AI Transformation Lead

Company-wide AI adoption, process transformation, and measurable productivity improvement

CyberLogitec Vietnam is a leading IT services company with 1,000+ professionals, delivering end-to-end software solutions across logistics, manufacturing, and enterprise domains.

We believe AI should be more than a technology or a set of tools. It should fundamentally transform how we work, how we deliver, and how we improve productivity across the organization.

We are looking for an AI Transformation Lead who will drive company-wide AI adoption, redesign work processes with AI, and continuously build AI capabilities across our workforce.

THE ROLE

The AI Transformation Lead will be the owner of company-wide AI adoption and productivity transformation at CyberLogitec Vietnam.

The primary mission of this role is not to develop AI technology itself, but to transform the way people work and deliver measurable productivity improvements through AI.

You will identify how AI can be effectively applied across Engineering, QA, BA, Project Management, Delivery, and Corporate Functions; redesign workflows; evaluate and deploy appropriate AI tools; and enable employees to integrate AI into their daily work.

You will also own the definition, measurement, and continuous improvement of the company's AI Maturity Level (AML), establishing objective indicators to assess AI adoption and capability across individuals, teams, and the organization.

This is not primarily an AI research, ML engineering, or AI product development role. Our priority is to leverage proven external AI tools and services to achieve practical and scalable business impact, while evaluating internal AI infrastructure where security, cost, integration, or strategic requirements justify it.

KEY RESPONSIBILITIES

1. AI Transformation Strategy & Roadmap

• Define and drive the company-wide AI Transformation Strategy and Roadmap, aligned with business priorities.
• Identify and prioritize high-impact AI use cases across Engineering, QA, BA, Project Management, Delivery, and Corporate Functions.
• Go beyond tool adoption by redesigning work processes and ways of working around AI.
• Continuously evaluate the impact of AI on productivity, quality, working time, and operational effectiveness.
• Work closely with senior leadership and functional leaders to translate transformation goals into actionable initiatives.

2. AI-Enabled Process Transformation

• Analyze existing workflows and identify opportunities where AI can improve productivity, quality, and efficiency.
• Design AI-enabled workflows for coding, code review, testing, documentation, requirements analysis, project management, reporting, and communication.
• Lead pilots with business and delivery teams to validate actual impact in real working environments.
• Convert proven use cases into repeatable best practices and standard workflows for company-wide adoption.
• Focus on measurable business outcomes rather than AI adoption for its own sake.

3. AI Tool Evaluation & Adoption

• Continuously evaluate external AI tools and services, including solutions such as ChatGPT, Claude, GitHub Copilot, and Cursor.
• Assess tools based on business applicability, productivity impact, user experience, cost, information security, and data protection.
• Lead pilots and Proof-of-Value initiatives, and define the appropriate tools and usage models by function and role.
• Manage licenses and usage, and analyze adoption and impact relative to cost.
• Prioritize external tools while assessing internal AI infrastructure only when justified by security, cost, integration, or strategic needs.

KEY RESPONSIBILITIES

1. Workforce AI Capability Development

• Develop and operate a company-wide AI Capability Development Program.
• Define role-based AI competencies and practical learning paths for employees.
• Deliver training, workshops, hands-on programs, and internal knowledge-sharing mechanisms.
• Capture and disseminate best practices grounded in real work cases.
• Develop AI Champions or Power Users who can accelerate adoption within their teams.
• Drive sustained adoption so employees use AI as part of their everyday work, rather than treating training as a one-time activity.

2. AI Maturity Management

• Own the definition, measurement, management, and continuous improvement of the company's AI Maturity Level (AML).
• Establish objective measurement frameworks and indicators for AI adoption and capability across individuals, teams, and the organization.
• Track adoption and capability levels, identify improvement areas, and drive targeted actions.
• Analyze the relationship between AI usage and actual business performance.
• Provide regular progress, insight, and recommendations to senior management and relevant stakeholders.

3. AI Governance & Sustainable Adoption

• Establish company-wide principles and governance for responsible AI use.
• Create a safe adoption environment that addresses information security, data privacy, intellectual property, and client confidentiality.
• Maintain standards for approved tools and permitted usage.
• Implement monitoring for AI licenses, usage, and cost.
• Partner with Security, IT, HR, and business leaders to make AI adoption sustainable at scale.

REQUIREMENTS

Must-Have

• Substantial hands-on and leadership experience in IT, Digital Transformation, Process Innovation, AI Adoption, or a closely related field.
• Demonstrated experience analyzing business processes and improving ways of working and productivity through technology.
• Strong understanding of generative AI and major AI tools, with practical experience applying them to real work.
• Hands-on ability to test new AI tools and evaluate their suitability for organizational adoption.
• Experience planning and executing organization-wide transformation or technology adoption initiatives.
• Strong change management, communication, facilitation, and learning enablement capabilities.
• Ability to define and use quantitative and qualitative indicators to measure technology adoption and operational improvement.
• Leadership and stakeholder-management skills to work effectively with diverse functions and senior management.
• Professional working proficiency in English.

Strongly Preferred

• Experience in an IT services, software development, or ODC environment.
• Good understanding of the Software Development Life Cycle and how Engineering, QA, BA, PM, and Delivery teams operate.
• Experience leading Digital or AI Transformation, or enterprise technology adoption, in an organization of 100+ employees.
• Experience in AI training, competency development, or organizational capability building.
• Experience defining or operating a Digital or AI Maturity framework.
• Experience with enterprise deployment, license and cost management, or governance of AI tools.
• Experience measuring and managing productivity improvement using actual operational data.

What success looks like: AI is embedded in everyday work; adoption is measurable; high-value workflows are standardized; employees continuously strengthen their capabilities; and productivity, quality, and cost improvements are demonstrated with evidence.