Briefing #20. {{current_date_mdy_dashed}}
Welcome to The Boardroom Brief — the intelligence briefing for leaders who run the room.
Every week (for paid subscribers) or every month (for free subscribers), I cut through the noise: AI tools worth your time, strategy moves worth stealing, and the numbers you actually need to know. No hype. No firehose of daily headlines. No tutorials written for developers. Just signal.
Let's get into it.
🧠 The Big Idea
The AI labs are coming for the consultants — and it changes everything about how you buy AI strategy.
Two things happened this week that most executives haven't fully processed yet.
OpenAI launched "The Deployment Company" — a $4 billion joint venture backed by TPG, Bain Capital, SoftBank, and Brookfield — to embed engineers and advisors directly inside Fortune 500 companies. Not selling models. Not licensing APIs. Actually doing the implementation work. Same day, Anthropic announced a $1.5 billion services JV of their own, backed by Blackstone, Goldman Sachs, and Hellman & Friedman, specifically for Claude deployments at enterprise scale.
In a single week, the two most powerful AI labs in the world both decided the same thing: the model business isn't enough. The implementation business is where the real money is.
Think about what that means for you.
For the past three years, the standard playbook was: hire a Big Four firm to run your AI strategy, buy a model license from OpenAI or Anthropic, and stitch them together. That playbook just got complicated. The people who build the model now also want to sell you the implementation. They know the technology better than anyone. They have the engineers. And they've just raised $5.5 billion combined to compete directly on your organization's doorstep.
The reason both labs moved at once isn't coincidence — it's the same diagnosis. Enterprises are hitting what insiders call the "last mile" problem. The models work. The integration doesn't. Change management, legacy data, compliance with frameworks like the EU AI Act, and the sheer organizational friction of deploying AI at scale — none of that gets solved by a better model. It gets solved by people doing the hard work inside the organization.
So what should you actually do with this?
Three things worth considering before your next AI vendor conversation:
1. Your AI strategy conversation is about to get more crowded.
Traditional consulting firms (McKinsey, Accenture, Deloitte) built their AI practices on being the neutral advisor between you and the labs. That neutrality is now complicated. The labs are no longer just vendors — they're competitors to your advisors. Understand whose interests are aligned with yours before the next strategy engagement starts.
2. The "last mile" problem is real — and it's yours to solve.
Both OpenAI and Anthropic are betting billions that enterprises can't implement AI without help. That's not a knock on your organization — it's a structural reality. If your AI initiatives are stalling, it's almost certainly not the model. It's the change management, data infrastructure, and organizational ownership. Those are fixable. They just require different resources than the pilot required.
3. This validates implementation speed as a competitive moat.
The labs are raising billions to help slow movers catch up. The executives who move now — before the ecosystem commoditizes implementation — will have compounding advantages by the time their competitors finally get to production. The window for early-mover advantage is not permanent.
🛠 Tool of the Week
Fireflies.ai — The AI that attends meetings so you don't have to (entirely)
Relevant this week given the topic: the #1 reason executives cite for stalled AI adoption is bandwidth. No time to evaluate. No time to implement. No time to manage the change.
Fireflies addresses the lowest-hanging fruit: your meetings. It joins your calls (Zoom, Teams, Meet), transcribes in real time, extracts action items, and delivers a structured summary to your inbox before the meeting ends. It integrates with your CRM, Slack, Notion, and project management tools.
The use case that converts skeptics: searching across six months of meeting transcripts in ten seconds to find exactly what was decided, who said it, and when. No more "I thought we agreed on this."
For executives navigating the new AI implementation landscape this issue covers — Fireflies gives you back 3-5 hours a week to actually run the initiatives you keep talking about launching.
Plans from $10/month. Most executives land on Pro ($19/month) — unlimited transcription, advanced search, CRM sync.
📊 By the Numbers
$4B — Capital raised by OpenAI's "The Deployment Company" JV, backed by TPG, Bain Capital, SoftBank, and Brookfield. Valuation at launch: $10 billion. (May 2026)
$1.5B — Anthropic's parallel services JV with Blackstone, Goldman Sachs, and Hellman & Friedman, announced the same week. Total AI consulting bets from both labs combined: $5.5B+. (May 2026)
360,000 — Applications Goldman Sachs received for its internship program last year. Seth Godin's term for this: "Red Queen hiring" — organizations running faster and faster just to stay in the same place, spending $14,000+ per executive hire on processes that don't demonstrably improve outcomes. (Seth Godin, May 2026)
74% — Share of AI's total economic value captured by the top 20% of adopting companies. The bottom 80% split the rest — with more than half reporting zero measurable financial return. (PwC AI Performance Study, 2026)
🎯 The Move
Audit who's advising you on AI — and whose interests they actually represent.
This week's news creates a simple but important question for your next strategy session:
Who is advising your organization on AI implementation — and are they still neutral?
Ask your current AI strategy partners these three questions:
Do you have financial relationships with OpenAI, Anthropic, or their affiliated ventures? (Several major consultancies do now — it's public.)
What is your recommended path from our current AI pilots to production — with a timeline and ownership model?
If we don't move to production in the next 90 days, what specifically does that cost us?
You don't need to be suspicious of your advisors. But you do need to be informed. The AI landscape just got significantly more complex — and the people who win in this environment are the ones who ask the right questions early.
📌 Worth Reading
1. OpenAI's Deployment Company — Full Breakdown
The clearest summary of what "The Deployment Company" actually does, who backed it, and why the timing matters. If you're briefing your board on AI strategy this quarter, this context is essential. (~5 min read)
2. Seth Godin: The Shared Tragedy of Red Queen Hiring
Published this week. Godin argues that modern hiring has become a collective action problem — organizations spending more and more on processes that don't improve outcomes, simply because everyone else is. The $14,000-per-executive-hire stat, 360,000 Goldman applications, and the quiet question: are the people you're hiring with all this process actually better than the ones you found ten years ago with less? Applies directly to AI talent acquisition. (~4 min read)
3. The Emerging Agentic Enterprise — MIT Sloan + BCG
MIT Sloan and BCG's global executive survey on AI strategy — specifically why organizations stall between pilot and production, and what the ones who don't stall do differently. This week's big news makes it more relevant, not less: the labs validating the "last mile" problem are the same organizations this research was tracking. (~10 min read)
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