AI Strategy & Roadmap: Collaborate with the Chief Data Officer and stakeholders to participate in the development and implementation of a comprehensive AI strategy that aligns with the organization's mission and objectives.
Use Case Identification & Assessment: Conduct thorough assessments of potential AI use cases, considering their feasibility, impact, and associated risks.
Solution Review & Architecture: Evaluate the technical soundness of AI project proposals, focusing on architecture, security, privacy, data quality, model performance, and scalability. Advise on design to ensure scalable and secure data architectures to support AI/ML workloads, ensuring data quality, availability, and compliance.
Risk Management & Mitigation: Assess the potential impact of AI projects. Identify and mitigate risks associated with AI projects, including data privacy concerns, algorithmic bias, and potential misuse of AI.
Collaboration: Foster strong relationships with cross-functional teams, including agency and IT teams. Provide guidance and support on technical and ethical considerations and assist with strengthening procedure and operationalizing AI considerations.
Technology Evaluation & Selection: Stay abreast of the latest AI technologies and trends, evaluating their suitability for specific use cases and recommending appropriate solutions.
Documentation: Prepare clear and concise technical reports summarizing the findings of project reviews as well as outline trends in use cases and surface considerations around opportunities for future use.