If you’ve been online at all lately, you’ve probably seen Matt Shumer’s viral essay, “Something Big Is Happening.” Shumer argues we’re in an “early COVID” moment for AI — where the disruption is already underway, and most people outside tech won’t realize the scale until it’s too late. The post spread fast, and the reaction wave did too: founders, investors, researchers, and journalists debating whether this is sober warning… or weaponized hype.
But here’s the part business leaders can’t afford to miss: regardless of whether you agree with Shumer’s timeline, the market is shifting right now. The biggest near-term risk isn’t “AGI arrives tomorrow.” It’s that companies adopt AI in a rushed, unmanaged way — leaking sensitive data, automating the wrong processes, making bad decisions on flawed outputs, and getting blindsided by security and compliance fallout.
Below is a clear, executive-level breakdown of (1) the core advantages Shumer and supporters highlight, (2) the disadvantages and risks critics are emphasizing, and (3) exactly what you should do this quarter to get ahead — with security built in.
PART 1: WHAT MATT SHUMER (AND SUPPORTERS) SAY IS CHANGING — THE ADVANTAGES
1. AI is moving from “assistant” to “work producer” Shumer’s central claim is that the latest models feel less like autocomplete and more like competent junior-to-mid level execution — planning steps, making decisions, and completing substantial tasks end-to-end. Supporters say this is already showing up in real workflows, especially in knowledge work: drafting, analysis, research synthesis, sales enablement, customer support, and software-related tasks.
Leadership takeaway:
If your competitors are using AI to compress cycle times (proposal writing, quoting, reporting, ticket resolution, documentation), your “speed of execution” gap can widen quickly.
2. “Those who use AI will outperform those who don’t” (a very practical advantage) Even critics who push back on doomer timelines often agree with the productivity reality: teams that standardize AI workflows can output more per employee. In competitive markets, that productivity becomes pricing power, faster service, and better customer experience — if implemented correctly.
Leadership takeaway:
You don’t need to believe in near-term AGI to benefit from AI. You need disciplined adoption.
3. The “AI building AI” narrative is accelerating urgency (right or wrong) One reason Shumer’s essay went viral is the fear that AI progress isn’t linear — that AI tools increasingly help build better tools. Whether or not you buy the strongest version of that claim, the perception alone is driving boardroom urgency, budget shifts, and rapid experimentation across industries.
Leadership takeaway:
Perception changes markets. Hiring, tooling, customer expectations, and competitor behavior will move even if the most extreme predictions don’t materialize.
PART 2: WHAT CRITICS SAY SHUMER (AND AI HYPE) GETS WRONG — THE DISADVANTAGES AND RISKS
1. Reliability: hallucinations, confident errors, and “looks right” outputs A major critique: LLMs still produce confident mistakes, and businesses don’t get paid for “pretty close.” That matters most where accuracy, compliance, and liability are real: finance, legal, healthcare, HR, security, and regulated operations.
Leader’s translation:
If your team starts trusting AI outputs without verification, you can silently bake errors into contracts, financials, reporting, and customer communications.
2. Executive overconfidence becomes the biggest near-term risk One of the sharpest points raised by Shumer’s critics is that leaders may overestimate what AI can do today, rush automation, degrade service quality, and create reputational damage — all while thinking they’re “innovating.”
Leader’s translation:
The danger isn’t just AI replacing roles. It’s leadership making high-stakes decisions based on inflated assumptions.
3. Security and privacy: the “shadow AI” explosion When AI hits the mainstream inside organizations, people use it whether you approve it or not. That drives:
· employees pasting sensitive data into public tools
· unmanaged browser extensions and plugins
· “AI agents” connected to email, files, and ticketing systems without proper controls
· vendors embedding AI features that quietly change your data exposure
Leader’s translation:
If you don’t govern AI usage, you won’t even know where your data went until it’s too late.
4. Brand and fraud risk: deepfakes + AI-driven social engineering As AI usage spikes, attackers adapt. The same tools that make employees faster also make criminals faster — especially in phishing, invoice fraud, voice spoofing, and executive impersonation.
Leader’s translation:
Your cybersecurity posture must evolve at the same speed as your AI adoption.
The debate around Shumer’s essay may continue, but one thing is no longer up for debate: AI is already reshaping how organizations operate, compete, and protect themselves. The winners in this shift won’t be the ones who panic, nor the ones who chase hype — they’ll be the leaders who move with clarity, discipline, and guardrails.
The next wave of AI adoption will reward companies that pair ambition with governance, experimentation with verification, and speed with security. Those who don’t will find themselves fighting self-inflicted fires: data exposure, flawed outputs, compliance surprises, and customer trust issues that could have been prevented.
Now is the moment to steer, not spectate. Build policies, set boundaries, train teams, and choose tools intentionally. If the disruption truly is accelerating — whether at the pace Shumer predicts or something more modest — the organizations that thrive will be the ones that treat AI as a strategic capability, not a chaotic free-for-all.
In short: adopt AI boldly, but not blindly. Your competitive advantage depends on getting that balance right.