Stop Automating Bad Processes: An AI Workflow Triage Method
Use this step-by-step method to expose broken handoffs, unnecessary approvals, missing data, and policy conflicts before adding AI to operational workflows.
LB
Tag: Strategy
The Unstructured Data Trap Derailing Enterprise AI Programs
Scanned PDFs, stale wikis, duplicate files, and missing permissions quietly sabotage AI quality; this playbook shows how to prioritize the fixes that matter.
DM
Should Your AI Stack Use One Model or a Portfolio of Specialists?
Compare the operational simplicity of a single provider with the resilience, cost control, and task fit of a multi-model architecture.
LB
The Case Against Fully Autonomous AI in High-Stakes Operations
A risk-based analysis shows where autonomy creates unacceptable exposure—and how bounded actions, verification, and escalation preserve useful automation.
AO
The AI Skills Gap Is Really a Workflow Design Gap
Many adoption problems blamed on weak prompting actually stem from unclear decisions, missing feedback loops, and poorly designed collaboration between people and AI.
AO
The AI Value Map: Connecting Model Capabilities to Business Outcomes
A practical framework helps leaders trace model capabilities through workflow changes, adoption signals, and financial outcomes before approving another AI investment.
DM
The AI Change Management Playbook for Teams Facing Automation Anxiety
A people-first playbook shows leaders how to communicate role changes, involve employees in workflow redesign, build trust, and measure adoption without coercion.
DM
AI Chips Beyond GPUs: What the New Hardware Race Means for Buyers
As custom accelerators challenge GPU dominance, enterprise buyers must weigh workload fit, software support, availability, energy use, and switching costs before committing.
LB
Why Your AI Roadmap Needs Decommissioning Plans From Day One
Models, vendors, and workflows age quickly; defining retirement triggers, migration paths, data disposal, and user communication early prevents obsolete AI from lingering.
DM
The AI Pilot Graveyard: Why Promising Experiments Never Reach Production
A forensic look at the technical, organizational, and financial gaps that strand successful AI pilots before they become dependable production systems.
AO
Fine-Tuning vs Prompting vs RAG: A Decision Framework for AI Teams
Compare cost, control, maintenance, and quality across three common adaptation methods, with a practical framework for choosing the right approach by use case.
DM
The AI Build-or-Buy Matrix: Decide What Deserves Custom Engineering
A practical matrix helps leaders weigh differentiation, data sensitivity, integration burden, talent, and switching costs before committing to an AI product path.
DM