Technology & AI Adoption Specialist – Operations

International Rescue Committee•Nairobi, NY

14h•$88,277 - $102,451•Remote

About The Position

The Technology & AI Adoption Specialist – Operations will drive the uptake of AI across IRC’s global operations by working directly with teams to identify, test, and scale high-value use cases. This role is responsible for ensuring AI tools translate into real improvements in how IRC works. The Specialist will manage a pipeline of AI opportunities across internal functions (e.g., Finance, Supply Chain, HR), embedding with teams to diagnose needs, co-design solutions, and support adoption through to sustained use. The Specialist acts as the bridge between operational teams (product owners) and technical developers, owning problem definition and user adoption so that development resources are deployed against well-scoped, high-value briefs.

Requirements

Minimum 6 years of experience in change management, digital transformation, business analysis, learning & development, or related roles
Strong familiarity with AI tools and applications, and ability to translate their capabilities and limitations into practical use cases and workflow improvements
Experience driving adoption of AI and other technology solutions in complex, matrixed organizations, from problem identification through implementation and sustained use
Strong problem-solving and analytical skills, including the ability to diagnose operational challenges, define clear problem statements and requirements, and analyze and redesign workflows to embed solutions into day-to-day operations
Experience designing and delivering training or capacity-building initiatives
Strong data orientation, including the ability to use data to inform decisions and track impact
Excellent interpersonal skills and track record of building networks (e.g., champions, communities of practice) to support adoption
Demonstrated ability to drive alignment and behavior change without direct authority
Experience working in international development, humanitarian, or nonprofit contexts strongly preferred
Ability to operate in low-resource, high-complexity environments
Fluency in English required; proficiency in French, Spanish, or Arabic preferred

Responsibilities

Establish and manage a structured pipeline of AI opportunities across departments, including clear problem definitions, requirements, and expected ROI
Maintain a shared intake and prioritization process with technical teams, ensuring the pipeline reflects both operational need and development capacity
Track use cases from intake through pilot, iteration, and scale
Coordinate with cross-functional teams to align on development, deployment, and support
Monitor outcomes and performance against defined success criteria (e.g., efficiency gains, time saved, adoption), providing visibility on progress, key bottlenecks, and lessons learned
Identify and prioritize high-impact AI use cases across internal functions, in close collaboration with AI Governance and Risk Transformation Lead and relevant product owners in functional domains
Work directly with teams to understand workflows, diagnose pain points, and define clear problem statements and requirements suited to AI
Map current-state and future-state processes and translate needs into developer-ready artifacts (e.g., user stories, workflows) that enable technical teams to build without additional requirements gathering
Co-design, test, and iterate solutions with end users and technical teams, including supporting user acceptance testing
Support AI deployment into live workflows, ensuring solutions are practical, ambitious, adopted, and sustained
Document and package successful use cases for replication and scale; ensure learnings from each use case deployment improves the next
Define and maintain appropriate handoff points with development team throughout product lifecycle
Lead AI adoption within targeted teams, ensuring solutions are embedded into redesigned workflows rather than layered onto existing ones
Serve as the primary point of contact for end-users post-deployment, absorbing support and iteration requests before they reach the development team
Identify and address barriers to adoption, including resistance, capability gaps, and process misalignment
Develop practical adoption strategies that drive consistent, confident use
Design and deliver targeted, role-specific learning and practical resources (e.g., workflows, prompts, job aids)
Develop clear, practical communications that translate AI initiatives into accessible, relevant narratives tied to impact
Create materials such as FAQs, use cases, and success stories that reinforce adoption and learning