I just put the final version of 100x on Amazon. It is a straight executive brief on AI transformation: how to connect your people, your data, and your AI into something that actually compounds.

I went through every line with my editor. 150+ passages updated, every stat traced to a real source. One change stopped me: "AI transformation" now replaces the old terminology in 22 places. That is the language your board is already using.

I also added a Philips North America case study: enterprise AI transformation inside a global manufacturer, with a testimonial from their leadership team.

Same framework, sharper. Comes with a free AI coach, templates, and 100+ pages of playbooks.

Reading time: 3 min. 

PwC's 2026 Global AI Jobs Barometer analyzed one billion job ads across 27 countries. The productivity split is not closing. It's compounding.

The most AI-exposed companies average 33.5% productivity growth. The top 20% hit 163%. Every organization in the study has AI on contract. Integration depth is the divide.

Headcount confirms it. AI-exposed companies grew 52% versus 36% for least-exposed firms. Workers with AI skills command a 62% wage premium.

How human-centric AI delivers business results

Your weekly briefing on tools that create competitive leverage

Launched at the Databricks Data + AI Summit, Agent/works governs AI agents across any cloud with pre-execution compliance checks, agent-specific permissions, and unified spend controls.

Best for: CIOs managing AI agents across multi-cloud stacks who need portable governance and cost controls.

Work IQ gives AI agents access to email, calendar, meetings, files, and org graph across Microsoft 365 at usage-based cost, no Copilot license required.

Best for: Enterprise CIOs on Microsoft-first infrastructure who need agents grounded in org context.

Enterprise AI inference carries a cost and latency penalty that most organizations never solve. Lin Qiao, co-founder and CEO of Fireworks AI, built large-scale AI systems at Meta AI Research before founding an inference platform that lets enterprises deploy any model at production speed. Fireworks recently reached a $15 billion valuation, with clients across finance, healthcare, and software. The model: separate infrastructure decisions from model selection, so teams optimize around fit rather than reputation.

Traditional AI transformation asks your people to learn the language of technology. The next generation makes the technology learn theirs. That inversion is the reason 70% of enterprise AI programs fail.

Philips North America brought Future Works in to operationalize AI across the functions that move their P&L. A parallel system, built to run alongside live operations, proved itself before it displaced anything. They found a way to reach millions in value and execute immediately. Every cycle since has funded the next.

Before any system goes live, two things need to be true: the daily workflow of the actual operator improves, not just the reporting dashboard. And the CFO sees the same value signal the operator does.

Get the full framework in 100x.

One book, handpicked from my conversations with friends, industry leaders, and tech innovators:

In Atomic Habits, James Clear argues that outcomes reflect the systems behind them, not the goals in front of them. Leaders generating outsized AI productivity are not better resourced. They have built integration habits that compound daily across the operation. Competitors keep raising targets without changing the underlying system.

Perfect for: executives who keep setting ambitious AI targets but see the same results quarter after quarter.

Every metric except the one your board actually wants.

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