AI Frameworks
Proven methodologies and decision frameworks for enterprise AI leaders.
Enterprise AI LLM Selection Framework
A structured approach to evaluating and selecting large language models for enterprise use — with specific guidance for Healthcare and Financial Services.
- Understand LLM categories and capabilities
- Evaluate realistic cost scenarios
- Navigate governance and compliance tradeoffs
- Account for industry-specific constraints
Additional Frameworks
AI Maturity Model
Assess your organization's readiness across technology, people, process, and governance dimensions.
AI Cost of Ownership Framework
Model the true cost of AI initiatives — including hidden infrastructure, talent, and maintenance costs.
AI Governance Readiness Checklist
Evaluate your organization's preparedness for responsible AI deployment and ongoing oversight.
How to Use These Frameworks
Each framework answers a decision most organizations hit in the same order: how ready are we, which model fits, what will it actually cost, and who is accountable when it goes live.
They are built from client work in Healthcare, Financial Services, and Technology, so the questions assume real constraints: existing vendor agreements, regulated data, audit expectations, and teams who already have day jobs.
You can use any one on its own. Together they form a straightforward path from assessment to a governed, funded rollout.