Essential
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Bachelor’s degree in Technology, Computer Science, Engineering, Business, Social Sciences, or a related field.
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At least 5 years of professional experience in technology, consulting, product development, international development, or related fields.
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Demonstrated experience driving adoption of new tools, systems, or ways of working in complex, multi-stakeholder environments.
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Proven ability to lead projects end-to-end, managing multiple workstreams simultaneously from conception through to delivery and evaluation.
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Proven ability to influence without formal authority and build collaborative relationships across organizational levels and geographies.
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Strong change management and stakeholder engagement skills, with demonstrated experience driving behaviour change initiatives in complex organizational environments.
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Be a quick learner about a range of domains and ability to understand what constitutes a string AI solution for each of the areas we work in.
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Working knowledge of AI tools (e.g., Claude, ChatGPT, Gemini, Notebook LLM) with ability to identify practical applications and articulate their value to non-technical audiences. Comfort working with technical departments to translate user needs into implementable solutions.
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Proven ability to bridge technical and non-technical teams, translating complex technical concepts into accessible language and organizational requirements into technical specifications.
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Demonstrated curiosity about AI/ML developments, with ability to assess emerging tools and techniques for organizational fit without requiring deep technical implementation skills.
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Excellent facilitation, presentation, and communication skills, with proven ability to make technical concepts accessible and engaging for non-technical audiences.
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Analytical mindset with comfort using data to track progress, identify patterns, and inform decisions.
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Demonstrated experience leading cross-functional change initiatives, influencing diverse stakeholders, and driving adoption in complex organizational environments.
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Excellent written and verbal communication skills in English.
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Legal authorization to work in Kenya or Nigeria without sponsorship.
AI Strategy and Leadership (20%)**
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Develop and own the Africa region AI adoption roadmap, translating global AI strategy into contextually relevant plans across diverse country environments.
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In collaboration with technical partners, pressure-test AI/ML ideas and proposals, balancing technical feasibility with organizational ambition and operational constraints.
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Provide strategic counsel to regional and country leadership on AI adoption progress, risks, opportunities, and return on investment.
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Contribute to global AI strategy discussions and serve as the Africa voice in cross-regional AI communities of practice alongside sharing knowledge and coordinating enterprise-wide progress with peers in India and the US.
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Ensure AI initiatives are governed responsibly, with attention to data privacy, ethical AI frameworks, and compliance with relevant regulations across country contexts.
Use Case Identification and Prototype Development (30%)****
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Drive discovery and prioritization of high-impact AI use cases that address real workflow challenges across programs, MLE, finance, operations, and P&C functions.
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Coordinate the design of AI solutions in partnership with departmental teams/ functional experts, defining clear scope, success metrics, and realistic timelines for proof-of-concepts and minimum viable products. Coordinate prototyping efforts rather than building solutions independently. Ensure that functional teams remain owners of use cases while you provide structure, coordination, and support.
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Manage the full pilot lifecycle from ideation and testing through evaluation and scaling decisions, ensuring rigorous documentation and learning capture.
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Facilitate cross-team learning from pilot successes and failures, creating feedback loops that accelerate organizational learning and position solutions for broader adoption.
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Maintain awareness of the AI tool landscape and translate emerging developments into accessible, actionable insights for non-technical audiences.
End-to-End Delivery and Partner Management (20%)****
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Oversee the delivery of AI projects end-to-end, coordinating the transition of validated prototypes into scalable solutions by working with internal technical teams and external partners
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Manage external technical partners and vendors, including selection, contracting, performance oversight, and risk mitigation, ensuring timely delivery to quality standards.
Change Management and Capability Building (20%)****
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Design and execute a region-wide AI adoption strategy that drives sustained behavior change across diverse country contexts and functions.
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Build and steward a network of AI champions across countries and functions to amplify adoption efforts and sustain momentum.
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Design and facilitate engaging learning events, including workshops, show-and-tell sessions, and peer learning forums that encourage experimentation and knowledge sharing.
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Embed AI learning into onboarding and ongoing professional development for Africa region staff, curating and developing practical materials including guides, prompt libraries, and use case repositories.
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Develop communication campaigns that demonstrate AI value propositions, address adoption barriers, and build staff confidence in using AI tools effectively.
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Collaborate with IT teams on license optimization, monitoring usage patterns across the region and making evidence-based recommendations for reallocation.
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Build internal capability by enabling operations and program teams to sustain and scale AI products post-launch, reducing dependency on external support over time.
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This is a core pillar of success for the role.
Monitoring, Evaluation, and Reporting (10%)**
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Establish and maintain dashboards tracking license utilization, user engagement, pilot outcomes, and impact metrics against strategic OKRs.
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Conduct regular pulse checks and surveys to assess user satisfaction, adoption barriers, and workflow impact across the region.
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Provide monthly progress reports to regional leadership, highlighting trends, surfacing risks, and recommending interventions.
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Analyse usage data to identify patterns, bottlenecks, and opportunities for targeted support. This will inform prioritization and resource allocation decisions.