CorpExcellence Research
AI Research
Practical research for leaders who need to adopt, govern and secure AI. Each topic page explains the issue, the risks and the questions to ask before you commit budget or sign off on a system.
Research areas
AI Strategy & Adoption
Choosing where AI creates value, funding it, organizing for it and building the skills to use it.
Generative & Agentic AI
Foundation models, copilots, agents and the knowledge systems that ground them.
AI Governance, Risk & Compliance
Regulations, frameworks, risk assessment, responsible AI, vendor risk and assurance.
AI Security
Protecting AI systems, securing the AI supply chain, countering AI-enabled fraud and using AI for defense.
Data for AI
The quality, governance, lineage and privacy controls that make data usable for AI.
AI Infrastructure & Operations
Compute and platforms, MLOps and LLMOps, evaluation and monitoring, and the cost of running AI.
How this research is organized
The library covers six areas of AI, from strategy and adoption through governance, security, data and operations. Each area has focused topic pages that follow the same structure: what the topic is, why it matters, what good practice looks like, common pitfalls and how to get started.
How to use it
Start with the area closest to the decision in front of you. Use the topic pages to frame conversations with your team, vendors or board. For more depth, see Research Reports. If you are building AI governance skills, see our Certifications guides.
Free articles on the same six areas are published under Insights.
Questions leaders should ask
- Which AI decision must we make in the next two quarters?
- Do we know every AI system in use, including in vendor products?
- Which AI risks would our board expect us to have a position on?