Insights

Where AI becomes revenue, in practice

Field notes on AI adoption, the pilot-to-production gap, and the revenue discipline behind both, written by the executives who lead our engagements.

An operating team reviewing an automated finance dashboard on a boardroom screen Featured · Agentic AI in the portfolio

Agentic AI is already doing four jobs in your portfolio

83% of operating partners report at least one agentic AI use case deployed or piloting. Most are scaling it with no playbook.

Matthew Firth · July 16, 2026
An operating partner arranging one-page portfolio scorecards on a boardroom table Private Equity

The operating team's playbook for portfolio AI readiness

Operating teams are getting leaner while AI demands get louder. A standardized, per-portco readiness module is how sponsors keep pace without adding headcount.

Kenneth Lim · July 15, 2026 Hands annotating a printed KPI dashboard beside a laptop Revenue

Define success before you build: the metrics-first rule

AI projects with quantified success metrics set up front succeed about 54% of the time. Without them, about 12%. One discipline, four times the odds.

Kenneth Lim · July 14, 2026 A single lit desk in an open-plan office after hours Governance

Shadow AI is already inside your company

Two-thirds of executives believe unapproved AI tools have already leaked company data. A ban won't fix it. A policy that channels the demand will.

Matthew Firth · July 14, 2026 An executive reviewing printed pilot reports alone in a meeting room Revenue

Why 95% of AI pilots fail, and what the other 5% do differently

MIT found that most enterprise AI pilots produce no measurable P&L impact. The gap between the pilots that stall and the ones that scale is organizational, and it is closeable.

Matthew Firth · July 13, 2026

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