Associate Director, AI Transformation at IDinsight

• Engagement leadership: Serve as the senior lead on external advisory engagements, owning client relationships, strategic direction, deliverable quality, and team allocation.
• Client development: Identify, scope, and structure new AI advisory engagements.
• Service design: Codify IDinsight’s AI transformation approach into repeatable frameworks, toolkits, and playbooks covering governance, change management, tool development, and benchmarking.
• Training and workshops: Design and deliver executive workshops, workflow redesign sessions, and training programs that build lasting client capability.
• Thought leadership: Represent IDinsight externally through blog posts, conference presentations, and sector conversations on AI transformation.

• Product vision and roadmap: Define and prioritize which custom AI products to build, determine make/buy decisions, ensure custom builds are reserved for problems that off-the-shelf tools can’t solve.
• User-centered discovery: Drive user research and workflow audits to identify where AI can deliver step-change improvements across IDinsight’s business units and external partners.
• Delivery oversight: Ensure products move from concept to deployed tools on quick timelines, apply agile principles, stop what doesn’t work and scale what does.
• Measurement: Track improvements with hard metrics. Use data to drive strategy and execution decisions.

• Commitment to IDinsight's values and mission.
• 8–15 years of professional experience, with significant time in consulting, digital transformation, product management, or technology implementation, ideally serving governments, foundations, or social sector organizations.
• People management: Track record of building, managing, and developing high-performing teams that include both technical and non-technical roles.
• Product leadership: Experience owning a product roadmap end-to-end, from user research and problem definition through build, launch, measurement, and iteration.
• Client-facing consulting: Experience leading complex advisory engagements, managing senior client relationships, and delivering results against defined success metrics.
• Technical fluency: Strong understanding of LLM capabilities and limitations, AI agent architectures, and the practical realities of deploying AI in organizations. Ability to credibly direct a technical team. The role does not require production coding skills.

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