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银行 · 2026年10月2日

Bank AI Spending Driven by Rivalry, Not ROI, Accenture Says

Accenture's Mike Abbott says banks are increasing AI investment largely to keep pace with rivals, not because of proven returns, with few redesigning workflows to capture real value.

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What happened

Banks are ramping up artificial intelligence spending largely to avoid falling behind competitors rather than because they have identified clear returns, according to Mike Abbott, who leads Accenture's banking practice. Speaking on the drivers of AI investment in the sector, Abbott said few banks have actually redesigned their underlying workflows to capture the value AI promises, meaning much of the current spend is defensive rather than strategic.

The comments point to a gap between the pace of AI budget growth across banking and the extent to which institutions have rethought how work actually gets done. Abbott's framing suggests that for most banks, AI adoption today is closer to competitive hedging — a response to what rivals are doing — than a deliberate operating-model transformation.

Why it matters

For an industry built on process, compliance and risk management, this is a notable warning. Buying AI tools or layering them onto existing systems without changing workflows, decision rights or role design tends to produce limited efficiency gains and little improvement in service or cost outcomes. The real value of AI in banking — faster underwriting, more personalised advice, leaner back-office processing — depends on redesigning the process the technology sits inside, not just adding a tool to the old one.

This matters for digital transformation leaders across financial services because it reframes AI spending as a test of organisational discipline rather than technology capability. The constraint is rarely the model; it is whether the bank has the governance, talent and process appetite to re-engineer how work flows before, during and after the AI is switched on.

The Renascence take

Fear-driven investment is a classic behavioural trap: it optimises for visible parity with competitors rather than for outcomes customers or employees actually feel. Banks chasing AI headlines without touching workflow design risk a widening gap between spend and value — and a credibility problem when boards eventually ask for ROI.

The tell here isn't the size of the AI budget — it's whether anyone has redrawn the process map. Technology adopted to keep up appearances rarely survives contact with a genuine efficiency or experience audit. The banks that will actually benefit are the ones treating AI as a reason to redesign decision rights, handoffs and service journeys from scratch, not as a patch applied to processes built for a pre-AI world. Leaders should be asking their teams a blunter question than "what AI are we buying": "what workflow are we willing to tear up to use it properly?"

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Mike Abbott, who leads Accenture's banking practice, said much of banks' current AI spending is driven by the fear of falling behind competitors rather than clear evidence of returns.

According to Abbott, few banks have redesigned their underlying workflows, decision rights or role design to work with AI, which limits the efficiency and service gains the technology can actually deliver.

Layering AI onto existing systems without rethinking how work is done tends to produce limited cost or service improvements, creating a gap between AI spend and measurable value that boards may eventually question.

Renascence argues banks should treat AI adoption as a trigger to redesign decision rights, handoffs and service journeys, rather than simply patching new tools onto pre-AI workflows.

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