Published thinking on AI adoption judgment, post-acquisition restoration, and enterprise transformation. Articles below are authored in Japanese with English summaries provided. The LinkedIn EN PE series carries English-original content for cross-border PE and deal-team readers.
The LinkedIn EN PE series is the primary surface for English-original CAIO content. Published biweekly, focused on post-acquisition operating reality, control-loop restoration, and AI in PE-portfolio operating contexts. Authored from the operator-inside vantage.
Frank Wang on LinkedIn →In a Day 60 post-acquisition review, an item that had stayed green turned out to have been slipping since Day 15 — color compresses judgment but leaves no trace of it. This article examines Loop 1, the first of four operating control loops to collapse — timeline visibility — and frames the three signals that need to sit behind the color, from the operator-inside perspective.
Read article →In the first 90 days after acquisition, what the portfolio company needs is not a new strategy but the reloading of operating loops — making weekly executive judgment explainable. Timeline visibility, stakeholder commitments, cost discipline, and decision auditability, from the operator-inside perspective.
Read article →In AI adoption discussions at mid-cap and small-cap firms, the themes raised first are often the ones that should not be tackled at all. Not by ROI, but by "structures that delay the decision," here is how to identify the three candidates to cut first.
Read article →Most AI adoption conversations start with tool selection. They should start with which business processes are ready for AI to compound — and which are not, often despite executive enthusiasm. This article frames the readiness question and walks through the patterns that distinguish processes ready for AI from processes that need DX foundation work first.
Read article →For executives who have decided AI matters but not where to begin, three structured steps for defining the first move — before committing to a tool, vendor, or budget. The starting point is not "what AI tool is best" but "what decision is the company actually trying to make."
Read article →Hiring a PM, product manager, or program manager for AI work fails when executives have not answered four prior questions about the operating model: where the role sits, what decision authority it carries, how the AI capability connects to existing decision rights, and how performance will be evaluated. This article walks through the four.
Read article →First-budget sizing for AI is rarely a benchmarking question. It is a question of decision-axis maturity — how confidently the company can identify the first theme, the first scope, and the first success criterion. This article unpacks how to size the first investment without anchoring on industry averages.
Read article →CAIO publishes articles in Japanese as the original. The articles listed above are available in English translation. For PE-portfolio and cross-border readers, the LinkedIn EN PE series is the primary surface for English-original content.
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