Published

How Southwest Marketing Mapped AI Bets Across 8 Functions

A 70,000-person airline's marketing team ran Double Diamond design thinking across 8 functions — codifying five signals that flag where AI actually pays off.

70,000-Person Scale

AI signals mapped, 8 teams

< 4 weeks

Implementation Time

Not disclosed

Project Cost

the challenge

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.

what they built

Nicola's team applied the Double Diamond Design Thinking Framework to conduct end-to-end discovery across Southwest's marketing function. One-on-one interviews and cross-functional workshops with representatives from social media, paid media, brand, creative, strategy, analytics, digital, and technology teams surfaced pain points and validated findings. The team codified a set of 'signals' — indicators that a process area is ripe for AI: available data or historic assets, repetitive tasks, existing templatization, reusable technical infrastructure, and high human error rates. These signals formed a reusable assessment framework now being applied to future AI opportunity identification across the enterprise.

Nicola's team began by establishing a disciplined separation between problem identification and solution design — a step that prevented the common failure mode of applying AI to the wrong processes. Using the Double Diamond Design Thinking Framework, the team conducted one-on-one interviews and cross-functional workshops with representatives from social media, paid media, brand, creative, strategy, analytics, digital, and technology teams across Southwest Airlines. Interviews were designed to surface where work was slow, repetitive, error-prone, or dependent on manual copy-paste actions between systems. Workshop sessions validated and pressure-tested findings across functional boundaries. From these sessions, the team codified five signals that reliably indicate where a process is ripe for AI: availability of data or historic assets, repetitive task structures, existing templatization, reusable technical infrastructure, and zones of high human error. The resulting framework now serves as a reusable assessment tool for future AI opportunity identification across the Southwest enterprise, giving the AI Programs team a structured, repeatable method rather than a one-off analysis.

best fit for

Enterprise organizations with large, distributed workforces that need a structured, research-grounded approach to AI adoption — particularly where leadership wants to move beyond 'AI for everything' toward strategic prioritization. Well-suited to organizations in transportation, hospitality, retail, or any sector with complex internal marketing and operational workflows.

Ai ROLE

In this engagement, AI itself is not yet deployed operationally — the AI role is prospective. The team used structured human research methods (interviews and workshops) to identify where AI could be most effectively applied, codifying a set of signals that indicate process readiness for AI or automation. The output is a prioritised set of AI opportunities, not an active AI system.

impact

Structured Signal Framework for AI Opportunity Identification

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.

Cross-Functional Alignment Across a 70,000-Person Enterprise

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.

Validated Design Thinking as the Repeatable AI Assessment Process

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.

implementation complexity

The implementation is a structured research and facilitation engagement — interviews, workshops, and framework development — requiring no software development, technical integration, or AI model deployment. The primary inputs are time, cross-functional access, and facilitation expertise.

Nicola Smith

Human-Centered AI Strategy Leader | Design-Thinking Facilitator | Futurist

Southwest Airlines

Strategic innovation leader and Senior AI Advisor at Southwest, specializing in customer experience, brand strategy, and emerging tech to drive growth and digital transformation.

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industry

Aviation & Aerospace

business organization

Marketing

Operations

AI TYpe

Process Automation (RPA + AI)

value type

Time Savings

Cost Reduction

other(firm) Case studies

frequently asked questions

How did Southwest Airlines map AI opportunities across its marketing function?

The experts applied a Double Diamond design-thinking framework, deliberately separating problem identification from solution design, and ran one-on-one interviews and cross-functional workshops across Southwest Airlines' social, paid media, brand, creative, strategy, analytics, digital, and technology teams. From those sessions they codified five reusable 'signals' that indicate where a process is ripe for AI. The output was cross-functional alignment across a 70,000-person enterprise and a repeatable assessment framework.

What AI tools and approach were used in the marketing AI assessment?

The work centered on process automation (RPA + AI) and a structured design-thinking discovery method, using Claude and ChatGPT. Rather than building a tool first, the team used interviews and workshops to identify high-value processes and codified five signals — available data/assets, repetitive tasks, templatized deliverables, reusable technical infrastructure, and high human-error zones.

What results did Southwest Airlines achieve?

The engagement produced cross-functional alignment across a 70,000-person enterprise, a structured signal framework for identifying AI opportunities, and a validated, repeatable design-thinking assessment process — replacing ad hoc 'AI hammer looking for a nail' approaches.

How long did the AI opportunity assessment take?

About four to eight weeks of structured discovery and workshops across the marketing function.

Who is this AI assessment approach best for?

Enterprise organizations with large, distributed workforces that want a structured, research-grounded path to AI adoption — particularly in transportation, hospitality, retail, or any sector with complex internal marketing and operational workflows.

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