Product Owner - AI

Role Purpose The AI Product Owner is responsible for owning and driving the delivery of AI products in APAC, with a primary focus on rapid iteration, scalability, and commercialization of customer-facing AI capabilities. The role acts as the single point of accountability for translating business and customer needs into a prioritised product backlog, ensuring AI products are delivered efficiently through agile ways of working and are ready for market adoption across APAC. Key Responsibilities 1. Product Ownership & Backlog Management • Own the product vision and roadmap for assigned AI products within APAC. • Translate business requirements, customer needs, and commercial opportunities into epics, user stories, and acceptance criteria. • Create, maintain, and prioritise the product backlog based on business value, scalability, and delivery feasibility. • Act as the final decision maker on backlog prioritisation and scope trade-offs. 2. Agile Delivery & Iteration • Work closely with Engineering, Data Science, Design, and Delivery teams to ensure clear, actionable requirements ahead of sprint execution. • Lead and participate in backlog refinement, sprint planning, sprint reviews, and retrospectives. • Enable fast build–measure–learn cycles through incremental delivery and feedback loops. • Ensure delivery aligns with agreed timelines, capacity, and quality standards. 3. AI Product Commercialisation • Drive customer-facing AI product readiness, including MVP definition, feature packaging, and rollout sequencing. • Partner with commercial and go-to-market teams to ensure AI capabilities are demo-ready and usable by customers and partners. • Support pilots and early launches, capturing feedback and optimising adoption. • Track and optimise outcomes such as usage, conversion uplift, automation rate, and operational efficiency. 4. Scalability & Reusability • Design AI solutions with a build-once, reuse-many mindset across APAC markets. • Identify opportunities where AI drives operational scalability and cost efficiency. • Promote standardisation of features, APIs, and configurations to minimise market-specific customisation. 5. Stakeholder Management & Communication • Act as the primary product interface between business stakeholders, technical teams, and delivery functions. • Facilitate alignment across regional and global stakeholders on scope, priorities, risks, and dependencies. • Communicate product progress and decisions using structured artefacts such as roadmaps and release notes. Key Deliverables • Product vision and roadmap • Prioritised product backlog • Sprint-ready requirements and clarifications • Demoable AI product increments • Adoption and performance insights • Inputs to commercial rollout and scaling plans Key Stakeholders Internal Product Management, Engineering & Data Science, Platform & Delivery Teams, Operations, Commercial / Sales / Go-to-Market, Security, Privacy, and Compliance External (as required) Customers, distribution partners, and AI technology vendors Required Skills & Experience Product / Business Analysis Capabilities • Proven experience as a Product Owner, Product Manager, or Senior Business Analyst in agile delivery environments. • Strong ability to translate complex requirements into clear functional stories and acceptance criteria. • Hands-on experience working with cross-functional delivery teams. AI & Digital Product Experience • Experience delivering AI-enabled or data-driven products (e.g. GenAI, automation, predictive analytics). • Hands-on experience developing or delivering customer-facing AI applications is a strong plus. • Ability to work effectively with Data Science and Engineering teams. • Understanding of AI product lifecycle concepts including iteration and human-in-the-loop workflows. Commercial & Regional Context • Experience delivering products across multiple markets, preferably within APAC. • Strong commercial mindset focused on time-to-market, scalability, and customer adoption. Ways of Working • Strong stakeholder management and facilitation skills. • Comfortable operating in fast-paced, ambiguous environments. • Outcome-driven and delivery-focused. Language Requirements • Fluent English (written and spoken) – mandatory. • At least one APAC language preferred: Korean and/or Japanese. Success Measures • Reduced time from idea to production for AI features. • Adoption and usage of customer-facing AI products. • Reusability of AI capabilities across APAC markets. • Alignment between business objectives and delivered AI functionality.