Structured AI Maturity Accelerator
SIMA Core™ is the static structural foundation consisting of three core models: AI Dimensions, AI Capability Levels, and AI Tool Categories. It provides the organizing principles for effective and responsible AI maturity.
SIMA Core™ consists of three interconnected models that provide the foundation for strategic AI implementation
Strategy, Governance, Data, People, and Technology AI dimensions serve as organizing principles for assessing organizational readiness.
Initial, Exploring, Applying, Formalizing, Optimizing, and Leading levels provide a roadmap for AI advancement.
Baseline, Business Assistance, Process Automation, Decision Optimization, and Autonomous Execution tools.
Five AI dimensions that serve as organizing principles for assessing organizational readiness and implementing AI in a scalable, ethical, and value-generating manner
Five progressive levels of increasing maturity and capability, each with increasing levels of AI control and growth objectives
AI vision and leadership support begins. Organizations build awareness and start exploring possibilities.
Early AI awareness with disconnected experiments, limited awareness, and lack of strategic direction.
Foundational investments in talent, data quality, and tooling begin to emerge with growing momentum.
AI is prioritized by leadership and increasingly integrated into business processes with formal frameworks.
AI leveraged strategically across functions with robust governance and real-time analytics.
AI is core to strategic differentiation, driving innovation and shaping industry standards.
Five categories of AI tools based on autonomy and functional capabilities, from passive assistants to strategic, independent actors
Purpose: Learn basics, gather usage data
Examples: FAQs, internal wikis, chatbots
Characteristics: Low autonomy, high guidance, static knowledge bases
Purpose: Boost productivity and creativity
Examples: Writing assistants, coding copilots, research summarizers
Characteristics: Dynamic support, task-specific boundaries
Purpose: Free resources, gain efficiency
Examples: RPA bots, automated schedulers, workflow orchestrators
Characteristics: Rule-based logic, deterministic outcomes
Purpose: Find insights, adapt to dynamic input
Examples: Dynamic pricing, route optimization, scenario planners
Characteristics: Predictive modeling, evidence-based recommendations
Purpose: Drive autonomous execution safely
Examples: Self-managing infrastructure, autonomous vehicles, AI command centers
Characteristics: Full autonomy, continuous learning, self-regulation
The purpose of each tool category is not to encourage the use of all tools, but to provide groupings that can be safely applied with reduced risk based on your AI Capability Level. Using complex tools at low capability levels is ill-advised.
Understanding the foundational principles that guide SIMA Core™ implementation
SIMA Core™ is static and provides the structural foundation. SIMA Flow™ provides the dynamic application of the core models, while SIMA Kit™ provides the necessary collateral to apply the Core Models.
The point is not to reach the highest capability, but to use the capability assessment to lay the groundwork for projects and identify areas for improvement.
As organizations mature, they can safely enact AI tools at higher levels with controlled risk. Starting with lower-level tools enhances learning in a less impactful environment.
The AI Dimensions work together to provide a comprehensive approach to AI maturity, ensuring all aspects of the organization are considered and aligned.
Transform your organization with the structural foundation of strategic intelligence management architecture