from reactive reporting to proactive decision-making.
Treasury leaders highlight operational realities
Speaking on the evolving role of corporate treasuries, Ashish Kumar, head of Oracle Sales for North America at Infosys, and CM Grover, chief executive of IBS FinTech, outlined how enterprises are shifting toward automated financial infrastructures.
They noted that many finance departments are still burdened by manual reconciliation and siloed workflows, limiting visibility and increasing operational risk. AI-based treasury platforms address this by creating automated data pipelines that ingest balances, payments and exposures in near real time. This allows treasurers to focus on strategy rather than administration, while also improving audit readiness and regulatory compliance.
Managing volatility, compliance and digital transformation
Global market instability has sharpened the need for accurate cash forecasting and risk modelling. AI tools can analyse historical patterns alongside live market data to generate forward-looking insights, helping companies anticipate liquidity needs and hedge currency or interest-rate exposure more effectively.
At the same time, regulatory demands continue to expand across jurisdictions, requiring faster and more detailed reporting. Automated treasury systems embed compliance into daily operations, reducing reliance on manual checks and lowering the risk of costly errors. Digital finance initiatives, including real-time payments and cross-border transaction platforms, further reinforce the need for integrated, intelligent treasury architectures.
Strategic implications for corporate finance
The shift toward AI-powered treasury management represents a broader transformation of corporate finance. Rather than operating as back-office functions, treasuries are becoming strategic hubs that support capital allocation, investment planning and enterprise-wide risk management.
By replacing spreadsheets with automated pipelines, organisations gain cleaner data, faster insights and stronger governance. This transition also supports scalability, allowing finance teams to manage growing transaction volumes without proportional increases in headcount. For multinational firms, centralised treasury platforms provide a single source of truth across currencies, regions and banking partners.
A new operating model takes shape
As AI adoption deepens, corporate treasuries are expected to evolve into digitally native operations, tightly integrated with broader enterprise systems. The technology is already reshaping how businesses manage liquidity, respond to market shocks and meet regulatory expectations.
What is emerging is a new operating model for finance: one built on continuous data flows, predictive analytics and automated controls. For organisations navigating today’s volatile economic landscape, AI-enabled treasury management is rapidly becoming a foundational capability rather than a competitive advantage.
Newshub Editorial in Europe – 20 February 2026
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