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AI Enablement & Adoption Manager @ Vertiv

Mandaluyong City, National Capital Region, PHOnsiteFull-timeJob reference 20268883
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About this role

AI Enablement & Adoption

The role is responsible for identifying, piloting, and embedding practical AI solutions into existing business processes. The role focuses on hands-on delivery, early wins, and building foundational AI capability across the organization with cross-functional collaboration.

Key Responsibilities:

AI Use-Case Delivery

• Identify high-impact, low-complexity AI use cases across the various functions in the organization • Work with IT and relevant business functions to identify and enable required AI tools / technologies for application • Design, prototype, and deploy AI-enabled tools and workflows • Integrate AI into existing systems and processes

Adoption & Enablement

• Embed AI into daily workflows • Deliver practical training to drive adoption • Act as an internal advisor on effective AI usage

Foundations & Guardrails

• Establish lightweight AI usage guidelines (data handling, accuracy, risk awareness) • Document playbooks and reusable patterns • Identify risks and limitations early

Stakeholder Collaboration

• Partner with Sales Operations, Business Transformation, IT, and other teams • Escalate blockers and dependencies • Contribute to longer-term AI roadmap development

Requirements:

• At least 10 years of total work experience of which 3 years are in the area of AI deployment, enablement, and adoption (with proven track record on it); rest of work experience on related or adjacent fields like automation, analytics, digital transformation, etc.) • Strong business acumen • Structured problem solving • Change management and adoption • Project and program management • Practical experience with generative AI tools (e.g., large language models, AI copilots) • Strong prompt engineering and workflow design skills • Experience using no-code / low-code automation platforms • Ability to integrate AI tools with existing systems (CRM, reporting, ticketing) • Working knowledge of APIs and basic scripting (e.g., Python or similar) • Understanding of data concepts such as data quality, privacy, and access controls • Ability to evaluate AI tools and vendors based on business fit and risk

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