The Wake-Up Call
Matt Shumer's recent essay, "Something Big Is Happening," has become one of the most widely shared pieces on AI this year — and for good reason. His core message is urgent and honest: AI capabilities are advancing faster than most people realize, and the gap between what AI can do today and what the public thinks it can do is dangerously wide.
He describes walking away from his computer for hours and coming back to find complex software projects completed. He cites a managing partner at a major law firm who spends hours daily with AI tools. He warns that the disruption heading toward every knowledge-work profession isn't a prediction — it's a description of what already happened to his industry.
Shumer's advice to individuals is simple: start using AI now, lean in, experiment every day. We agree. But his essay is written for individuals — and it leaves out the part that matters most for organizations.
How do you harness this wave across an entire enterprise — without drowning in the risks?
The Opportunity
Let's start with the opportunity, because it's enormous.
The acceleration Shumer describes isn't just a threat to jobs. It's the single greatest productivity unlock most organizations will see in their lifetimes. Tasks that took analysts days can be completed in hours. Research that required entire teams can be drafted by one person working with AI. Document review, financial modeling, customer insights, competitive analysis — the speed and depth of work that AI enables is transformative.
The enterprises that lean into this moment have a genuine competitive advantage. Not just in efficiency, but in what becomes possible: exploring strategies that were previously too expensive to model, testing ideas that would have taken quarters to prototype, giving every employee access to capabilities that used to require specialized teams.
But here's the catch. Shumer tells individuals to "just start using AI." Imagine what happens when every employee in a thousand-person organization takes that advice on the same Monday morning — each choosing their own tool, feeding in whatever data they need, with no shared infrastructure and no guardrails.
That's not adoption. That's chaos.
The Widening Gap
Every quarter, the models get more capable. Every quarter, employees find new ways to use them. Every quarter, the volume of sensitive data flowing through ungoverned channels grows.
The governance gap isn't linear. It's compounding at the same rate as the capabilities themselves.
This doesn't mean the answer is to lock things down. Organizations that block AI access entirely don't eliminate usage — they just push it underground into personal accounts, personal devices, and consumer tools with no enterprise controls. The result is even less visibility and more risk.
Build the Sandbox
The most forward-thinking organizations are realizing something important: the answer isn't restriction or chaos. It's creating an environment where teams can experiment boldly — with the newest models, the latest capabilities, real business data — inside a space that's secure, auditable, and governed by default.
Think of it as a sandbox for the entire organization. A place where:
Every team can explore freely. Marketing can test AI-powered content workflows. Legal can experiment with contract analysis. Engineering can prototype with the latest models. Finance can build AI-assisted forecasting. Nobody waits for IT approval to try the next breakthrough — because the sandbox already supports it.
New capabilities arrive fast. When a new model launches — and they're launching constantly — it's available to the organization within the platform, not through a dozen ungoverned consumer tools. Teams stay on the cutting edge without creating new security blind spots every time the landscape shifts.
Experimentation is safe by design. Sensitive data stays within your perimeter. Access policies are enforced automatically. Every interaction is logged — not to slow people down, but to give the organization confidence that rapid experimentation isn't creating hidden liability. The sandbox doesn't restrict what people can build. It ensures that whatever they build, they build it safely.
Knowledge compounds across the organization. When AI usage happens through a shared platform, the organization learns together. Successful workflows get shared. Best practices emerge organically. Instead of a thousand isolated experiments, you get a compounding advantage.
Ride It, Don't Survive It
Shumer's essay frames AI primarily through the lens of disruption and survival. We see it differently. Yes, the pace is breathtaking. Yes, organizations that ignore it will fall behind. But the real story isn't about threat — it's about leverage.
The enterprises that build the right infrastructure now aren't just protecting themselves. They're positioning to move faster, experiment more ambitiously, and compound their AI capabilities in ways that competitors stuck in either lockdown mode or unmanaged chaos simply can't match.
Consider the difference:
Without infrastructure: Every department adopts AI independently. Data flows to a dozen different external tools. Nobody knows what's being used, by whom, or what data has been shared. When something goes wrong — and eventually it will — there's no trail, no containment, no understanding of the blast radius. Meanwhile, good experiments die in silos because there's no way to share what works.
With infrastructure: The entire organization has access to the best available AI capabilities through a single, governed platform. Teams experiment freely — they're encouraged to. But the organization has full visibility. Successful experiments scale. Failed experiments are contained. When regulators ask questions, answers are available instantly. And when the next wave of capabilities arrives, the platform absorbs it — no new security review, no new procurement cycle, no fragmented tooling.
The first organization is treading water. The second one is surfing.
The Window
Shumer talks about a "brief window" where early adopters can gain an advantage. He's right — and the window applies to infrastructure too.
Right now, most enterprises haven't built this. The organizations that stand up governed AI platforms today will have a compounding head start: their teams will be more fluent with AI, their workflows more mature, their data practices more robust. That gap will only widen as the models accelerate.
The rising tide of intelligence is real. The question isn't whether it will reach your organization. It's whether you'll have the infrastructure to ride it — and turn it into your greatest competitive advantage.
Sources
- Matt Shumer — "Something Big Is Happening" (2026)