Case Study 3: AI Knowledge Portal

This case study presents the development of an enterprise AI enablement product at The World Bank, designed to support employees across different stages of AI adoption, from discovering AI capabilities and building knowledge to using AI responsibly and exploring opportunities to build AI solutions. The AI Knowledge Portal brings together AI products, learning, community, governance guidance, and development resources into a single experience supporting organisation-wide AI adoption.

PRODUCT STRATEGY
Product Context
The AI Knowledge Portal serves as the Enablement layer of the World Bank Group’s AI Platform, following the Access layer with AI Chat and AI Search.
Its role is to help employees navigate the growing AI landscape, from discovering available products and resources to learning, engaging with the AI community, using AI responsibly, and eventually building AI solutions.
Business Problem
As AI capabilities expanded across the organisation, the World Bank Group faced a growing challenge of making these capabilities discoverable, understandable, and scalable across a diverse global workforce.

Key organisational challenges:
  • connecting AI access with broader adoption;
  • increasing visibility and reuse of existing AI capabilities;
  • connecting learning and guidance with practical application;
  • scaling responsible AI adoption;
  • creating pathways from AI use to experimentation and development.
Product Vision
Create central AI Knowledge Portal that helps employees move from discovering AI to learning, engaging, using AI responsibly, innovating, and ultimately building with it. The Portal connects AI products, education, community, governance, innovation, and development resources into a coherent experience that supports organisation-wide AI adoption.
AI Use Case Discovery
The product scope was shaped at the intersection of employee needs and organisational priorities, with analysis of AI adoption journeys helping identify the key product capabilities required to support adoption.

These translated into core product areas:
  • Discover. Find internal AI initiatives and approved external AI capabilities.
  • Learn. Build AI knowledge and practical skills, and learn from AI Champions.
  • Engage. Connect with AI communities, events, and organisational knowledge.
  • Use Responsibly. Access governance, policies, and responsible AI guidance.
  • Innovate. Explore existing AI ideas and propose new opportunities for AI solutions.
  • Build. Access AI Factory and approved APIs to safely experiment with AI capabilities and evaluate their potential for new internal AI initiatives.
PRODUCT DISCOVERY

Product discovery was grounded in organisational priorities and focused on understanding the employees the Portal needed to support. Key employee segments and their business objectives helped define the AI needs the product needed to address, while key user journeys showed how employees would engage with AI across different scenarios. These insights informed the product capabilities and architecture that followed.

Key Employee Segments

  • Data & Research
    Role: Data Analyst
    Objective: Turn data and research into actionable insights.
    AI Need: Discover AI tools, knowledge, and use cases relevant to analytical work.
  • Operations
    Role: Operations Manager
    Objective: Improve efficiency and automate repetitive work.
    AI Need: Find practical AI solutions and examples that can be applied to operational workflows.
  • Investment
    Role: Investment Specialist
    Objective: Support investment analysis and decision-making.
    AI Need: Discover relevant AI capabilities, knowledge, and examples across the organisation.
  • Leadership
    Role: Manager
    Objective: Understand AI opportunities and support adoption within teams.
    AI Need: Access AI initiatives, adoption insights, governance guidance, and relevant organisational knowledge.
  • Technology
    Role: Developer / IT Specialist
    Objective: Explore and implement AI capabilities.
    AI Need: Access technical resources, APIs, development tools, and reusable AI solutions.
  • Country Programs
    Role: Policy Specialist
    Objective: Support country programmes and development priorities through analysis and evidence.
    AI Need: Find relevant research, institutional knowledge, and AI use cases for programme and policy work.

Key User Journeys

The identified needs were translated into role-specific AI adoption journeys, covering discovery, learning, community engagement, responsible use, reuse, innovation, and AI development. Each journey connects a specific employee need with the relevant Portal capabilities and next step, creating multiple pathways through the same product.

  • Discover
    Find and reuse relevant AI capabilities
    • Discover AI initiatives
    • Explore products and use cases
    • Identify relevant entry points
  • Connect
    Build AI knowledge through communities
    • Discover events and communities
    • Connect with AI Champions
    • Share knowledge and experience
  • Learn
    Build practical AI capability
    • Explore learning resources
    • Follow relevant learning paths
    • Apply AI in daily work
  • Align
    Support informed AI adoption across teams
    • Understand AI initiatives
    • Assess adoption and maturity
    • Identify scaling opportunities
  • Govern
    Enable safe and responsible AI use
    • Understand governance requirements
    • Assess AI-related risks
    • Identify mitigation approaches
  • Create
    Move from AI capabilities to new solutions
    • Explore approved APIs
    • Experiment through AI Factory
    • Build and evaluate solutions
  • Scale
    Reuse proven AI solutions across teams
    • Discover existing solutions
    • Access documentation and owners
    • Adapt solutions for new contexts
  • Apply
    Identify AI opportunities in operational work
    • Identify workflow inefficiencies
    • Explore relevant AI solutions
    • Integrate AI into workflows

Product Architecture Diagram

These user needs and journeys informed the product architecture, translating diverse adoption needs into a structured navigation layer for the World Bank’s AI Platform. The Portal brings together core areas, AI Visibility, AI Education, AI Community, AI Governance, and AI Execution, providing connected pathways from discovering and learning about AI to responsible use, experimentation, and AI development.

Beta Release
An initial beta version provided an early product foundation for validating the Portal’s structure, content model, and user experience before further evolution.
PRODUCT

The Portal is structured around 7 core product capabilities designed to support different stages of AI adoption, from orientation and discovery to learning, responsible use, innovation, and development. This structure translates a complex AI landscape into clear pathways that help employees find relevant capabilities, build confidence, apply AI, and identify opportunities to do more.

1. Overview.
Orientation layer
Context. The growing number of AI products, learning resources, initiatives, and communities created a complex environment for employees to navigate.

Solution. The Portal provides a central orientation layer and continuously curated entry point, surfacing the most relevant and up-to-date AI capabilities, resources, and opportunities in one place.

Value. Reduces the effort required to navigate a constantly evolving AI landscape and helps employees quickly discover what is most relevant right now.
2. Discover.
AI visibility and Reuse
Context. AI products, initiatives, and use cases were distributed across teams and functions, making it difficult for employees to understand what already existed or find relevant solutions.

Solution. Create a consolidated discovery layer that makes existing AI capabilities and their application across the organisation visible.

Value. Enable employees to discover, understand, and reuse existing AI capabilities, reducing duplication and supporting broader adoption.
3. Learn.
AI Literacy
Context. Employees could learn about AI through courses, internal articles, news, blogs, and practical prompts, but these learning opportunities were not connected through a single AI-focused experience.

Solution. Portal curates AI-related content from existing organisational resources and connects it through a dedicated AI learning journey, creating a bridge between learning and hands-on adoption.

Value: Supports employees in developing AI knowledge and moving from awareness toward practical application.
4. Engage Section.
Community and Adoption
Context. As AI adoption grew, employees needed a central space to connect with AI experts, communities, events, and organisational knowledge beyond individual AI products.

Solution. Brings together events, announcements, communities, and training requests, creating multiple ways for employees to engage beyond individual AI products. It supports knowledge sharing, visibility of AI initiatives, connection with AI Champions and communities, and access to learning opportunities tailored to team needs.

Value. Turns AI adoption from an individual activity into a shared organisational capability, helping employees learn from each other, discover relevant initiatives, and spread proven practices across teams.
5. Use Responsibly.
AI Governance
Context. Responsible AI guidance, risk information, and policies were distributed across different organisational resources.

Solution. The Portal brought responsible-use guidance and risk resources into a dedicated part of the AI adoption journey.

Value. Makes responsible AI guidance part of the employee journey rather than a separate governance resource, supporting safer adoption, clearer decision-making, and more consistent application of AI policies across the organisation.
6. Innovate.
Centralized AI Ideas Hub
Context. In a large organisation, AI ideas could emerge across many teams and channels, making them difficult to consolidate and connect with existing initiatives.

Solution. The Portal creates a central space where employees can explore existing ideas, check available AI products, and propose new AI opportunities through a structured submission process.

Value. Creates a pathway from employee ideas to AI opportunity assessment and prioritisation.
7. AI Factory.
AI Development Gateway
Context. Employees and teams exploring AI needed a clearer path from discovering capabilities to experimenting with and building AI solutions.

Solution. The Portal connects users to AI Factory capabilities including the Model Garden, AI Playground, API documentation, and guided development resources.

Value. Provides a clear path from AI discovery and experimentation toward development, making internal AI building capabilities more discoverable to teams considering internal AI initiatives.
Product Evolution
The Portal evolved into a central entry point for navigating the organisation’s growing AI capabilities, connecting discovery, learning, responsible use, collaboration, innovation, and development within one experience. By making AI capabilities and organisational knowledge easier to discover and act on, the product supported a more connected path from AI awareness to practical adoption and new AI opportunities.
METRICS AND IMPACT

The Portal’s business impact was reflected in broader AI adoption and the resulting efficiency gains from using AI in day-to-day work. Product performance was primarily measured through user activity and engagement across the Portal, providing signals of reach, adoption, and continued use.

Enterprise Impact
Organization-wide rollout
Across 20,000+ internal employees in 189 member countries.

Increased AI Discoverability
The Portal made existing AI products, initiatives, learning resources, and expertise easier to find, reflected in strong engagement with AI product discovery.

Streamlined AI Access
The curated Overview and structured pathways helped employees find relevant AI resources more quickly and understand where to go next.

Connected AI Adoption Journey
The Portal connected discovery, learning, responsible use, engagement, innovation, and development, helping employees move from exploring AI toward practical use.

Employee-driven Innovation
The Ideas Hub created a structured pathway for employees to contribute new AI opportunities to the organisation.
Product Performance
~65% Returning Users
Around two thirds of users came back to the Portal after their first visit, showing that it became a useful resource rather than a one-time destination.

~70% AI Product Discovery
Around 70% of active users explored AI products, initiatives, or use cases through the Portal.

~50% Learning to Practice
Around half of users engaging with practical AI learning went on to try a prompt or access an AI capability, showing a connection between learning and hands-on use.

~30% Cross-team AI Product Use
Around one third of discovered AI products attracted users beyond their original team or business area, indicating growing visibility and reuse of existing solutions.

100+ AI Idnitiatives Submitted
Employees used the Ideas Hub to propose new opportunities for applying AI to products, services, and internal workflows.
ROLE AND DELIVERY
My Role
My official role at The World Bank was Senior Consultant, working within the organisation’s AI-focused technology department. For the AI Knowledge Portal, I contributed across product strategy, discovery, product definition, and delivery — helping shape the Portal’s role within the AI Platform, define its core capabilities and employee journeys, and translate the product direction into a working enterprise experience. My work bridged organisational priorities, employee needs, content and technology constraints, and cross-functional delivery, working closely with stakeholders and engineering from early product definition through implementation.

Product Strategy and Definition
Helped shape the Portal’s role within the World Bank AI Platform, translating organisational priorities into product direction, core capabilities, and priorities.

Product Discovery
Defined employee journeys, AI use cases, and key user needs, translating them into the Portal’s product structure and capability model.

Product Architecture and Development
Shaped how the Portal’s capabilities, content, and resources were organised, turning the product strategy into a coherent employee experience and working product.

Product Delivery and Execution
Owned key parts of the product delivery process — from requirements, user stories, and acceptance criteria to prioritisation, prototyping, validation, and close collaboration with engineering and stakeholders.
Delivery Approach
The product was delivered through an iterative Agile approach, combining structured planning, cross-functional collaboration, and continuous feedback.

Plan. Product priorities and roadmap were translated into epics, user stories, acceptance criteria, and tasks in Azure DevOps.
Explore. Product, engineering, data, and architecture teams worked together to explore solutions, clarify requirements, and align on technical feasibility.
Deliver. Work progressed through Agile/Scrum cycles, including planning, backlog refinement, daily coordination, and sprint reviews.
Learn and Iterate. User feedback, testing, and adoption insights informed product decisions and subsequent iterations.
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