Designing an AI Operating Model with Clear Decision Rights and Learning Loops
A practical method for assigning AI decision rights, choosing mixed operating structures and turning pilot evidence into strategy changes.
The ModelFold Blog
Independent B2B reporting on putting AI to work: picking use cases worth doing, redesigning the work around them, and running them under real governance.
How to Observe Real Work Before Proposing an AI Use Case
A practical field-research method for observing real workflows, testing bottleneck hypotheses and deciding whether AI deserves a controlled trial.
Designing an Intelligent Document Processing Pipeline from Intake to Retention
A practical, technology-neutral guide to designing traceable document processing from secure intake through review, delivery and retention.
Redesigning Exceptions, Approvals and Handoffs Before Workflow Automation
A practical method for mapping real workflows, testing controls, defining handoffs and resolving exceptions before automation begins.
Designing a Source-Grounded Generative AI Drafting Workflow
Build a controlled AI drafting workflow that separates approved evidence from prose, assigns clear reviews and records meaningful changes.
Building a Scenario-Based Evaluation Set for a Business AI System
A practical guide to building reproducible AI evaluation scenarios for ordinary work, difficult boundaries, known failures and prohibited behaviour.
Design a Bounded AI Assistant with Tools, Permissions and Context Limits
A practical method for setting capability-level context, tool permissions, action limits, approvals, refusals and release evidence for business AI assistants.
Redesigning Roles Task by Task When Introducing AI Assistance
A practical method for testing AI against real tasks, tracing redistributed effort and redesigning roles only when workload evidence is sound.
Version Prompts, Models and Workflow Logic as One AI Release
A practical method for binding prompts, models, tools and workflow logic into one testable AI release, with staged promotion and complete rollback.
How to Build an AI Inventory and Risk-Tiering Method Teams Can Maintain
Build a maintainable AI inventory, rate each use across four clear dimensions and route it to proportionate review without implying legal classification.
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Ten topics covering the full life of an AI programme, from first use case to retirement.