AI in Treasury 2026: Impact after the hype

AI and the end of banking?

Since almost forever, banks have been the unquestioned center of corporate Treasury. But AI, programmable money, stablecoins and tokenized assets are challenging assumptions that have shaped financial infrastructure for generations.

Some believe these technologies will make banks less relevant. Others argue they'll make them more important than ever—just less visible.

Rather than chasing predictions, we'll examine the forces reshaping finance today—and separate genuine structural change from the latest wave of hype.

The questions at the heart of this conversation:

• Why some predict "the end of banking"—and what they're getting wrong
• How AI, stablecoins and tokenized money market funds could reshape corporate liquidity
• Which parts of banking are likely to disappear—and which become even more valuable

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AI and cash flow forecasting: Who needs it?

Every finance conference in recent years has promised that AI will transform forecasting. But treasury professionals have a habit of asking awkward questions. If the forecast already works, why change it? If AI is genuinely better, where's the evidence? And if no one can explain how it arrived at a number, should anyone trust it?

This session takes the sceptic's perspective. Rather than assuming AI belongs in cash forecasting, it asks whether it has earned its place.

The questions that drive the discussion:

• What problem is AI actually solving in cash forecasting?
• Is better forecasting about smarter algorithms—or better data?
• How should treasury leaders evaluate AI when accuracy, explainability and accountability all matter?

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AI and payment fraud: When the bad guys have AI too

Treasury has always been built on trust. Trust in people, in processes, and in controls designed to ensure that the right payment reaches the right recipient for the right reason.

Artificial intelligence is beginning to challenge each of those assumptions.

This conversation explores what happens when sophisticated AI is no longer the exclusive advantage of large organisations, but a tool equally available to fraudsters, insiders and organised criminal networks. Unlike corporations, they have no compliance obligations, governance frameworks or audit trails slowing them down.

Rather than asking how AI can make treasury more efficient, this session asks a more uncomfortable question: are the controls that have protected corporate payments for decades still designed for the threats treasury faces today?

The must-answer questions driving this discussion:

• How is AI changing the economics and sophistication of payment fraud?
• Which treasury controls become more important—and which are quietly becoming less effective?
• In a world where identities, voices and evidence can be fabricated, what does "trust" in corporate payments actually mean?

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AI and treasury data: Ownership, control, authenticity & trust

AI is rapidly finding its way into Treasury—but beneath the excitement lies a more uncomfortable question: can a function built on accuracy, control and auditability truly trust a technology that is still evolving?

This session moves beyond the familiar conversation about productivity gains to examine the foundations of AI in Treasury. From fragmented data and governance challenges to ownership, explainability and accountability, we'll explore what it will take for AI to become a trusted part of financial decision-making—and whether Treasury is as ready for AI as AI is for Treasury.

The must-answer questions driving this discussion:

• Is the biggest barrier to AI in Treasury the technology itself—or Treasury's readiness to use it?
• Can AI ever be trusted with decisions that demand complete transparency, auditability and control?
• Does AI solve Treasury's data challenges—or simply expose them?

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AI, treasury & procurement: The blind spot finance can't afford

Treasury has always been measured by control, precision, and protecting the enterprise from risk. But AI is changing where valuable financial intelligence comes from—and much of it sits outside treasury.

This conversation explores whether finance's traditional operating model is becoming a liability in an AI-powered organisation. As procurement, supply chains, and supplier networks become increasingly intelligent, treasury faces a new challenge: how do you manage risk if you're only looking at part of the picture?

The must-answer questions that make this session essential:

• Is AI making functional silos more dangerous than ever?
• What can treasury learn from procurement that it has traditionally ignored?
• Does AI reduce financial risk—or simply replace familiar risks with new ones?
• What happens when supplier intelligence becomes financial intelligence?

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AI and the last human treasurer

AI has dominated treasury conversations for years. The promises have been bold. The predictions even bolder. But beyond the headlines and product demos lies a much bigger question: what will Treasury actually look like once AI becomes business as usual?

This session explores how AI is reshaping treasury processes, changing the nature of decision-making, and redefining the role of the treasurer. From automation and judgement to trust and accountability, we'll examine where humans still create value—and where they may no longer need to.

The must-answer questions at the heart of this session:

• Which treasury processes are changing first as AI moves from hype to adoption?
• What skills will define the next generation of treasury professionals?
• Will AI simply support better decisions—or fundamentally change who makes them?

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AI in Treasury: Real value beyond the hype

Everyone says AI is transforming Treasury. But for many finance professionals, one question remains unanswered: why?

This conversation challenges the assumptions behind AI in Treasury software. Rather than accepting AI as inevitable, it asks where intelligent systems genuinely outperform automation, where they fall short, and whether the technology is solving problems Treasury teams actually have—or simply creating new expectations.

The must-answer questions driving this conversation:

• Where does AI genuinely create value that traditional automation cannot?
• What questions should every Treasury team ask before believing an AI business case?
• By 2030, what will AI have fundamentally changed—and what will remain unmistakably human?

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