It’s just easier to work with AI agents than humans.
Not better in every way. Not a perfect replacement. Not without real costs and real limits. But easier. And I think that distinction is going to shape the workforce in ways most people aren’t ready for.
It’s not even all about cost savings or productivity. It’s about … easier.
Let Me Be Clear About What “Easier” Means
Our agents have to be trained. Some of them have been rebuilt two or three times before they worked well. They all hit walls—tasks they can’t do, edge cases they fumble, outputs that need human review.
We manage them daily. They’re not set-it-and-forget-it.
And yet.
Compare that to the full human hiring process: sourcing candidates, running interviews, making an offer in a competitive market, negotiating comp, waiting through a notice period, onboarding over 60-90 days, managing performance, dealing with the occasional bad hire, hoping they don’t leave in 18 months. For every role. Repeatedly.
Agents don’t require recruiting fees. They don’t need benefits, PTO, or equity refreshes. They don’t get disengaged. They don’t have bad weeks. They don’t leave for a competitor.
Even accounting for all their real limitations—and there are many—the operational overhead of deploying an AI agent is a fraction of the overhead of hiring a human.
That’s what “easier” means. Not that agents are always better. Just that the process of deploying and maintaining them is dramatically lower friction.
The Honest Comparison Most Leaders Aren’t Ready to Say Aloud
Here’s the framing I keep coming back to:
A truly great human is still better than any AI agent at most complex, judgment-intensive work. Full stop. If you can find and keep exceptional people, do it.
But here’s the thing: most hires aren’t great hires.
Most hires are average. Maybe above-average. They do the job. They’re fine. They’re the solid B-player who executes reliably but doesn’t surprise you.
A good AI agent beats that hire on almost every operational dimension. Not on raw capability—but on consistency, cost, availability, and the total management burden required to get work out of them.
When companies look at their open headcount and ask “what does this person actually do day-to-day?”—and the answer is something structured and repeatable—the math is increasingly pointing toward agents.
This Is Why 2027 Worries Me
I’m not worried about 2026. The transition is still early. Most companies are still figuring out which agents actually work and how to integrate them properly. There’s still significant friction.
But the learning curves are steep in the right direction. What takes months to set up today takes weeks next year and days the year after.
The companies that are running 20+ agents in production now—we’re getting very good at deploying the next one. We know what works. We know what to watch for. The institutional knowledge compounds.
By 2027, I think a meaningful number of companies will have crossed a threshold where the default answer for a new workflow or an open role is not “let’s hire someone.” It’ll be “let’s see if an agent can handle this.”
That shift—from exception to default—is what changes employment in a structural way.
What Shopify, Salesforce, and Others Are Already Saying
This isn’t just SaaStr. Tobi Lütke at Shopify issued a memo last year that essentially made AI a prerequisite for headcount requests—before you ask for a new hire, you have to demonstrate why AI can’t do the job. Shopify has held headcount roughly flat for three years while revenue has grown past $11B ARR.
Marc Benioff cut Salesforce’s support headcount from roughly 9,000 to 5,000. He wasn’t subtle about why.
A Yale CEO survey from late 2025 found that roughly two-thirds of CEOs expected to maintain or reduce headcount over the next 12 months specifically because of AI capabilities.
These aren’t companies in distress making desperate cuts. These are well-capitalized businesses making deliberate operational choices about how they want to scale.
You’re Already Doing The Math
If you’re running a B2B company right now, you’re probably already doing this math whether you admit it or not. When someone leaves your team, you’re asking the question. When you’re looking at a new function, you’re weighing the options.
The honest answer is: for a lot of roles, agents are already good enough—and the trajectory means they’ll be better-than-good-enough for many more roles within 18-24 months.
That doesn’t mean humans become irrelevant. The exceptional people—the ones who think in frameworks, build relationships, make judgment calls under ambiguity, create things that didn’t exist before—those people remain invaluable. If anything, they become more valuable as the baseline gets automated.
But the average hire, for the structured role, doing repeatable work? That’s where I’d be paying close attention if I were building a career right now.
Where This Leaves Us
I don’t think the right response is doom. The right response is honesty.
At SaaStr, we’ve gone from 20+ humans to 3 humans and 20+ agents. Revenue is up 47% year-over-year. The agents handle the repeatable, high-volume work. The humans do what agents genuinely can’t: judgment, relationships, creativity, strategy.
That’s probably the model for a lot of companies by 2027.
The hard part isn’t the technology. The hard part is being honest that the transition is real, it’s already underway, and the companies that pretend otherwise are just deferring a decision they’ll eventually have to make anyway.
The companies moving now are building operational muscle. The ones waiting are going to find the learning curve considerably steeper when they finally have to catch up.
2027 is closer than it looks.
