INSIGHTS

Thinking out loud.

Perspectives on AI strategy, implementation, and leadership. Written for the people making the decisions.

For shorter letters on AI and office life, see Dear Issy.

The Revenue Fire Protection Companies (Like Other Contract Service Providers) Quote But Never Collect

Fire protection companies quote but never collect 20-30% of billable revenue. Here is why deficiency pull-through fails and what fixes the quote-to-cash cycle.

Issy · Aug 29, 2026

LONG READ·STRATEGY· 10 min read

How New York's Accounting Firms Are Evaluating AI

How New York's accounting firms are evaluating AI for assurance and compliance. Most get the sequence wrong. This 90-day framework evaluates AI without pilotitis.

Issy · Aug 12, 2026

LONG READ·STRATEGY· 13 min read

AI Hiring Disclosure in Ontario: What Employment Lawyers Should Tell Their Clients

Ontario's Bill 149 AI hiring disclosure rules create two-front liability. Employment lawyers need a client advisory that goes beyond the ESA compliance floor.

Issy · Aug 1, 2026

LONG READ·IMPLEMENTATION· 6 min read

How a Fire Protection Company Found $300K Inside Its Own Contracts and Books

A workshop became a custom app their inspectors use on site, and a data project across more than a thousand contracts. We found over $300,000 in work that was done and never billed, and services billed with no contract on file.

Issy · Jul 31, 2026

LONG READ·SECURITY· 10 min read

Where Have All the Claws Gone? The Hidden AI Agent Surge Mid-Market CEOs Can't Ignore

Where have all the claws gone? Agentic AI tools like OpenClaw are already inside mid-market networks. Here is the board-level risk framework you need now.

Issy · Jul 27, 2026

LONG READ·STRATEGY· 12 min read

AI Competitive Advantage for Mid-Market Leaders: Why Speed-to-Decision Beats Data Hoarding

AI competitive advantage mid-market firms miss has nothing to do with data volume. Decision velocity is the real moat. Here is the framework to close that gap.

Issy · Jul 19, 2026

Q&A·STRATEGY· 22 min read

Where to Start When You Have a Lot of Data and Want to Be AI-Native

You have a lot of data and want to be AI-native — where do you start, and what setup is cheapest while ROI is still unproven? A reference engagement on a 1.5 TB corpus, with cost models for CEOs and pipeline detail for CTOs.

Issy · Jun 29, 2026

Q&A·STRATEGY· 12 min read

Turning Data into Actionable Insights: The Information Architecture Question Leaders Get Wrong

Turning data into actionable insights fails when leaders skip information architecture. Here is the structural question every mid-market CEO must answer first.

Issy · Jun 27, 2026

Q&A·STRATEGY· 13 min read

Automotive Dealership Data Governance: The Fundamental Rules for Leveraging Customer Data Without Falling Offside

Automotive dealership data governance is the line between competitive edge and liability. Here are the fundamental rules every dealer principal must know.

Issy · Jun 25, 2026