Case study · A mid-tier Australian bank (operations + risk)
A 2-week AI Readiness Sprint for a mid-tier bank operations team that was being pulled in five different AI directions at once. Output: a written go/no-go on each.
Quantified outcomes
Outcome metrics for this engagement are pending partner sign-off and will publish here once verified.
The problem
A mid-tier bank operations team had received AI proposals from five separate internal stakeholders (CRO, COO, CISO, GM Retail, GM Business Banking) plus three vendor pitches in the prior quarter. The CEO had asked the COO to converge on "what we should actually do first" before any further investment was committed. The team didn't have the bandwidth to do a structured prioritisation themselves and had requested an external sprint that would produce a written, defensible recommendation in front of the executive committee.
The approach
The standard 2-week AI Readiness Sprint, scoped to the operations + risk function but with stakeholder interviews extending across the five internal AI proponents and one of the three vendor proposals (the one the team had been pushed hardest to evaluate). Week 1: structured interviews with each stakeholder + a data + access map across the relevant systems. Week 2: scoring workshop with the operations team + a draft go/no-go recommendation against each candidate. The exec readout at the end of week 2 was attended by all five proponents.
The outcome
The recommendation was adopted by the executive committee at the readout meeting. The vendor proposal was deferred (the cost-value model didn't pencil out at the proposed scale). Two of the five internal use cases were greenlit to Design; one of those proceeded to a full Generative AI Pilot with us six weeks later. The two "stop" recommendations were both accepted by the proponents (one was a process-change recommendation rather than AI; the other had data readiness issues that needed resolution first).
Stack used
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