Eureka Case 30 min Undergrad

De Piloto a Escala

You are Álvaro Cendón-Lapuerta, 51, Chief Digital Officer of Seguros Cibeles, a Madrid insurer. Over the past year your teams ran twelve generative-AI pilots. Every one of them dazzled in the demo. Not one is in production. The board wants to know which one you are going to ship.

The situation

Seguros Cibeles is a mid-size Madrid insurer — motor, home and life — with about 1.4 million policyholders. Over the past year your digital teams ran twelve generative-AI pilots: a customer-service chat assistant, a claims-document summarizer, an underwriting first-draft tool, a policy-wording explainer, and eight more. All twelve demoed beautifully. Not one has reached production.

Last month a competitor announced a customer-facing generative-AI assistant, and the Cibeles board now wants the firm to "ship genAI." The obvious candidate is the customer-service copilot — the pilot with the best demo and the board-friendliest story. You have the budget and the team for one serious operationalization push this year. Twelve pilots, one slot, and a gap between demo and production that most pilots never cross.

Your job in this case: look at why genAI pilots die between demo and production, model the economics of the deployment options, and decide which push Seguros Cibeles makes this year — and how. The board expects a recommendation in two weeks.

The decision

Which genAI push does Cibeles make?

  • A · Ship the customer-service copilot
  • B · Operationalize one internal workflow
  • C · Hold and build the platform

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