AI Adoption & Enablement Lead

About the role

Position Objective

Key Responsibilities

• Develop and execute adoption strategies for Google Cloud, Vertex AI, Gemini, and enterprise AI solutions in line with customer objectives and the Google Engineer business roadmap.
• Assess organizational readiness, user needs, business priorities, adoption barriers, and change impacts across functions and stakeholder groups.
• Define adoption roadmaps, stakeholder plans, communication plans, enablement journeys, and measurable success criteria for each engagement.
• Partner with business and technology leaders to secure sponsorship, align priorities, and embed AI initiatives into day‑to‑day operating models.
• Design and deliver practical enablement programs covering Google Cloud concepts, Vertex AI capabilities, Gemini use cases, responsible AI, security, and effective human–AI collaboration.
• Create role‑based learning paths, workshops, demonstrations, playbooks, quick‑reference guides, communications, and communities of practice for technical and non‑technical audiences.
• Translate complex cloud, data, AI, and Generative AI concepts into clear business language and hands‑on learning experiences.
• Coordinate with solution architects and engineering teams so that enablement materials accurately reflect the implemented solution, controls, and operating procedures.
• Promote responsible AI behaviors, including appropriate use, human oversight, data protection, security, model limitations, and escalation routes.
• Work with business functions and customer teams to identify, prioritize, and validate high‑value AI and automation use cases.
• Facilitate discovery workshops, design‑thinking sessions, stakeholder interviews, and value‑assessment activities for Google AI opportunities.
• Support pilots and proof‑of‑value activities by defining user journeys, adoption hypotheses, feedback loops, and readiness criteria.
• Help transition successful use cases from pilot to production by coordinating user readiness, process changes, documentation, support models, and adoption communications.
• Capture and share reusable patterns, lessons learned, success stories, and customer references across the Google Engineer business.
• Act as a trusted advisor to customer executives, business leaders, product owners, HR or learning teams, and technology stakeholders on AI adoption and change priorities.
• Lead change‑impact assessments, stakeholder mapping, communication activities, feedback collection, and resistance‑management actions.
• Facilitate executive briefings, steering meetings, enablement sessions, user forums, and cross‑functional working groups.
• Coordinate distributed NTT DATA, customer, partner, and Google‑aligned teams to maintain consistent messages, expectations, and adoption actions.
• Build trusted relationships in international and cross‑cultural environments, including engagements with APAC stakeholders when required.
• Define and maintain adoption KPIs covering reach, participation, readiness, active usage, use‑case progression, user confidence, satisfaction, and realized business value.
• Maintain adoption dashboards, executive reports, risk and issue logs, decision records, and action trackers with clear owners and due dates.
• Monitor user feedback, usage trends, business outcomes, and emerging risks; recommend corrective actions and continuous‑improvement initiatives.
• Ensure adoption activities align with customer governance, security, privacy, compliance, responsible AI, and operational‑readiness requirements.
• Contribute to proposals, statements of work, delivery plans, and service‑improvement initiatives by articulating the people and adoption work required for sustainable outcomes.

Essential Qualifications

• Bachelor’s degree or higher in Information Technology, Computer Science, Artificial Intelligence, Data Science, Engineering, Business, Organizational Development, Change Management, Education, or a related discipline.
• At least 8 years of experience in digital transformation, technology adoption, organizational change, business transformation, consulting, learning enablement, or a comparable field.
• At least 3 years of experience leading enterprise AI, Generative AI, automation, cloud, data, or emerging‑technology adoption initiatives from strategy through measurable implementation.
• Proven experience turning complex Google Cloud and AI capabilities into practical user journeys, learning programs, operating changes, and sustained adoption outcomes.
• Practical knowledge of Google Cloud and AI concepts, including Vertex AI, Gemini, data and analytics services, Generative AI use cases, model limitations, responsible AI, security, and production readiness.
• Demonstrated ability to design and facilitate executive briefings, workshops, role‑based training, communities of practice, and cross‑functional enablement programs.
• Experience defining adoption metrics, analyzing user feedback and usage data, building dashboards or reports, and linking adoption activity to business value.
• Strong program management, stakeholder management, facilitation, communication, presentation, analytical, influencing, and problem‑solving skills.
• Professional English communication skills and the ability to work effectively with international customers, engineering teams, and senior stakeholders.

Preferred Qualifications

• Google Cloud certification, such as Cloud Digital Leader, Associate Cloud Engineer, Professional Cloud Architect, or Professional Machine Learning Engineer, or equivalent practical experience.
• Hands‑on exposure to Vertex AI, Gemini, BigQuery, Cloud Storage, Google Workspace AI capabilities, prompt design, RAG concepts, AI evaluation, or enterprise AI governance.
• Prosci, ADKAR, ACMP, CCMP, Lean Change, Agile, Scrum, PMP, or comparable change and delivery certification.
• Experience with enterprise learning, collaboration, adoption analytics, or service‑management platforms such as Google Workspace, Jira, Confluence, ServiceNow, or comparable tools.
• Experience in consulting, technology services, managed services, cloud migration, AI transformation, or enterprise platform modernization.
• Experience supporting APAC clients or multinational organizations; English language proficiency is highly desirable.
• Ability to operate in a matrix organization and build reusable enablement assets for regional or APAC‑wide delivery.

Success Measures

• Google Cloud, Vertex AI, and Gemini adoption plans are aligned with customer priorities, delivery milestones, governance requirements, and measurable business outcomes.
• Target audiences complete relevant enablement activities and demonstrate improved confidence, readiness, responsible‑use awareness, and active usage.
• High‑value AI use cases progress from discovery and pilot into repeatable, production‑ready business adoption with clear ownership and support models.
• Adoption dashboards, stakeholder feedback, risks, decisions, and improvement actions remain accurate, visible, and actively managed.
• Customer satisfaction, user engagement, AI capability maturity, and realized productivity or business value improve through evidence‑based interventions.