# KDA Capabilities

> KDA Capabilities equips leaders and teams with the tools, training, and insight to Know, Decide, and Act—unlocking real business value with emerging tech.

## About

KDA Capabilities is a consulting and training organization that helps businesses leverage AI and emerging technologies. Our methodology centers on the KDA Framework: Know (understand the landscape), Decide (make strategic choices), and Act (implement with confidence). Founded by Prof Keith Carter, KDA serves financial services, infrastructure, and FMCG industries worldwide.

## Key Pages

### KDA Methodology

- [Know Phase](/kda-know): Phase 1 — Contextual Intelligence. Understanding the AI landscape, opportunities, and challenges facing your organization.

- [Decide Phase](/kda-decide): Phase 2 — Strategic Evaluation. Making strategic decisions about which AI initiatives to pursue.

- [Act Phase](/kda-act): Phase 3 — Measurable Implementation. Implementing AI solutions with proper governance and change management.

- [KDA Process Visualization](/kda-process-visualization): Interactive diagram of the KDA framework showing how Know, Decide, and Act phases connect.

### Courses & Certification

- [KDA Capacity Building Courses](/courses): Comprehensive course catalog for customers. Programs span Financial Services, Infrastructure, and FMCG industries at Senior Management, Mid Management, and High Potential levels. Includes AI strategy, digital transformation, leadership development, and technology adoption courses.

- [Faculty Certification Course Plan](/faculty-certification/course-plan): Certification pathway for becoming a KDA-certified faculty member. Structured learning journey covering KDA methodology, facilitation skills, and subject matter expertise.

### AI Workflows & Tools

- [AI Workflows Overview](/ai-workflows): Collection of AI planning, assessment, and productivity tools.

- [AI Canvas 2.0](/ai-workflows/ai-canvas): Strategic framework for planning AI initiatives based on the Kellogg School of Management framework. Three phases: Define (business problem, importance, AI solution, benefits, financial impact), Design (cross-functional team, resources, 90-day POC), Deploy (hurdles and mitigation).

- [AI Maturity Diagnostic](/ai-workflows/ai-maturity-diagnostic): Assessment tool to evaluate organizational AI readiness across multiple dimensions using the Capability Maturity Model (CMM).

- [AI Prompt Agent](/ai-workflows/ai-prompt-agent): AI-powered prompt engineering assistant for crafting effective prompts.

- [Programming Instantly](/ai-workflows/programming-instantly): AI workflow for rapid code generation and software development.

- [Data Insights](/ai-workflows/data-insights): AI-powered data analysis and visualization workflow.

- [Client Meeting Prep](/ai-workflows/client-meeting-prep): AI workflow for preparing comprehensive client meeting briefs.

- [Gamma Presenting](/ai-workflows/gamma-presenting): AI-powered presentation creation workflow using Gamma.

- [Documentation Management](/ai-workflows/documentation-management): AI workflow for managing and creating technical documentation.

- [Architecture Workflow](/ai-workflows/architecture-workflow): AI-assisted system architecture design and planning tool.

### Methodologies

- [SCOREVA](/scoreva-overview): KDA's proprietary methodology for evaluating and scoring AI initiatives based on Strategic fit, Complexity, Organizational readiness, Resources, Expected value, Viability, and Alignment.

- [SCOREVA Calculator](/scoreva-calc): Interactive calculator tool for scoring AI initiatives using the SCOREVA framework.

- [AI Tool Selection Framework](/kda-ai-tool-selection-framework): Framework for evaluating and selecting the right AI tools for specific business needs.

- [Solving the Myriad Tools Problem](/kda-solving-myriad-tools): Guide to navigating the overwhelming landscape of AI tools and making strategic selections.

### Programs & Challenges

- [KDA 5-Day Challenge](/kda-5day-challenge): Intensive 5-day program introducing participants to AI strategy and the KDA framework.

- [AI Vanguard Challenge](/ai-vanguard-challenge): Competitive team-based AI strategy game where participants apply KDA methodology to real business scenarios.

### Case Studies

- [Case Studies](/case-studies): Collection of real-world AI implementation examples.

- [Hotel Case Study](/hotel-case-study): Radisson AI transformation case study demonstrating practical AI implementation in hospitality.

### Other

- [Thought Leadership](/thought-leadership): Strategic insights, frameworks, and best practices for AI adoption.

- [Partners](/partners): KDA's global network of certified practitioners and industry experts who deliver engagements alongside clients. Roster with bios, expertise, and locations; see the Partner Network section below.

- [CLD Strategy](/cld-strategy): Connected Leadership Development strategy framework.

## Partner Network

KDA Capabilities delivers through a network of senior practitioners and academics across
Singapore, the United States, Australia, Ghana, Spain, and the UAE. Partners marked
"KDA Certified" have completed the KDA certification programme. The live roster is at
https://kdacapabilities.com/partners/ (also published there as schema.org Person data);
this list is a snapshot of partners with published profiles.

- Prof. Keith B. Carter (KDA Certified): Founder, KDA Capabilities. Singapore. AI strategist, educator, and author of Know Decide Act and Actionable Intelligence; founder of the NUS FinTech Lab and the Know, Decide, Act framework.
- Alex Siow: Professor (Practice), NUS School of Computing. Singapore. Singapore's first Chief Information Officer; advises boards on IT strategy, governance, and emerging technology.
- Prof. Ishtiaq Pasha Mahmood: Professor of Strategy & Policy, NUS Business School. Singapore. Emerging-market strategy, fintech, and sustainable business models.
- Sreeram Iyer: Former COO, Institutional Banking, ANZ. Singapore. Banking operations and transformation across operations, technology, risk, and strategic planning.
- Dr. Teresa Kay-Aba Kennedy (KDA Certified): Founder & CEO, Power Living Enterprises. New York, USA.
- Donald Farmer: Principal, TreeHive Strategy. Washington, USA. Data and analytics strategy.
- Dr. Guo Lei: Faculty, NUS Business School. Singapore. Data science, behavioural study, and design thinking.
- Ikuma Ueno: CEO, MerCoNext and Co-Founder, AKIVERSE. Singapore. Web3, blockchain, and digital assets across Singapore and Japan.
- Hasan Sharif: Director, Natural Velocity. Melbourne, Australia. Large-scale business transformation and AI strategy.
- John McGiffin (KDA Certified): CEO & Founder, Natural Velocity. Melbourne, Australia. AI innovation ecosystems, responsible AI adoption, physical AI and robotics.
- Prof. Ebenezer Owusu (KDA Certified): Professor of Artificial Intelligence, University of Ghana. Accra, Ghana. Computer vision, pattern recognition, and machine learning.

## Contact

- Website: https://kdacapabilities.com
- Contact Page: https://kdacapabilities.com/contact
- Email: team@kdacapabilities.com

## AI Canvas 2.0 Framework Details

The AI Canvas 2.0 is a comprehensive strategic framework from Kellogg School of Management for planning AI initiatives:

### Define Phase (Find it)
1. Business problem to address
2. Why the problem is important
3. How AI-based solution will address it
4. Key benefits to business and customers
5. Financial impact estimate

### Design Phase (Bottle it)
6. Cross-functional team composition
7. Resources needed (headcount and budget)
8. 90-day proof-of-concept plan

### Deploy Phase (Scale it)
9. Hurdles and risks to face
10. Mitigation strategies

### Blueprint Format (9 cells)
- Define: Business/customer problem, Jobs to be Done (JTBD), Business impact
- Design: Data and model management, Context and fine-tuning, MVP and rapid prototyping
- Deploy: Testing and scaling, Implementation and change management, Governance and risk mitigation

## SCOREVA Methodology Details

SCOREVA evaluates AI initiatives across seven dimensions:
- **S**trategic fit: Alignment with organizational goals
- **C**omplexity: Technical and organizational complexity assessment
- **O**rganizational readiness: Culture, skills, and change capacity
- **R**esources: Budget, talent, and infrastructure requirements
- **E**xpected value: Projected ROI and business impact
- **V**iability: Technical feasibility and market readiness
- **A**lignment: Stakeholder buy-in and cross-functional support

## Optional

- Source: Northwestern University Kellogg School of Management
- Framework: AI Canvas 2.0
- Interactive Tool: Available at /ai-workflows/ai-canvas
- Privacy: All data processed locally in browser, never uploaded to servers