बैंकिंग · 13 सितंबर 2026
Bank AI Spending Driven by FOMO, Not ROI, Says Accenture Exec
Accenture's Mike Abbott says banks are raising AI budgets mainly to keep pace with rivals, not because they've redesigned workflows to capture measurable returns.
What happened
Accenture's banking industry lead, Mike Abbott, says fear of competitive disadvantage — not a clear business case — is the primary driver behind rising bank spending on artificial intelligence. Speaking about the sector's AI investment patterns, Abbott said many institutions are increasing budgets largely because rivals are doing the same, while relatively few have actually redesigned the underlying workflows needed to convert that spending into measurable returns.
According to Abbott, most banks have layered AI tools onto existing processes rather than rethinking how work gets done. The result, per the report, is spending that looks strategic on paper but has yet to translate into consistent revenue gains or cost reductions for the majority of institutions.
Why it matters
The comments point to a familiar pattern in enterprise technology adoption: budget commitments outpacing operating-model change. For banks, AI's real value depends less on the tools deployed and more on whether workflows, roles and decision rights are rebuilt around them. Spending driven by peer anxiety rather than a defined use case tends to produce pilots and point solutions rather than the structural change needed for AI to show up in revenue or expense lines.
For digital transformation leaders, this is a signal to separate AI investment from AI value capture. Boards approving larger AI budgets should be asking not just what is being bought, but which processes are being redesigned to use it — and how success will be measured.
The Renascence take
This is less a story about artificial intelligence than about herd behaviour under competitive uncertainty — a classic case of loss aversion shaping investment decisions more than expected value does.
Banks chasing rivals' AI budgets without redesigning workflows are optimising for reassurance, not results — a textbook case of fear of missing out overriding return-on-investment discipline. The fix isn't more AI spend; it's sequencing: map the customer or employee journey first, identify where AI genuinely removes friction or cost, then invest against that case. Any institution that can't name the workflow it's changing shouldn't be able to name a budget line for AI either.
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