Enterprise AI Analysis
INSYTE: A Classification Framework for Traditional to Agentic AI Systems
The INSYTE framework offers a robust, multi-faceted approach to classifying AI systems, from traditional rule-based to advanced agentic AI. It addresses the limitations of existing unidimensional Levels of Autonomy frameworks by evaluating AI systems across eight key dimensions grouped into four categories: system design, functionality, operating environment, and operational independence.
Unlocking AI System Potential
Our deep dive into the INSYTE framework reveals its capacity to provide nuanced classifications, fostering clearer communication and supporting strategic decision-making in AI deployment and regulation.
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Key Dimensions
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Classification Levels
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Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Understanding the INSYTE Framework
The INSYTE framework is designed to provide a comprehensive and nuanced classification of AI systems by breaking down essential characteristics into eight dimensions. These dimensions are grouped into four categories: system design (underspecification and adaptiveness); system functionality (breadth and depth); operating environment (diversity and dynamism); and independence from human operational control (intervention and oversight). Each dimension is assessed on a level from 0 to 5, allowing for a detailed and contextual 'whole system' view.
INSYTE Classification Process
The INSYTE classification process is systematic and user-friendly, guiding stakeholders through each step to accurately classify AI systems.
Identify System Objectives
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Assess 8 Dimensions (Level 0-5)
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Generate Radar Chart Pattern
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Review Justification Report
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Compare System Variants
Key Benefits of INSYTE Adoption
The INSYTE framework offers significant advantages for various stakeholders across the AI lifecycle, from design to regulation.
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Seamless Cross-Stakeholder Communication
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Enhanced Design & Deployment Decisions
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Robust Safety Engineering & Assurance
Regulatory Clarity for Agentic AI
INSYTE aids in developing risk-based regulatory regimes by offering a nuanced perspective on autonomy, identifying risk-relevant characteristics often overlooked by simpler classifications.
High Impact Regulatory AlignmentComparing AI System Variants (CLARA)
Illustrative comparison of CLARA, a clinical conversational AI assistant, across its four versions using INSYTE dimensions.
| Dimension | CLARA 1 | CLARA 2 | CLARA 3 | CLARA 4 |
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| Underspecification | Rule-based, pre-specified flows. | LLM-based, minimal rules, few-shot examples. | Hybrid: deterministic backbone, LLM-generated responses. | Agentic LLM, high-level objectives, learning from data. |
| Adaptiveness | Reacts to single uncertainty (unclear patient utterances) using predefined tactics. | Proactively reacts to multiple, foreseen types of uncertainty using dynamic tactics. | Reacts to few, foreseen uncertainty types with predefined and dynamic tactics. | Proactively reacts to multiple, foreseen uncertainties using highly dynamic tactics. |
| Breadth of functionality | Single clinical conversation, few output types. | Variants of clinical conversation, few output/task types. | Variants of clinical conversation, few output/task types. | Many different task types (conversations, explanations, follow-up actions). |
Healthcare Sector Example: CLARA
CLARA, a cloud-based clinical conversational assistant, demonstrates how INSYTE can illustrate the increasing sophistication of AI systems. From CLARA 1 (rule-based, scripted conversations) to CLARA 4 (agentic LLM-based system with 'tools' for ordering tests and prescribing medicine), the framework provides a clear trajectory of AI development. This highlights INSYTE's utility in illustrating research and development trajectories.
Calculate Your Potential ROI
Our interactive ROI calculator helps you estimate the potential savings and reclaimed hours by integrating advanced AI systems into your enterprise. Input your team size, weekly hours spent on tasks, and average hourly rate to see the impact.
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Your AI Implementation Roadmap
A structured approach to AI implementation ensures successful integration and maximum impact. Our roadmap outlines key phases for adopting INSYTE and advanced AI systems.
Assessment & Strategy
Conduct a comprehensive INSYTE assessment of existing systems and define strategic AI integration goals.
Pilot Program & Validation
Implement INSYTE for a pilot AI project, validate classifications, and refine strategies based on early results.
Full-Scale Deployment
Roll out INSYTE across relevant AI systems, fostering cross-functional understanding and informing governance.
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