Too many AI ideas, no operating model
Pilots multiply across teams, but there is no shared model for prioritizing, sequencing, or retiring them.
AI Strategy & Operations
AI Strategy & Operations Consulting
I help organizations turn AI from scattered experimentation into governed, measurable operating advantage.
Why AI adoption stalls
Organizations are experimenting with AI, but adoption stalls because workflows, governance, measurement, and trust were never designed.
Manual workflows with unclear automation paths
The work that should be automated first is not obvious, so automation gets applied unevenly, or not at all.
Agent pilots without governance
Agents touch real workflows before anyone has defined review gates, escalation paths, or failure modes.
Data access and trust concerns
Teams hesitate to connect AI to real data because ownership, access boundaries, and risk exposure are undefined.
No clear ROI measurement
Without a measurement layer, it is impossible to tell which AI investments are actually paying off.
Teams unsure where AI should actually fit
Enthusiasm outpaces judgment. Everyone has an opinion on where AI belongs, but no one owns the decision.
How we can work together
Engagements
01
AI Opportunity Diagnostic
A short assessment of workflows, data readiness, automation opportunities, risks, and high-value use cases.
02
Workflow Redesign Sprint
Map a specific process, remove operational friction, and design an AI-enabled future-state workflow.
03
Agent Build Pilot
Build or prototype a narrow AI agent for a real workflow, with human-in-the-loop controls.
04
AI Governance & Risk Model
Define usage rules, review gates, escalation paths, data boundaries, and measurement controls.
05
AI Operating System Retainer
Ongoing support to prioritize AI opportunities, manage pilots, document operating standards, and scale what works.
How I work
Diagnose. Design. Build. Govern. Scale.
01
Diagnose
Assess workflows, data readiness, automation opportunities, and risk exposure.
02
Design
Map the target workflow and the operating model that will carry it.
03
Build
Prototype the narrow agent or automation, with human-in-the-loop controls.
04
Govern
Define usage rules, review gates, escalation paths, and data boundaries.
05
Scale
Prioritize what is next, document operating standards, and expand what works.
Related work
Proof across research, product, and operations.
Source-grounded strategic analysis on AI, markets, and operating systems, published under this practice.
A logistics and dispatch platform demonstrating workflow automation and operating-system thinking end to end.
An AI-assisted churn risk operations system for B2B SaaS teams, validated end-to-end from risk scoring to intervention playbooks and escalation governance.
Amazon
A 2025–2030 sourcing roadmap and executive decision support for a nine-figure mandate.
City of Edmonton
Workflow automation, analytics governance, and measurable operational savings across public-sector teams.
The research layer
Strategic Digest is the public research behind this practice.
Every engagement draws on the same source-grounded analysis published in Strategic Digest: how AI is reshaping markets, operating models, and governance. Reading it is a good way to see how this practice thinks before working together.
Read Strategic Digest →Start with a focused diagnostic.
The fastest way to find out if this is a fit is a short AI Opportunity Diagnostic: a focused look at your workflows, data readiness, and highest-value automation opportunities.
Start with a focused AI diagnostic →Use the contact page to schedule an intro call or send a short note about the workflow you want to improve.