The Industries With the Thinnest Margins Are AI's Biggest Winners
- AI transformation consultancy Varick Agents argues that beyond software companies, traditional industries with chronically single-digit margins — manufacturing, logistics, warehousing, staffing agencies, field service — have the biggest room for profit gains from the AI shift.
- These companies typically run margins around 3%. The author's math: cutting operating costs by less than one percentage point can lift profit by more than 25%.
- The author's math: at labor-intensive companies, labor costs run about 25% of revenue, and roughly a quarter of that (about 6% of revenue) goes to coordination work itself — scheduling, approvals, exception handling. Cut that coordination burden by 10%, and profit rises by about 20%.
- The author lays out a three-step fix: find the hidden coordination costs, remove any dependence on employees actively adopting new tools, and embed AI directly into the company's existing systems (NetSuite, email, PDFs, spreadsheets) as the operating substrate.
- The piece cites a logistics company case: beyond the drivers, coordination costs — dispatch, route changes, customer updates, claims, invoicing, back-office reconciliation — add up to nearly 10% of revenue. The piece closes by claiming its manufacturing and logistics clients have already achieved eight-figure (USD) profit gains.
Which Companies Will Profit Most From AI?
The companies with the most room to gain from AI probably don't have the most engineers or the biggest software budgets. They're manufacturers, freight carriers, distributors, staffing agencies, field service companies — thin-margin for decades, and nobody would ever call them AI companies.
That's the claim from a long-form post on X by AI transformation consultancy Varick Agents — whose clients are exactly this kind of company.
The thinner the margin, the bigger the leverage. A company at a 3% margin can boost profit by more than 25% just by cutting costs less than one percentage point; the same move at a 30%-margin software company barely moves the needle.
Same 1% Cost Cut, Wildly Different Outcomes
AI creates value three ways: grow revenue, cut cost, reduce risk. Most of the market's attention sits on the revenue side — better products, faster sales, more capable employees. But for companies that already run thin margins, cost is the longest lever.
Why These Industries Have Stayed Poor for Decades
There's a structural reason low-margin companies have been stuck here for decades. Most compete in commoditized markets: the product is highly interchangeable, and price is set by the market, not by any single company. Since they can't move price, cost is the only lever they can actually pull.
And a large chunk of that cost is labor. Beyond the frontline work itself, there's the overhead of coordinating it: scheduling, dispatch, approvals, exception handling — countless administrative processes that grind away at profit round after round. This has long been treated as a fixed cost that can't be cut, which is exactly where AI has the best shot at making a dent.
The Work Behind the Work: What Is Coordination Cost
Beyond the actual work employees do, a company also has to maintain an entire layer of people to keep that work flowing smoothly to the right department: managers, supervisors, analysts, finance, operations, back office. This management overhead that keeps work flowing is coordination cost. It's long been treated as a fixed cost that can't be cut — and it's exactly the biggest cost category AI can now attack.
It's like a construction site: the wages for the bricklayers actually laying bricks are easy to tally, but the site also needs people to schedule the timeline, approve change orders, coordinate material deliveries, and handle disputes. Their wages are a cost too — and one usually treated as a given, a fixed expense that can't be cut.
Take a logistics company the author recently worked with. The visible labor cost is the drivers — but the company is also paying for an entire coordination apparatus built around them.
After working through several low-margin company transformations, the author says this isn't an isolated case. Logistics, manufacturing, facilities management, field service, staffing agencies, medical clinics — any industry with commoditized services, limited pricing power, and delivery that depends on heavy human coordination follows the same pattern: prices won't move, and margins stay thin, simply because it takes a whole layer of coordination staff to reliably deliver what is, at bottom, a fairly standardized service.
Cut Coordination Cost 10%, How Much Does Profit Rise?
Translate this lever into dollars, and walking through one concrete calculation makes it clear.
The savings are only 0.6% of revenue (smaller than the rough "less than 1%" figure mentioned earlier, since this only touches the coordination-cost slice), which sounds negligible. But applied to a 3% margin, it lifts profit from 3% to about 3.6% — a roughly 20% profit increase that rewrites the entire earnings curve. Cut coordination cost by the same 10%, and the thinner the margin, the more profit gets unlocked.
Why These Companies Can't Learn to Use New Tools
When companies buy AI, they're usually betting on one assumption: that employees will proactively open a new tool, use it correctly, and gradually turn that usage into value on the P&L. That assumption doesn't even reliably hold inside tech companies — it's even harder for manufacturing and logistics workers who aren't used to adopting new software.
Most enterprise AI products still depend on this kind of behavior change: get employees to open a new interface, remember when to use it, judge which tasks it applies to, then translate the results back into the process they were already running. The result is that AI becomes yet another place where work has to happen — while what employees actually want is for the work to just get done. So the real question becomes: how do you capture AI's profit expansion without depending on employees to actively adopt it?
Sink AI Into the Company's Operating Substrate
The author breaks the fix into three steps. The first two have already been set up above; the third is where it really unfolds.
Like water and electricity: infrastructure works in the background without you having to turn it on; ordinary software is a tool you have to actively open and remember to use.
Gives employees a new interface, expects them to remember to open it, judge when to use it, then manually move the results back into the original process. One more place where work has to happen.
Directly changes the operating layer under employees' feet: AI handles extraction, matching, flagging, and approval prep in the background of existing systems, and employees only get pulled in when judgment is needed. The value doesn't depend on anyone remembering to use it every day.
Take the most common case, accounts payable. If the process already runs across NetSuite, email, PDFs, and spreadsheets, AI runs across those same surfaces, straight through the chain.
Software asks employees to adapt to a tool; infrastructure changes the operating layer beneath them. Process owners can still pause it anytime, change the rules, approve exceptions, or pull humans back in, and employees still know what's happening. The only thing that changes: value no longer depends on anyone remembering to use AI every day.
Movers Get to Bank the Windfall
Efficiency gains will eventually spread across a commoditized market and get competed back into price, forcing everyone back into a price war. But companies that move first get to cash this cost advantage in as real profit before it's erased — resetting their cost position ahead of the pack.
The piece closes with Varick Agents citing its own track record: manufacturing and logistics clients that worked with them have already achieved eight-figure (USD) profit gains, and companies wanting similar results can find them at varickagents.com.
Varick Agents is a consultancy that builds and deploys AI agent systems for large enterprises; the team describes itself as engineers from a range of tech companies. It doesn't do point automations like "auto-reply to an email" — instead it takes over the whole process from intake to execution to reporting, in four steps:
Margins are thin because operations are heavy; operations are heavy because labor needs to be coordinated. AI is the first technology that can cut away a large chunk of that coordination work without forcing an entire team to change how it works.Varick Agents, original post
AI's Biggest Winners: From Tech Companies → Decades-Thin-Margin Grind Industries
AI transformation firm Varick argues: manufacturing, logistics, and staffing — industries with single-digit margins — can multiply profit just by cutting an invisible layer of "coordination cost." One page, with a chart.
↓ Read it in one page · includes an animated chart
First, know who these companies are: manufacturing, logistics, warehousing, staffing agencies, field service (think on-site repairs, dispatching security and cleaning staff). They do the heaviest, most hand-coordination-dependent work in their line of business, yet their margins have stayed thin for decades.
✘ But can't raise prices, and can't cut costs either
Price is set by the market, not the company (commodity competition — nobody can raise it); and the "coordination overhead" layer of cost has been treated as an uncuttable fixed expense for decades — that's the real weak point
Varick's argument in one line: for thin-margin companies, AI's job isn't to grow revenue — it's to cut cost. Because the thinner the margin, the more profit every dollar saved unlocks.
Using AI for efficiency moves profit from 30% to about 30.75% — the company's trajectory barely changes.
The same sub-1% cut in operating cost jumps profit from 3% to about 3.75% — a rise of more than a quarter.
And the biggest chunk of that savable cost hides in something long treated as "uncuttable": coordination cost.
What actually eats into these industries' profit isn't frontline workers — it's the management overhead that keeps work flowing: scheduling, dispatch, approvals, claims, reconciliation. The term for it is "coordination cost."
A company with $100M in revenue and a 3% margin makes $3M in annual profit. If AI cuts coordination cost by 10%, that saves about $600K, all of which flows straight to profit — $3M becomes $3.6M, a 20% increase. The thinner the margin, the more the same cut delivers.
thin for decades
Profit 30% → 30.75%
- × Dispatch, route changes
- × Customer updates, claims
- × Invoicing, back-office reconciliation
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