Leeds, UK

GeorgePalacios

Enterprise AI Enablement & Engineering Leader

A leader in AI strategy, governance, platforms and organisational adoption, grounded in engineering and regulated delivery.

Answers use reviewed public professional evidence only.

Explore the evidence

Evidence behind the profile

Enterprise AI leadership in practice.

Enterprise AI enablement and engineering leader who connects strategy, governance, organisational change and hands-on technical delivery. Partners with directors and specialist functions in regulated banking to turn emerging AI opportunities into governed, bank-wide services and tools, practical standards and reusable capabilities. Brings 13+ years in engineering, including direct team leadership, enterprise capability development and reliable technology delivery.

  1. AI governance and evaluation

    Develops and applies the bank’s AI Risk Framework and widely used governance and evaluation approaches, translating policy into practical controls and production-readiness criteria.

  2. Platform and vendor stewardship

    Owns technical stewardship of GenAI platforms and tools serving users across the bank, balancing access, security, compliance, cost, standards, support and adoption. Acts as the bank’s technical point of contact with platform vendors.

  3. Adoption and reusable capability

    Leads development and adoption of widely used internal AI capabilities, including the AI Coach. Extends delivery through reusable agent patterns, practical education and governed citizen development, with its first product now in production.

  4. People and enterprise leadership

    Leads cross-functional AI enablement working groups spanning security, risk and compliance, technology, education and responsible use. Builds on earlier formal leadership of a six-person engineering team with accountability for people, recruitment, budget, delivery and technical standards.

Trace the progression

Career progression

13+ years building
governed technology capability

A consistent progression from engineering operations to enterprise AI leadership.

  1. Engineering operations

    Reliability, security and technical standards

  2. Shared platforms and automation

    Reusable services, cloud enablement and CI/CD

  3. AI delivery

    Award-winning prototypes and adopted AI products

  4. Enterprise AI enablement

    Strategy, governance, platforms and adoption

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Next step

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