Key Responsibilities for Lead AI
- Project Leadership & Delivery
- Lead the planning, execution, and delivery of AI initiatives aligned with business priorities
- Build business cases with AI as a backbone around : Increasing Customer Experience, Increasing Operational Efficiency, Campaign Intelligence, Insights to Front-end teams, etc.
- Collaborate with data science, engineering, and business teams to define requirements, timelines, and KPIs.
- Own the project lifecycle—from idea validation through to deployment and post-launch performance tracking.
- AI Strategy & Business Alignment
- Work closely with business stakeholders to identify opportunities where AI can drive value.
- Translate business problems into data-driven solutions and actionable AI use cases.
- Advocate for the adoption of AI and educate non-technical stakeholders on AI capabilities and limitations.
- Cross-functional Collaboration
- Facilitate communication between technical and non-technical teams.
- Align stakeholders across product, operations, IT, data, and executive leadership.
- Change Management & Adoption
- Drive user adoption by ensuring projects are human-centered and business-relevant.
- Create feedback loops and support teams in adjusting processes to effectively leverage new AI tools.
- Governance & Ethics
- Ensure ethical and responsible AI use by working with internal risk, compliance, and legal teams.
- Contribute to developing standards and best practices for AI governance.
Qualifications
- Required:
- 5–10 years of experience in project management, digital transformation, or business consulting roles, ideally with a focus on technology or AI.
- Proven experience leading AI/ML or data-driven projects from concept to production.
- Strong understanding of AI/ML concepts and their application in business contexts (you don’t need to code, but you should understand the methods and limitations).
- Experience working with cross-functional teams in matrix organizations.
- Exceptional communication and stakeholder management skills.
- Preferred:
- Background in industries such as finance, retail, healthcare, logistics, or manufacturing where AI is driving transformation.
- Experience working with Agile or hybrid project delivery methodologies.
- Familiarity with AI/ML platforms (e.g., AWS Sagemaker, Azure ML, Google Vertex AI) or low-code/no-code AI tools (good to have)
- Master’s degree in Business, Technology, Data Science, or related field.