Seen Here: Madimetja Rapudi, Head of Liquidity Management South Africa at Standard Bank Corporate and Investment Banking (CIB) Photo Credit: Supplied
03 November 2026 – Corporate treasury is approaching a significant turning point as artificial intelligence (AI), particularly agentic AI, promises to transform how businesses manage liquidity, assess financial risks and make critical decisions.
After more than a decade of investment in digital transformation, which has given organisations greater visibility over cash positions, improved forecasting and automated routine processes, the next frontier is no longer simply accessing better information. It is turning that information into intelligent, timely and actionable decisions.
For corporate treasurers, this shift could fundamentally reshape the function, moving it beyond traditional monitoring, reporting and reconciliation towards more proactive decision-making, intelligent workflows and increasingly automated execution.
According to Madimetja Rapudi, Head of Liquidity Management South Africa at Standard Bank Corporate and Investment Banking (CIB), agentic AI presents an opportunity to fundamentally rethink the role of treasury within modern organisations.
The technology enables systems to analyse information, identify emerging patterns, detect exceptions and recommend actions based on predefined policies and risk parameters. Rather than simply displaying information on dashboards, these systems can help treasury teams understand what has changed, why it matters and what action may be required.
The result is a potential shift from information processing to strategic financial decision-making.
Moving beyond visibility to intelligent action
Treasury departments operate in increasingly complex financial environments, where liquidity positions, funding requirements, foreign exchange exposures and market conditions can change rapidly.
Traditionally, treasury professionals have had to gather information from multiple systems, manually investigate discrepancies and analyse data before determining the appropriate response.
Agentic AI could significantly streamline this process.
Imagine a treasury function that begins each morning with an intelligent briefing identifying excess liquidity, highlighting entities approaching overdraft limits, flagging unusual cash movements and identifying foreign exchange exposures nearing approved thresholds.
Instead of spending hours searching for potential problems across different platforms, treasury professionals could receive prioritised insights, supporting analysis and recommended courses of action.
This progression from data to insight, recommendation and ultimately execution represents a major opportunity for the future of corporate treasury.
Rapudi believes the real value lies in empowering treasury professionals to spend less time assembling information and more time applying their expertise to decisions that have a meaningful impact on business performance.
A changing role for transaction banks
The implications of agentic AI extend beyond corporate treasury departments to the broader banking industry.
Historically, corporate banking platforms have focused on providing clients with access to account balances, payment functionality, transaction records and financial reports.
However, as technology advances and client expectations evolve, businesses are increasingly likely to demand more sophisticated services that go beyond transactional capabilities.
Treasurers will want platforms that can explain movements in their cash positions, identify the reasons behind unexpected changes and highlight the potential implications for their organisations’ liquidity.
This creates an opportunity for transaction banks to evolve from providers of financial information into providers of actionable intelligence.
For banks, competitive advantage will increasingly depend on combining advanced technology with treasury expertise, strong connectivity and an understanding of clients’ financial objectives.
However, Rapudi cautions that technological sophistication alone will not be enough.
Trust will remain fundamental. Corporate clients must be confident that AI-generated recommendations are transparent, explainable and aligned with their interests.
Governance must come before autonomy
While agentic AI offers significant opportunities for efficiency and improved decision-making, its adoption also raises important questions about accountability, risk management and financial control.
Treasury is responsible for some of the most critical financial activities within an organisation, including cash management, liquidity planning, financing and financial risk management.
These responsibilities demand strong governance structures and clearly defined decision-making authority.
Rapudi argues that the future of AI in treasury should not be measured by how much autonomy organisations can give machines, but by how responsibly they deploy the technology.
He describes AI adoption as a spectrum, ranging from systems that monitor activity and generate alerts to those that recommend actions, prepare instructions for approval and, in carefully controlled circumstances, execute predefined transactions.
The level of autonomy should depend on the nature of the activity, the financial exposure involved, the associated risks and the clarity of the policies governing the process.
Routine, repetitive and highly structured activities may be suitable for greater automation. However, decisions involving significant financial exposure, complex judgement or heightened fraud risks will continue to require human oversight.
The priority, therefore, should not be maximum automation, but responsible automation.
Why human judgement will remain critical
Despite the growing capabilities of AI, Rapudi maintains that treasury will remain fundamentally a human discipline.
While technology can process vast amounts of information, identify patterns and apply rules consistently, it cannot fully replicate commercial judgement, contextual understanding, strategic thinking and accountability.
One of the emerging risks is the possibility of organisations becoming overly dependent on AI systems simply because they have demonstrated consistent accuracy.
Effective governance requires more than having a human approve an AI-generated recommendation. Treasury professionals must understand the assumptions behind recommendations, examine the methodologies used and have the ability to challenge or override decisions when circumstances demand it.
This will require a new approach to skills and responsibilities within treasury departments.
Rather than spending much of their time gathering and processing information, professionals will increasingly be expected to interrogate recommendations, assess alternative scenarios, evaluate commercial implications and exercise informed judgement.
The relationship between people and technology will therefore become one of collaboration rather than replacement.
The starting point is the business problem, not the technology
Despite the excitement surrounding agentic AI, Rapudi believes organisations should resist the temptation to begin their transformation journeys by investing in technology without first understanding the challenges they need to solve.
Instead, businesses should identify where fragmented information, repetitive analysis and manual processes are slowing down decision-making.
Which activities consume disproportionate amounts of time? Where are recurring exceptions requiring unnecessary investigation? Which treasury policies are sufficiently clear to be translated into automated processes?
Answering these questions can help organisations determine where AI can deliver meaningful value.
In some instances, the solution may not require agentic AI at all. Improved processes, stronger system integration or conventional automation may achieve the desired outcome more effectively.
The organisations that benefit most from AI will not necessarily be those deploying the most advanced technology. They will be those that understand their operational challenges and apply appropriate solutions, supported by robust governance and clear accountability.
The future of treasury is intelligent, connected and human-led
As businesses navigate increasingly complex financial environments, the ability to make timely and informed decisions will become an increasingly important source of competitive advantage.
Agentic AI offers treasury teams an opportunity to move beyond traditional reporting and monitoring towards a more intelligent operating model, where information is continuously analysed, potential risks are identified earlier and decisions are supported by actionable recommendations.
For transaction banks, it also signals an opportunity to rethink how they serve corporate clients, moving beyond transactional platforms towards more intelligent, insight-driven financial partnerships.
However, the technology’s long-term value will depend on maintaining the right balance between automation, human expertise and financial control.
As Rapudi concludes, the question is no longer whether AI will play a role in treasury. It already does.
The real challenge is determining how organisations can combine human expertise with artificial intelligence to make better financial decisions, faster, without compromising governance, accountability or control.
Ultimately, the future of treasury will not belong to organisations that hand decision-making over to machines, but to those that use intelligent technology to empower people to make better decisions.
The next era of treasury transformation will be defined not by how much information organisations can see, but by how intelligently they can act on it.
