We’re not just experiencing another technology wave—we’re in the early innings of a complete economic refactor. And it’s not because of the algorithms. It’s because of the speed.
AI isn’t creeping in the door like the internet or mobile did. It’s showing up everywhere at once—automating, augmenting, accelerating, and in some cases, outright eliminating tasks across every function. This isn’t just disruption. It’s refactoring: a forced rebuilding of how companies work, grow, and compete.
There’s no opt-out clause. You’re either adapting your org from the inside out—or you’re already behind.
Let’s make one thing clear. This isn’t disruption in the classic sense. Disruption, as defined by Christensen, happens slowly. It starts at the low end of the market, works its way up, and by the time it gets to you, you’ve had a decade to plan for it.
AI isn’t playing that game.
This is refactoring: a full-system rewrite while the code is still running.
We’re not removing entire departments (yet), but we are slicing away 30–50% of the day-to-day tasks that used to require people. And for companies that are paying attention, it’s creating leverage—fast.
That leverage isn't being driven by the AI itself. It’s being driven by the urgency and clarity of leadership to make the right bets early.
The biggest risk to most companies right now isn’t AI. It’s how fast AI is moving—and how slowly they’re responding.
Let’s zoom out. In the past, companies had time to adapt to disruption. Print gave way to digital over 15 years. Television took decades to evolve. Even mobile apps had a multiyear adoption curve.
AI isn’t following that playbook.
Between 2022 and 2024, we went from “this model writes weird poems” to “this model is rewriting entire workflows.”
The curve isn’t linear. It’s vertical.
Most orgs aren’t ready for that kind of change. Their tech stacks, their people, their processes—none of it is built for exponential acceleration. And so what’s happening inside many companies is quiet but existential: talented people are falling behind. Tech-forward competitors are catching up. Efficiency is becoming asymmetrical. And the real cost? Time.
Because every month you delay a real AI strategy is another month your competitors are reducing cost, increasing speed, and compounding advantage.
Let’s talk to the investors for a second. PE and VC partners: this isn’t a “CTO problem.” This isn’t just product-led growth. This is your next multiple.
Every board should have a product roadmap for AI. If you don’t, you’re missing the forest for the trees.
This isn’t just about whether the product uses AI. It’s about whether the company uses AI—to grow faster, operate leaner, and scale smarter.
Here’s what PE and VC boards need to be asking right now:
If the answers are hand-wavy, unclear, or buzzword soup, your Portco is probably behind.
Here’s a simple frame I use:
Companies that embrace AI will scale faster, with fewer people, and achieve higher margin. Those that don’t will spend more, take longer, and bleed talent.
The leverage is too real to ignore. In early-stage SaaS companies I’ve seen, one head of marketing with AI can now do what a 5–10 person team used to handle. In enterprise sales orgs, reps are closing more deals per capita with the help of coaching AI, call summaries, and better targeting models.
This is the beginning of the compression era. If you’re not tracking this at the board level, you’re missing the most important operational KPI of the next decade.
AI isn’t a single player. It’s an overlay across every department. And the refactor is happening function by function.
Here’s what it looks like in practice:
AI is changing everything from lead scoring to follow-ups. The best reps are using GPT-style tools to draft messaging, summarize discovery calls, and get instant answers about products or pricing. Managers are using AI to coach at scale, analyze talk time, and flag risks mid-pipeline.
Old way: Add headcount to drive more pipeline.
New way: Use AI to increase rep productivity by 30–50% without hiring.
It’s no longer a question of whether AI will be part of your creative stack—it already is. Tools now write copy, generate images, A/B test assets, and even simulate audience reactions. Brand marketing has to be more strategic than ever because AI makes execution easy—and sameness inevitable.
Old way: Hire more writers, analysts, editors.
New way: A small team + AI = faster time to campaign, more testing, better results.
From AI-powered scenario planning to daily variance reports, finance is undergoing a quiet revolution. The CFO’s new analyst? It's a machine that doesn’t sleep and doesn’t miss typos.
Old way: Build an FP&A team to handle modeling and reconciliation.
New way: Automate 60–70% of routine analysis and focus people on scenario strategy.
AI triage bots, ticket deflection tools, and sentiment monitors are helping CSMs stay proactive, not reactive. We’ve seen CS headcount freeze, while ARR under management grows.
Old way: Hire more CSMs as ARR grows.
New way: Use AI to flag churn risk, prioritize outreach, and summarize interactions.
Developers using copilots are writing code faster, catching bugs earlier, and maintaining cleaner documentation. The role of engineering is shifting from “builders” to “strategic integrators.” Those who understand business logic and how to orchestrate AI will thrive. The rest will look slow.
Old way: Measure productivity by velocity or lines of code.
New way: Measure outcomes—what did one engineer enable with AI?
Let’s kill the false narrative: AI doesn’t have to mean layoffs.
Yes, we’ll see companies pause hiring. Yes, we’ll see functions shrink or reconfigure. But we’re also going to see entire new capabilities emerge—faster prototyping, faster decision cycles, more personalized customer experiences, and higher-margin operations.
Think of AI like the cloud. Did the cloud reduce the need for on-prem hardware teams? Sure. But it also created entirely new industries, roles, and playbooks that didn’t exist before.
The companies who win with AI will be the ones that:
We’ve already seen it ourselves. At Perform, we’ve increased operational scale by over 30% without hiring additional analysts. We didn’t eliminate the human touch—but we did eliminate the bottlenecks that slow it down. Our best people now spend time on high-leverage work. AI handles the rest.
If you’re not sure what “good” looks like, here’s a snapshot of what leading companies are doing:
They’re not waiting for a vendor to tell them what to do. They’re taking ownership of the change.
That’s not a quote for effect—it’s a strategic imperative.
Boards must look at AI the way they would a product launch:
Because in 12–24 months, your competitors will either be faster, cheaper, or both. And if you’re still running a 2019 playbook with a few generative toys layered on top, you’re toast.
This isn’t about tech maturity. It’s about operating maturity.
It’s about building a company that can adapt—at speed.
Refactors aren’t elegant. They’re messy. They touch every part of the system. But once they’re done, they unlock new capabilities and performance.
AI is forcing that refactor across the economy. And while others hesitate, your opportunity is to lead. Build the roadmap. Appoint the leader. Redesign the org. Empower your people.
The companies that move now will do more with less, attract better talent, and create entirely new advantages.
The rest will try to catch up—if they’re lucky enough to survive the rewrite.
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