Treasury Trends 2026: An outlook

Treasury teams are heading into 2026 with a familiar problem—more volatility, more stakeholders, and more expectations. The pressure isn't abstract. Leadership still wants fast, confident answers on liquidity, risk, and funding decisions, even when the underlying reality is fragmented: multiple systems, uneven bank connectivity, and data that arrives late or in inconsistent formats. In that environment, "good enough" visibility is no longer good enough—because decisions made on partial or outdated information create avoidable cost, risk, and internal friction.

That's why the most essential treasury trends for 2026 are about building a connected, decision-ready operating model: integrating the data that actually drives outcomes (from cash to working capital and beyond), moving from spreadsheet-bound reporting toward more dynamic modelling and scenario analysis, and using automation to remove high-volume manual work so teams can focus on oversight and judgment. At the same time, controls and fraud prevention are evolving into continuous disciplines—because faster processes and more connectivity also raise the stakes if governance doesn't keep up.

In this article, we'll break down the practical trends shaping treasury in 2026—and what they mean for how treasury teams organise work, modernise connectivity, and strengthen controls.

AI becomes an embedded spectrum, not a single feature.

A defining trend for 2026 is the way treasury teams talk about AI: not as one tool, but as multiple types of intelligence working together—predictive approaches for forecasting, causal approaches for understanding drivers, automations, conversational interfaces for interrogating reports, and generative assistance for drafting proposals (for example, in FX-related work) within policy constraints. The implication is clear: "AI in treasury" won't be a single module—it will be woven into daily workflows.

At the same time, expectations for 2026 are grounded: adoption is often described as iterative, with experimentation and "small steps" building momentum. Treasury teams will increasingly trial use cases, compare outcomes to reality, and scale what proves reliable.

Integration expands beyond treasury's classic boundaries

Another 2026 trend is that treasury outcomes depend on more than treasury data. The focus is shifting from connecting "typical treasury areas" (cash management and forecasting) to integrating upstream operational inputs—working capital and supply chain—across not just short horizons but also medium- and long-term views. This also underscores a recurring theme: data quality is a gating factor for the usefulness of any advanced analysis (AI-supported or otherwise).

The leaner the system landscape, the faster the value

A consistent perspective is that the speed of progress by 2026 will largely depend on the groundwork already in place—particularly how "lean" and standardised the systems and banking setup are. Examples include operating with a single ERP rather than a fragmented landscape, and having a clear core banking strategy (a small set of global relationships rather than many local ones) to reduce complexity and enable more consistent automation and analysis. In short, the 2026 advantage is less about chasing the newest concept and more about making the data environment workable.

From spreadsheets to dynamic models and scenario analysis

For 2026, "dynamic models" and better trend recognition are positioned as a practical response to volatility—especially where spreadsheets struggle to keep up. Scenario analysis is highlighted not only for cash, but also for risk, signalling a shift in treasury routines: away from static reporting cycles and toward more adaptive decision support.

Automation targets high-volume work—and frees time for strategic work

A notable 2026 productivity direction is automating high-volume, low-value activities to free capacity for lower-volume, high-value work. This also links to speed: reducing time-to-market by translating written requirements into prototypes more quickly (reducing the commercial drag of long delivery cycles). Taken together, the trend is that automation isn't only "efficiency"—it becomes a survival and competitiveness lever, because it reallocates scarce human time to the work that influences resilience and outcomes.

Treasury fraud prevention becomes continuous and organisation-wide

By 2026, fraud and controls are framed as topics that receive full attention only after something goes wrong—yet the operational reality is that treasury often sits near the end of a broader process involving multiple departments. Expert opinions emphasise that effective control frameworks require a top-level mandate, defined workflows, cross-departmental awareness, and periodic internal testing of the organisation's response to threats. It is also described as continuous rather than a one-off project.

There is also a clear direction on "how" treasury behaves under pressure: unusual payment requests should be challenged and verified via direct confirmation, and as fraud tactics evolve, organisations will increasingly use AI to detect fraud in real time time as well—meeting AI-enabled criminals with AI-enabled defence.

The connective tissue: APIs, model access to structured data, and reporting layers

Although "APIs" are sometimes treated as old news, they remain relevant, mainly when teams still rely on end-of-month consolidations and manual data gathering. Beyond APIs, a newer concept is raised: giving models access to structured data so they can ingest, analyse, and produce outputs—positioned as a different layer from simply moving data from A to B. Reporting layers (with examples like BI-style interpretation of structured context) are also treated as part of the overall stack that makes "connected treasury" real.

The human side of 2026: Capability, courage, and top support

A central theme in 2026 is that people, processes, and systems rise (or fail) together. Digitised processes require re-engineering and digital capability within the team; this is more of a resource reconfiguration story than a simple headcount reduction story. There's also an explicit signal that internal support for digital transformation matters, as does the treasury's willingness to claim a strategic place at the table.

At the same time, the "2026 agenda" discussion returns to practical blockers: budget, the need for top-down support, and the challenge of doing more with leaner treasury organisations. The direction is that becoming a strategic partner to leadership requires the organisation to enable it through mandate, resources, and technology adoption that is "not an option anymore," but a competitiveness requirement.

What to prioritise in 2026

Therefore, treasury teams planning for 2026 will likely focus on:

• Connecting data across cash, forecasting, and the wider operational inputs that drive treasury outcomes (working capital, supply chain, procurement), with explicit attention to data quality.
• Reducing complexity where possible (systems landscape and banking setup), because complexity directly slows down the usefulness of automation and AI assistance.
• Moving away from static spreadsheet-led cycles toward more dynamic models and scenario analysis for both cash and risk.
• Automating high-volume operational work to release time for strategic, enterprise-wide contribution, and using controlled experimentation to scale what works.
• Treating controls and fraud prevention as continuous, organisation-wide disciplines that need mandate, workflows, awareness, and periodic testing, not "a treasury project."

Closing thought

The 2026 picture is not "AI replaces treasury." It is treasury teams using a connected ecosystem, supported by process redesign, better data foundations, and layered automation to escape constant operational firefighting and contribute more directly to resilience, risk management, and leadership decision-making. The differentiator is not hype; it's readiness: the groundwork, the mandate, and the capability to turn technology into reliable outcomes.