The future of Asian banking isn’t ‘AI-first’ – it’s ‘fearless-first’

The biggest temptation is to treat AI as a “bolt-on feature.”

As Asia’s financial sector is discovering, the brave banks that trust AI to help rewrite their organisations – not just automate them – will seize tomorrow’s profits. Playing it safe is now the riskiest move of all.

“88% Deployed, 39% profiting” – The C-Suite crisis nobody’s talking about
Every week brings new headlines across Asia about how regional banks are leading the world in adopting artificial intelligence. Eighty-eight percent say they’ve deployed the latest technology in customer service, risk analysis, and more.

But behind closed boardroom doors, a very different conversation is happening.

CEOs and CFOs are asking hard questions: “Where’s the ROI?” “Why did we spend millions on AI pilots with so little to show for it?” Because dig deeper and two numbers flash red: 88% AI deployed, but only 39% profitably using it.

After all those glossy pilots – from chatbots to back-office automation – more than half of those banks see little bottom-line change. Executives are quietly panicking as competitors tout the same AI wins whilst their own balance sheets tell a different story. The critical question executives now demand answers to: why are so many pilots unable to cross the profitability chasm?

And here's the uncomfortable truth that almost no one in the industry wants to say out loud: The technology works fine. The problem is everything else.

The elephant in the boardroom 
Walk into any banking conference in Asia and you’ll hear endless panels on “AI strategy” and “next-generation algorithms.” What you won’t hear? The messy and uncomfortable work of organisational transformation.

It’s the industry’s worst-kept secret. Vendors won’t talk about it because they’re selling technology, not change management. And bank executives? Many would rather invest in another AI pilot than confront the reality that their hundred-year-old organisational structures are the real obstacle to AI profitability.

The conversation is stuck on the wrong question. Banks keep asking: “Which AI should we buy?” when they should be asking: “How fundamentally must we reorganise ourselves for AI to actually work?”

The 88-to-39 gap is really telling us: the real barrier isn’t algorithms – it’s the willingness, and courage, to be more than “AI adopters.” And the industry conversation is conspicuously silent on this front.

From generative to agentic AI – but still organising like it’s 1924
When generative AI exploded onto the scene, banks rushed to invest and headline-chase. But the next phase is quietly underway: Agentic AI.

What’s the difference? Generative AI teaches machines to express; Agentic AI systems learn to collaborate. In modern finance, this means unlocking teamwork between humans, bots, and data advisors who each take on part of decision-making and execution.

An AI agent doesn't just flag financial risks – it negotiates with other systems, proposes responses, and learns from outcomes. The conversation shifts from reducing costs to reimagining how profits are made.

But here’s the problem executives are discovering the hard way: You can’t run a collaborative AI system inside a command-and-control organisational structure. It's like running Formula One racing on horse-and-buggy roads. The technology is ready. Your org chart isn’t.

You can’t bolt transformation on – and that’s why your AI investments aren’t paying off
The biggest temptation is to treat AI as a “bolt-on feature.” Buy the latest software, hook it to your old systems, and hope that profitability magically rises. But as frustrated executives are now realising – hope isn’t a strategy.

This is the inconvenient truth the industry needs to face: It’s not enough to deploy an AI agent by plugging in an API – it requires process redesign, organisational restructuring, and employee retraining. Yet when was the last time you heard a banking keynote dedicate serious time to reorganising power structures, redefining job roles, or dismantling approval hierarchies?

The conversation focuses on the shiny object – the AI itself – whilst ignoring the elephant: your bank’s 20th-century organisational DNA actively working against 21st-century technology.

The true winners are those banks willing to rethink centuries-old assumptions: hierarchies that decide everything top-down, workflows that prioritise status quo over speed, incentive systems that reward risk-aversion, and siloed departments that refuse to share data or decision-making power.

And here’s what makes executives most uncomfortable: This isn’t a technology project they can delegate to IT. This is a fundamental business transformation that requires them to give up control, redistribute power, and accept that their banks will look radically different on the other side.

Those who dare to flatten hierarchies, encourage cross-departmental teams (with AI as a core member, not just a supporter), and build in tolerance for messy first drafts will achieve sustainable, AI-driven profitability. Those who cling to tradition won’t survive the next wave of competition.

The real enemy isn’t complexity – it’s the fear of organisational upheaval
In Asia’s banking halls, what holds most institutions back isn’t lack of capital or smart people – it’s a deep aversion to organisational messiness. But in the world of Agentic AI, safety is now the highest-risk bet.

And this is precisely what the industry refuses to discuss openly. Everyone wants to talk about AI capabilities and deployment speed. Almost no one wants to talk about the painful work of reorganising departments, redefining power structures, or telling senior executives that their roles need to fundamentally change.

Tomorrow’s work model is deep collaboration between humans, AI agents, and robots; job definitions, performance reviews, and compliance must all be redrawn. This isn’t a weekend workshop. This is multi-year organisational transformation work that threatens established hierarchies and comfortable ways of working.

Ask any leader: When did your bank last tear up a major workflow because an AI agent proved it could handle risk better? When did HR last rewrite performance reviews to measure AI-human team effectiveness? When did you last promote someone based on their ability to collaborate with AI systems?

If your answer is “never,” that isn’t a technology gap. It’s a courage gap. And it’s exactly why your AI investments aren't delivering the returns your board is demanding.

The bottom line: Courage is the new competitive advantage
The 88-to-39 gap isn’t about technology. It’s about institutional courage. And it’s why executives privately question whether their AI investments were worth it.

The industry still debates algorithms whilst avoiding the truth: Profitable AI requires organisational transformation most banks haven’t begun.

Every quarter with underperforming AI investments tests board patience whilst competitors – perhaps digital-first challengers – advance with fundamentally different operating models. The difference isn’t the technology they deploy. It’s the organisations they’ve built to deploy it.

The evidence is clear: World-class AI running inside traditional organisational structures produces mediocre results. The 49% searching for profitability have the same technology as the 39% finding it. What separates them is organisational courage.

Asian banking is at an inflection point. The institutions that thrive will reimagine banking through human-machine collaboration and commit to the multi-year transformation work that makes it possible.

The critical question: Can organisations evolve as fast as the technology they’re implementing? The gap between AI deployment and AI profitability suggests most can’t – or won’t.

The future isn’t “AI-first.” It’s fearless-first.

For those ready to transform: The opportunity is substantial. For those waiting for proof, or consensus, or perfect conditions – the 88-to-39 gap will likely widen. Not because AI fails, but because organisational transformation wasn’t part of the equation.

The technology works. The question is whether your organisation can.