Designing an AI Operating Model with Clear Decision Rights and Learning Loops
Build an operating model by assigning decision rights, evidence, escalation, and review across standards, funding, delivery, risk, operations, and reuse.
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 verifying workflow pain, locating recurring constraints, and deciding whether AI or a simpler change merits a test.
Design an Intelligent Document Processing Pipeline from Intake to Retention
Build a traceable IDP pipeline with clear stage contracts for intake, extraction, validation, human review, delivery, retention, recovery, and control.
Redesigning Exceptions, Approvals, and Handoffs Before Workflow Automation
Practical guide to mapping real workflows, redesigning exceptions, testing approvals, defining handoffs, and deciding when automation is ready to deploy.
Design a Source-Grounded Generative AI Drafting Workflow
Build a controlled generative AI drafting workflow that separates approved evidence from prose, sets clear reviews, and records consequential changes.
Building a Scenario-Based Evaluation Set for a Business AI System
Build a scenario-based AI evaluation set covering real work, difficult boundaries, known failures, grading, reviewer calibration, and release testing.
Design a Bounded AI Assistant with Tools, Permissions, and Context Limits
A practical method for bounding AI assistants with capability-specific context, tool permissions, approvals, refusals, evidence, and safe release tests.
Redesigning Roles by Tasks When Introducing AI Assistance
Practical framework for mapping tasks, testing AI assistance, tracking hidden effort, and redesigning roles only after workload evidence is stable enough.
Version Prompts, Models, and Workflow Logic as One AI Release
Bind prompts, models, tools, policies, and workflow logic into one testable AI release, then promote and roll back the complete configuration safely.
Create an AI Inventory and Risk-Tiering Method Teams Can Maintain
Build a maintainable AI inventory, rate inherent exposure across four clear dimensions, and route every use to proportionate review as conditions change.
No articles found matching your criteria.
Explore by Category
Ten topics covering the full life of an AI program, from first use case to retirement.
AI Strategy
Connect business needs, capability choices, sequencing, economics, governance, and learning.
AI StrategyAI Use-Case Discovery
Find decision, content, knowledge, prediction, and workflow opportunities grounded in real work.
AI Use-Case DiscoveryWorkflow Automation
Redesign tasks, rules, handoffs, exceptions, approvals, and evidence before automating them.
Workflow AutomationGenerative AI For Work
Apply language and media systems to drafting, retrieval, service, analysis, and assistance responsibly.
Generative AI For WorkIntelligent Document Processing
Extract, classify, validate, route, and review information from business documents.
Intelligent Document ProcessingConversational AI And Agents
Design bounded assistants and agents with tools, context, permissions, evaluation, and escalation.
Conversational AI And AgentsAI Evaluation
Test usefulness, accuracy, robustness, safety, bias, latency, and cost against real scenarios.
AI EvaluationResponsible AI Governance
Establish ownership, inventory, risk tiers, controls, transparency, review, and incident paths.
Responsible AI GovernanceAI Adoption And Work Redesign
Prepare roles, skills, workflows, incentives, managers, and feedback for responsible use.
AI Adoption And Work RedesignAI Operations And Monitoring
Manage versions, prompts, data, access, performance, drift, failures, spend, and retirement.
AI Operations And Monitoring