Strategic Consulting
Bangkok, Thailand
Assessment Framework
Our multi-layered assessment system evaluates AI readiness at every level — from individual skills to organizational maturity to executive leadership capability.
Individual Assessment
Our assessment covers the full spectrum of AI competency — from foundational literacy to strategic leadership — aligned with frameworks from UNESCO, the World Economic Forum, and leading consulting firms.
Level 1
The building blocks of AI literacy. Everyone in a modern organization needs these baseline competencies to participate meaningfully in AI-related discussions and decisions.
Level 2
Practical ability to use AI tools in daily work. These competencies distinguish productive AI users from passive observers.
Level 3
Deep technical capabilities for building, deploying, and maintaining AI systems. Required for engineering and data science roles.
Level 4
The ability to drive organizational AI transformation. Essential for executives and senior leaders responsible for AI strategy.
Beyond technical skills: Research from Fortune and the World Economic Forum highlights that critical thinking, creative problem-solving, and communication are the true differentiators in the AI era. Our framework assesses both technical capability and these essential human skills that AI cannot replicate.
Adoption Profile
Based on Everett Rogers’ Diffusion of Innovation theory, our AI Adoption Profile assessment identifies where individuals and teams fall on the adoption spectrum — enabling targeted strategies that accelerate readiness across every segment.
Early experimenters who embrace uncertainty and actively seek out new AI technologies. They prototype, test, and iterate — often before formal organizational support exists.
Influential decision-makers who recognize AI's transformative value. They adopt strategically and help build the case for broader organizational investment.
Pragmatic professionals who adopt AI once clear evidence of value exists. They need structured training, proven use cases, and organizational support.
Skeptical adopters who require widespread acceptance before engaging with AI tools. They adopt out of necessity and need significant support.
Resistant to change, they adopt AI only when it becomes unavoidable. Addressing their concerns requires empathy, hands-on guidance, and patience.
Our AI Adoption Profile evaluates four key dimensions through a structured 5-10 minute assessment, producing personalized recommendations for each individual.
Familiarity with AI technologies, understanding of benefits and limitations, frequency of staying updated on developments
Hands-on experience with AI tools, types of solutions used (advanced models, productivity tools, consumer apps), confidence levels
Emotional response to AI, key concerns (ethics, privacy, job displacement), willingness to learn and experiment with new tools
6-12 month adoption intentions, types of support needed (training, workshops, education programs, mentoring, peer learning)
Organizational Assessment
Beyond individual skills, we assess organizational readiness across five critical dimensions. Our maturity model identifies where your organization stands and provides a clear roadmap for progression.
Each dimension is scored across five maturity levels, providing a clear picture of current capabilities and the specific steps needed to advance.
No formal AI capability; awareness is limited or non-existent
Basic understanding; pilot projects underway with limited scope
Structured approach; AI integrated into selected processes
Systematic deployment; measurable outcomes across departments
Advanced, integrated, continuous improvement; AI-first culture
Strategic Planning Tool
A structured canvas for developing your organization’s AI strategy. Seven interconnected components guide leaders from vision to execution — ensuring alignment between ambition, capability, and governance.
North Star
Define your organization's aspirational AI future — the overarching goal that guides all AI initiatives and investments.
Choices & Approach
Strategic decisions about where to compete with AI, which capabilities to build vs. buy, and how to differentiate.
What We Will Do
Identify and prioritize specific AI use cases by business impact, feasibility, and strategic alignment.
When & How
Phased implementation plan with clear milestones, dependencies, and resource requirements over 12-36 months.
Critical prerequisites: data readiness, talent pipeline, technology infrastructure, change management, and external partnerships.
Budget allocation, team composition, technology costs, training investments, and expected ROI timeline.
Who decides what: AI ethics board, project approval process, risk management framework, and accountability structure.
Executive Assessment
Effective AI transformation requires leadership that understands both the strategic potential and operational realities of AI. Our CIO/Executive AI Competency Assessment evaluates 10 critical dimensions scored across five proficiency levels.
Anticipating disruption — scenario planning, trend analysis, and strategic positioning for AI-driven market shifts.
Integrating AI and technology strategy with core business vision, ensuring every initiative serves organizational goals.
Regulatory frameworks, audit management, ethical AI deployment, and responsible data governance.
Organizational blueprints for human-AI collaboration, value chain optimization, and system integration.
Data strategy, AI adoption maturity, transitioning from model-centric to data-centric approaches.
Threat intelligence for AI systems, incident response, data poisoning mitigation, adversarial robustness.
Cloud/hybrid strategy, specialized compute, scalability, platform modernization for AI workloads.
Agile/Waterfall for AI projects, handling probabilistic outcomes, scaling pilots, stakeholder engagement.
Building innovation pipelines — rapid experimentation, prototyping culture, emerging technology assessment.
Creating value through AI — platform strategies, new revenue streams, digital-first business models.
Basic awareness; relies on others for AI decisions
Can participate in AI discussions; understands key concepts
Independently manages AI initiatives; applies frameworks
Drives AI strategy; mentors teams; leads complex projects
Shapes industry standards; innovates new approaches; thought leader
Why executive assessment matters: Research from TUAI Center and Thammasat University shows that organizations with AI-competent leadership adopt transformative technologies 2.5x faster and achieve 40% higher ROI on AI investments.
Start with individual competency assessment, then expand to organizational maturity and executive leadership evaluation.