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 InternalProduct 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.