AI Innovation Manager

Holland America Line has been exploring the world since 1873. Our ships offer innovative features and enriching experiences focused on destination exploration and personalized travel, inviting guests to savor the journey. 

The Manager, AI Innovation is responsible for advancing Holland America Line and Seabourn's AI innovation capability through hands-on solution development, strategic portfolio support, enterprise enablement, and scalable operating practices. This role leads a team of Analysts through complex AI discovery and prototyping efforts, translates ambiguous business problems into actionable AI use cases, and builds practical tools, workflows, prompt assets, automations, and decision-support solutions that help teams improve productivity, decision quality, guest experience, and commercial outcomes. In addition to developing AI-enabled solutions, the Manager serves as a force multiplier for the Director, AI Innovation by helping shape the AI roadmap, preparing leadership-ready recommendations, structuring the use case portfolio, researching emerging AI trends, and converting strategy into repeatable processes, standards, content, and ways of working. The role partners closely with IT, data, security, privacy, architecture, business operations, and functional leaders to define how AI ideas move from intake and experimentation through review, production evaluation, adoption, and ongoing support. The position requires strong business judgment, technical fluency, executive-level communication, and the ability to influence without direct authority across a matrixed organization.

Here’s a summary of what Holland America Line is looking for.  Is this you? 

Responsibilities:

Advanced AI Solution Discovery, Design & POC Delivery

• Lead discovery for complex AI opportunities across multiple business areas, including facilitation of stakeholder interviews, workflow mapping, pain point analysis, success metric definition, and readiness assessment.

• Translate ambiguous business challenges into clear AI use cases, requirements, user stories, acceptance criteria, risks, assumptions, dependencies, and business value hypotheses.

• Build functional AI-enabled prototypes and tools, including agents, copilots, prompt libraries, workflow automations, dashboards, knowledge assistants, decision-support tools, and lightweight applications that business users can test and evaluate.

• Design prototypes with scalability and production evaluation in mind by documenting data needs, process impacts, user roles, controls, technical assumptions, limitations, and support requirements.

• Lead user testing and iteration cycles, synthesize feedback, evaluate whether solutions meet business objectives, and make recommendations on whether to scale, refine, pause, or retire use cases.