1ª Entrevista ELAS TRANSFORMAN | Rocío Vega y Alba Buidiño (Zebra Brain): Mujeres liderando la IA

Summary

Rocío Vega and Alba Buidiño of Zebra Brain combine expertise in mathematical engineering and AI with experience in law, HR, and organizational dynamics. Their central business thesis is that digital transformation is rarely just a technology problem: solutions must fit how people work, align with business goals, and receive active support from leadership.

Zebra Brain offers consulting that can support companies from diagnosis through design, implementation, and training—not just deliver a report or technical solution. The company is also developing Lira, an AI agent intended to support performance-review processes by gathering and analyzing information over time. Lira has been tested in beta versions but has not yet been commercialized; the founders say they plan to launch it soon.

Frameworks and playbooks

• Technical and human perspectives on transformation: Assess both the technology and the organization’s people, relationships, processes, and informal decision-making. A technically strong solution can fail if employees do not understand it, trust it, or know how to use it.
• Diagnose before digitizing:
  1. Clarify the company’s objectives and business questions.
  2. Understand current processes, finances, and team needs.
  3. Identify whether technology can address a real problem.
  4. Start with a smaller intervention if the organization is not ready for a larger change.
  5. Implement and train, then support adoption.

The founders stress that AI should not be introduced simply because it is fashionable. Sometimes, their conclusion may be that a company is not ready for, or does not need, the proposed solution.

• Change-readiness checklist: Look for openness to change, a clearly defined business objective, and genuine executive sponsorship. Leadership must provide time and investment, and visibly demonstrate commitment. Employee enthusiasm alone is unlikely to sustain a project if it is not a strategic priority.
• Manage adoption as a process: Expect an initial period of enthusiasm followed by friction when employees discover that AI requires training and does not immediately produce results. The discussion describes this as a “J-curve” and recommends managing expectations and providing support throughout.
• Build trust through transparency: Explain what an AI tool does, why it is being used, what data it collects and uses, who makes decisions, and where human responsibility lies. Address these choices during design rather than leaving them ambiguous.
• Observe organizational practices as well as stated policies: Interviews and time spent with teams can reveal differences between formal descriptions of how decisions are made and how work actually happens.

Go-to-market and sales lessons

• The founders’ early sales conversations were too conceptual. They learned to translate AI into concrete business value, such as potential cost reductions, revenue improvements, or process benefits.
• They used cold calling, accepting that rejection was part of the process.
• Associations and speaking opportunities—including APD and Startup Galicia—helped them reach potential clients and build relationships.
• Referrals began to develop after successful projects and satisfied clients.
• They adjusted proposals to match a client’s readiness rather than insisting on a technically attractive solution the organization could not yet implement.

Product, operations, and examples

• Lira: The idea originated in a discussion about using AI to make performance reviews less bureaucratic, faster, and potentially more objective. The intended agent can gather and analyze information over time, helping retain organizational knowledge and potentially identify risks such as absenteeism or employee turnover. These are intended functions, not validated outcomes.
• Data as decision support: Information is valuable when it answers a business question. Data collected merely to look good in presentations has little practical value.
• Organizational dynamics: The founders compare companies to dynamic systems: misalignment or low motivation in one team or process can affect the wider organization. This makes team-level diagnosis and change support important.
• Knowledge retention: Organizational knowledge should become part of the company’s systems rather than depend solely on individual memory.

Metrics and timelines

• No numerical revenue, margin, CAC, LTV, churn, or growth targets are given.
• Lira had undergone beta testing and was described as nearing commercialization, but no launch date or performance results were specified.
• The founders said their initial market conversations about AI took place roughly a year and a half earlier. At that time, many prospects associated AI mainly with ChatGPT rather than its integration into business processes.

Actionable recommendations

• Begin with the business problem and a clear measure of value, not with a preferred technology.
• Involve management early and secure explicit commitments of budget and employee time.
• Interview employees individually to understand concerns, digital confidence, and likely adoption barriers.
• Make AI’s purpose, data practices, decision rights, and human accountability clear.
• Train and support users after implementation; do not assume deployment alone creates adoption.
• Learn from peers, mentors, clients, and other organizations, including how they handle leadership, suppliers, and collaboration.
• For women pursuing technology ventures, the founders recommend speaking with other entrepreneurs, learning from their mistakes, and maintaining curiosity while shaping one’s own path.

Presenters and sources

• Rocío Vega — Zebra Brain co-founder; mathematician with a doctorate in mathematical engineering and experience in digitalization, energy efficiency, modeling, and AI.
• Alba Buidiño — Zebra Brain co-founder; background in philosophy, law, HR, and organizational dynamics.
• Interviewer: Isabel Álvarez, BTI Estrategia.
• Source: Interview in the ELAS TRANSFORMAN series, Oficina Acelera Pyme de INEO.