Editorial
Writing
Research-backed stories and practical guidance on AI adoption, tools, costs, and the work of putting them into production.
How to Use AI for a Quality of Earnings Review That Holds Up in a Deal
A practical system for using AI in M&A quality of earnings: source records, adjustment tests, cash conversion, industry examples, audience-specific outputs, and a worked EBITDA bridge.
Gary Stanton · October 6, 2026
Which AI Certifications Are Worth the Time? A Role-by-Role Guide
A useful AI credential should prove the work a person is trusted to do. This guide maps assessment types to leaders, operators, finance, sales, support, risk, and engineering—and names the badges to skip.
Gary Stanton · October 6, 2026
AI Adoption Analytics: Measure Work, Not Just Logins
Usage dashboards show who opened an AI tool. A useful adoption view also shows which work was accepted, repaired, rejected, or never attempted.
Gary Stanton · October 5, 2026
AI ROI Sensitivity Analysis: Find the Assumption That Breaks the Case
A single return estimate hides the effect of low adoption, review time, and errors. Vary those inputs one at a time before calling released hours a benefit.
Riley Morgan · October 1, 2026
An AI Pilot Scorecard That Can Actually Stop a Rollout
A pilot needs a decision rule before the first demo. This scorecard measures accepted work, errors, full cost, and adoption against the current process.
Dana Whitfield · October 1, 2026
Prioritize Salesforce Deals with Claude: Next Actions and Win Probability
A practical method for ranking movable deal actions, checking Salesforce probability against history, and avoiding made-up win percentages.
September 28, 2026
How to Use AI for Calendar Tasks: Prompts from Simple to Complex
Copy practical prompts for planning, scheduling, and rescheduling. See where AI can act on its own, where a person should approve, and what changes across Google Calendar, Outlook, and Apple Calendar.
September 28, 2026
Quick Tips: Use Markdown Files to Pass Work Between AI Agents, Teammates, and Future You
Write the first Markdown handoff note yourself, then let an AI assistant update it after each completed task. Here is the repeatable pattern and 15 business uses worth trying.
Gary Stanton · September 26, 2026
The Hidden Work Behind AI Pilots: Why Good Experiments Still Stall
MIT Sloan’s field study found that AI pilots need sustained expert testing, review, and repair. Leaders who budget only for software miss the work that makes adoption possible.
Dana Whitfield · September 25, 2026
Microsoft’s Two AI Bills: Why a Copilot Seat Is No Longer the Whole Budget
Microsoft is separating predictable employee access from metered agent work. A useful budget now counts accepted work, credit consumption, and the review that remains.
Pete Callahan · September 25, 2026
AI Coding Models Got Faster. Your Review Queue May Not.
New coding models finish more tasks with fewer steps, while GitHub is changing its default code-review effort. The buying case lives in merged changes, deployment stability, and reviewer load.
Riley Morgan · September 24, 2026
Six Months of Better AI Models: What Actually Changed for Business Teams
The spring-to-fall model releases improved computer use, professional work, and cost per task. The executive question is which workflow can now pass its acceptance test—not which benchmark won.
Dana Whitfield · September 24, 2026
The EU’s AI Transparency Rules Are Live. Here Is the Deployment Check.
Article 50 transparency obligations began applying on August 2. The executive job now is to turn labels and disclosures into release controls across product, marketing, service, and internal automation.
Priya Subramanian · September 21, 2026
Seven Hours Saved, More Work Stuck: AI Moved Science’s Bottleneck
Scientists report saving almost seven hours a week with AI, while validation and physical experimentation accumulate downstream. The executive lesson is to budget the bottleneck, not celebrate the shortcut.
Riley Morgan · September 21, 2026
Copilot is a tenant tax, not a second ChatGPT
Microsoft 365 Copilot is worth the seat if the work already lives in Word, Outlook, and Teams. It is an expensive way to buy another chat tab. Here is the seat math, and when to skip it.
Gary Stanton · September 16, 2026
The Productivity Gap Is Real: What Happens When Your Competitor Adopts AI First
By April 2026, the gap between companies that deployed AI six months ago and those just starting is already permanent. Here's why catching up later doesn't work, and what to do Monday morning.
Dana Whitfield · April 9, 2026
The Three-Layer ROI Framework: Why Most AI Projects Fail Before They're Measured
Companies measuring AI ROI the wrong way kill good projects and overfund bad ones. Here's how operators at scale separate signal from noise.
Dana Whitfield · March 15, 2026
How to Build an AI Business Case Your CFO Can Audit
A defensible AI business case starts with one constrained workflow, a measured baseline, and claims finance can trace. Use this model to price capacity, quality, risk, and the cost of review.
Dana Whitfield · March 3, 2026
The 30-Day AI Workflow: How to Prove Value Before You Scale
Most companies build ambitious AI systems and hope they work. Winners do the opposite: they automate one boring task, measure ruthlessly, and only scale when the signal is unmistakable.
Jules Marchetti · October 12, 2025