Job Summary
The AI Transformation Lead – Supply Chain will drive the adoption and scaling of Artificial Intelligence (AI) capabilities across Resmed's Supply Chain team. This role is responsible for identifying high-value business opportunities, translating them into practical AI-enabled solutions, and partnering with cross-functional teams to deliver measurable outcomes. The position serves as a strategic bridge between supply chain, digital, data, and technology teams, ensuring AI initiatives are aligned with business priorities and enterprise standards. The role also champions AI capability development across the organization by fostering a community of practice, establishing governance frameworks, and enabling sustainable adoption of AI technologies.
Let’s talk about Responsibilities
- Define a supply chain AI transformation roadmap by identifying and prioritizing high-value use cases that align with business objectives and operational priorities.
- Own and maintain a supply chain AI initiative portfolio, overseeing the lifecycle of solutions from ideation through deployment, scaling, monitoring, and continuous optimization.
- Lead the delivery of AI pilot projects and proofs of concept, partnering with data scientists, engineers, digital teams, and business stakeholders to design, validate and scale solutions.
- Provide expertise in deploying AI, machine learning, generative AI, and automation solutions, ensuring they deliver measurable business outcomes and operational improvements.
- Partner with data, analytics, and business teams to improve data quality, accessibility, and governance required to enable scalable AI solutions.
- Establish and maintain AI governance frameworks, guardrails, and responsible AI practices to ensure compliant, secure, and scalable adoption across the organization.
- Drive stakeholder engagement, change management, and value realization activities, serving as a trusted advisor on AI opportunities, risks, and emerging capabilities.
- Develop and continuously improve AI playbooks, standards, best practices, and operating models that accelerate solution delivery and adoption.
- Build and facilitate an AI community of practice through workshops, training, knowledge-sharing sessions.
- Track and communicate business value realized through AI initiatives, ensuring alignment with supply chain priorities and executive stakeholder expectations.
- Monitor emerging AI technologies, industry trends, and best practices to identify opportunities that strengthen supply chain capabilities and competitive advantage.
- Collaborate with enterprise architecture and technology teams to evaluate AI platforms, tools, and vendor capabilities that support the supply chain AI strategy.
- Foster strong cross-functional collaboration by building trusted relationships, aligning stakeholders, and driving effective communication to achieve shared business outcomes.
- Establish and embed consistent ways of working, governance, and delivery practices that promote accountability, continuous improvement, and successful execution of AI initiatives.
Let’s talk about Qualifications and Experience
Preferred:
- Bachelor's degree in supply chain management, Engineering, Computer Science, Data Science, Business, Information Systems, or a related field; advanced degree preferred.
- 5+ years of experience leading AI, digital transformation, advanced analytics, automation, or technology-enabled business initiatives within supply chain, operations, manufacturing, or related domains.
- Strong leadership, facilitation, and stakeholder management skills, with experience leading cross-functional teams, building communities of practice, and driving organizational adoption of new technologies.
- Demonstrated experience successfully deploying AI, machine learning, generative AI, or intelligent automation solutions from concept through production implementation.
- Experience establishing governance frameworks, standards, and controls for AI solutions, while balancing innovation, risk management, and business value.
- Experience building AI adoption frameworks, communities of practice or training programmes initiatives that promote sustainable AI capability development.
Nice-to-Have:
- Experience within large-scale global organizations recognized for advanced AI, digital, or supply chain capabilities (e.g., leading multinational technology, e-commerce, healthcare, manufacturing, or logistics companies).
- Experience contributing to or supporting enterprise AI centers of excellence, innovation teams, or digital transformation programmes.
- Experience leading AI or Data Science teams
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