Most companies are using AI to do the same things faster. A small group is using it to do completely different things. That gap is not closing. It's growing. Here's what the companies winning with AI are actually doing differently.
TDLR:
The 20% Taking 75% of the Gains 📊
What McKinsey's Manifesto Actually Says 📋
RAMP Built the Playbook 🏗
The Mindset Shift Nobody Talks About 🧠
The Bro's Take 🤔
A PwC study found that 75% of AI's economic gains are being captured by just 20% of companies.
But here's the part that matters. It's not that these companies are better at AI. It's that they're using it differently. They're not thinking about efficiency.
They're thinking about growth. They're two to three times more likely to use AI to identify new opportunities and 2.6 times more likely to say AI helps them reinvent their business model.
Doing the same with less is not the play. Building something new is.
McKinsey dropped a 12-point AI transformation manifesto and most people missed the point of it.
Technology alone doesn't create advantage. Systems do. The companies leading on AI have built coordination layers around it.
They've invested in data as an ongoing operational discipline, not a one-time project. They're training senior business leaders on AI, not just delegating it to IT.
And they've identified the specific economic leverage points in their business where AI creates the biggest impact.
The numbers back it up. AI leaders in McKinsey's study saw a 20% EBITDA uplift, broke even in one to two years, and generated three dollars of incremental EBITDA for every dollar invested.
This is not about productivity. It's about business model transformation.
RAMP noticed that 99% of their employees were using AI daily but most were stuck. Not because the models weren't good enough. Because the setup was too painful.
So they built Glass. Every employee gets a fully configured AI workspace on day one. All integrations connected via SSO. A marketplace of 350-plus reusable skills built by colleagues. Persistent memory. Scheduled automations that run without anyone being at their desk.
The key insight: when one person figures out a better workflow, everyone on their team gets it automatically. One person's breakthrough becomes everyone's baseline.
Their internal AI guide, Sensei, looks at what tools you've connected, what role you're in, and what you've been working on, then surfaces the five skills most relevant to you on day one. No browsing a catalogue of 350 options.
RAMP didn't buy this off the shelf. They built it because internal AI infrastructure is now a competitive moat. You don't hand your moat to a vendor.
Here's what I'm seeing from the inside working with AI every day.
Most organisations think about AI adoption as a spectrum. Some people are power users. Most are casual users. A few are left behind. So they build systems that reflect that assumption, capping what most people can do.
RAMP's approach flips this entirely. Don't limit anyone's upside. Make the complexity invisible while preserving full capability. Assume everyone can become a power user because the AI itself is there to help them get there.
That's the real unlock. AI doesn't just do the work. It teaches you how to use it while you're using it.
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The gap between AI leaders and everyone else isn't about access to models. Everyone has access to the same models.
It's about systems. Coordination layers. Harnesses that make individual AI outputs point in the same direction. Institutional memory that doesn't reset every session. Skill marketplaces that compound across teams.
The companies building this now are creating advantages their competitors can't match by copying a tool. Because the tool is not the advantage. The system around it is.
The question is not whether your company is using AI. It's whether anyone has thought about what happens when all of that individual usage adds up to nothing.
And that's it for today! Thanks for reading ♥️
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