Artificial intelligence is no longer a future-state discussion for treasury teams. Across the financial services industry, organizations are actively exploring and implementing AI to improve decision-making, streamline operations, and unlock new efficiencies. Yet despite growing adoption, many institutions are encountering a familiar challenge: technology is moving faster than organizational readiness.
According to Alithya's recent Financial Services Industry Trends Report, 74.3% of organizations are already using AI, at least moderately, to support decision-making. At the same time, 66.2% identified a lack of internal expertise and skills as the biggest barrier to successful AI adoption. This suggests that while the technology itself is becoming more accessible, the ability to scale it effectively remains a significant hurdle.
AI adoption has reached the mainstream
The conversation around AI has evolved dramatically over the past few years. Financial services institutions are no longer questioning whether AI has a place in treasury and finance functions. Instead, they are exploring how to apply it to real business challenges.
Common AI use cases include:
- Improving forecasting accuracy
- Enhancing liquidity management
- Supporting scenario analysis
- Accelerating reporting processes
- Identifying trends and anomalies in large data sets
As adoption increases, treasury leaders are beginning to recognize that success depends on far more than selecting the right platform or tool. The organizations generating the greatest value from AI are investing in the people, processes, and governance structures required to support long-term adoption.
The real challenge is not technology
Historically, large transformation initiatives were constrained by technology limitations. Today, the opposite is often true.
The marketplace offers a growing number of AI-powered capabilities that can be integrated into treasury environments. Yet many organizations struggle to progress beyond pilot projects because they lack the internal capabilities needed to operationalize and govern those solutions.
Treasury teams are increasingly being asked to:
- Evaluate emerging AI use cases
- Understand data requirements and quality standards
- Assess risk and compliance implications
- Establish governance frameworks
- Measure business outcomes
- Manage organizational change and user adoption
These responsibilities often extend beyond the traditional scope of treasury operations. As a result, organizations find themselves with access to powerful technology but without the expertise needed to maximize its potential.
Why treasury skills matter more than ever
Treasury has always sat at the intersection of finance, risk, and strategy. AI only amplifies this reality.
While technology providers can deliver tools, treasury leaders remain responsible for ensuring those tools support business objectives, comply with regulatory requirements, and produce trustworthy outcomes.
Success requires a combination of capabilities, including:
- Treasury domain expertise: Teams must understand the underlying business processes, decision frameworks, and risk considerations that AI solutions are intended to support.
- Data and analytics skills: AI outcomes are only as effective as the data that informs them. Treasury leaders need confidence in data quality, governance, integration, and reporting structures.
- Governance and risk management: As AI becomes embedded in decision-making processes, organizations must ensure transparency, accountability, and appropriate controls.
- Change management: Perhaps most importantly, employees must understand how AI supports their work and how to use new capabilities effectively.
Without these foundational elements, even the most advanced technology investments can struggle to deliver measurable business value.
Automation is only the first step
Our survey also found that 72.7% of respondents identified operational efficiency as the leading area for automation investment.
This is not surprising. Many treasury functions continue to rely on manual processes, spreadsheet-based workflows, and resource-intensive reporting activities. Automation offers a clear opportunity to reduce effort, improve consistency, and free teams to focus on higher-value work.
However, treasury leaders should be careful not to view automation as the end goal.
The greatest opportunity lies in moving beyond task automation toward intelligent decision support.
Organizations that successfully combine automation, analytics, and AI are better positioned to:
- Improve forecasting accuracy
- Respond more quickly to changing market conditions
- Strengthen strategic planning
- Enhance risk visibility
- Support executive decision-making
In other words, the ultimate objective is not simply doing the same work faster. It is enabling better business decisions.
Confidence is growing, but readiness remains uneven
One encouraging data point from our research is that 75.9% of respondents expressed confidence in their ability to meet evolving compliance requirements.
This suggests that many financial institutions recognize the importance of governance and controls as they modernize their operations.
However, confidence in compliance readiness should not be mistaken for complete organizational preparedness. As AI use expands, institutions will need ongoing investments in skills development, operating model evolution, and governance maturity.
The challenge facing many organizations is not whether AI can create value. The challenge is creating the organizational capabilities required to scale that value sustainably.
Closing the gap between technology and business value
The most successful treasury transformations are not driven by technology alone. They are built on a foundation of strong processes, high-quality data, effective governance, and skilled teams who understand how to align innovation with business objectives.
Organizations that focus exclusively on technology risk falling short of their desired outcomes. Those that invest equally in people, processes, and adoption are far more likely to realize the full benefits of AI and automation.
Alithya helps financial institutions bridge this gap. Our team combines deep financial services expertise with technology, data, governance, and change management capabilities to help organizations modernize treasury operations, implement AI-enabled solutions, strengthen decision-making processes, and drive sustainable business outcomes. Whether organizations are exploring their first AI use cases or scaling enterprise-wide transformation initiatives, we help ensure that technology investments translate into measurable value. Contact us for more information.