Southwest Airlines' marketing team relied on largely manual go-to-market campaign processes, including repetitive copy-paste actions between tools and documents, inconsistent templatization, and limited visibility into where friction was slowing execution.
The AI Programs team needed a structured method to identify which parts of the campaign process were genuine candidates for AI or automation, without defaulting to applying AI everywhere indiscriminately. The challenge was surfacing the right problems before jumping to solutions.
Nicola's team conducted cross-functional discovery interviews and workshops across Southwest Airlines' marketing function, codifying a reusable five-signal framework that identifies where AI can add value, available data, repetitive tasks, templatization, reusable infrastructure, and high error rates.
The team codified five "signals" that indicate where AI could add value in a process: available data/assets, repetitive tasks, templatized deliverables, reusable technical infrastructure, and high human-error zones. This framework is now reusable across future Southwest AI initiatives.
By conducting user research with representatives across marketing, tech ops, ground ops, digital, analytics, and brand, the team built ground-level advocacy before any tool was built, converting research participants into future adoption champions.
The Double Diamond framework proved effective for AI use-case discovery, giving Southwest a repeatable, mature process for evaluating AI opportunities, replacing ad hoc "AI hammer looking for a nail" approaches common in enterprise AI teams.
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