A competitor with a smaller headcount is often automatically seen as the cheaper party. That assumption only holds if everything else is equal: the same margins, the same subcontractors, the same quality of execution. In practice that is almost never the case. Fewer people can mean that a company has outsourced work, that it operates at a lower quality level, or that part of the work is now done by AI with a cost structure that is no longer based on fte's. That last case is the one that distorts the comparison most, and it is the case that is growing fastest.
As long as delivery time, response or aftercare depend on staffing levels, personnel size is a reasonable indicator of capacity and thus of costs. The moment a competitor has planning, intake or the initial assessment handled by a system with human oversight of the outcome, that relationship disappears. The competitor may then need fewer people, but not less capacity. It can deliver faster, process more requests or perform more consistently, without this being visible in the payroll. Anyone who then only looks at staff numbers concludes the opposite of the truth.
This shift does not proceed at the same pace everywhere. In one company, intake is already largely automated with an employee only assessing exceptions; in another company, the exact same work is still done entirely by hand, often within the same sector and the same region. The difference rarely lies in the sector as a whole, and more often in what an individual company dares to redesign. That makes the comparison more difficult than a glance at headcount, and it also makes it more valuable: whoever knows which part of a competitor's work has shifted from human labor to a system with oversight also knows why that competitor can be cheaper without this coming at the cost of quality or speed.
This analysis works with public and indirect signals: job postings, job descriptions, turnaround times reported by customers, pricing, and the way a company describes its own process. That produces an estimate of where a competitor has deployed AI and where not, but not certainty. A company that shows nothing externally of internal automation is rated lower on AI deployment in this approach than it actually is. Conversely, a company that heavily emphasizes AI marketing can do so without the underlying execution already being that far along; how you distinguish such claims from each other is described at recognizing AI promises that turn out to be empty. Where figures on competitors are missing or not public, the approach to bridging that gap is described at methods for obtaining competitive information without access to their figures. Every score in the benchmark is therefore traceable to the source on which it is based, so you can judge for yourself whether that source is solid enough to base a decision on.
The comparison has no value when the dimension on which you compare is not the dimension on which customers actually choose. A competitor may have become faster on a point that is irrelevant to your customers, while the dimension that does decide the deal remains unchanged. That is also why a cheaper cost structure at a competitor is not automatically a threat: if speed does not tip the scale in your market, a competitor that has become faster through AI is not necessarily a competitor that wins more deals. Which dimensions do tip the scale, and which of those dimensions lose their distinguishing power once everyone deploys AI on them, is worked out at the dimensions that lose their value when AI use becomes widespread. An outcome that is not tied to such a dimension is a figure without weight.
If competitors in your market are moving toward automated execution at a comparable pace, execution speed becomes a level playing field rather than a distinguishing factor. The question then shifts to what can still be won on once the execution work is equally well organized for everyone; that question is addressed at what companies still compete on once AI takes over the execution work. This is also where new entrants can have a structural advantage: a party that starts without a personnel burden builds its process around automation from the outset, without an existing team and existing systems to adapt. How you recognize such an entrant at an early stage is described at signals that a new party is entering the market without building up staff. And because a lead based on AI deployment is not automatically lasting, it is also relevant how long such an advantage holds up before competitors can do the same, worked out at the durability of a technological lead in your market.
This page is about the comparison between companies, not about decisions within your own workforce; which work in your own organization qualifies for takeover by AI is a different question, one that is answered with a task-oriented work scan, and decisions about the personnel consequences of that remain subject to the legal requirements that apply to them.
Identify for yourself on which two or three dimensions you believe you win from the competitor that concerns you most. A free dimension check shows which of those claims can be substantiated with evidence and which rest on assumption. The full benchmark, with the evidence matrix per dimension, is under construction.
Vraag maar waarop er in uw markt gewonnen wordt. Ik vergelijk liever dan dat ik uitleg.
Answers come from this site’s knowledge base. Not tailored advice, and not a scan of your company.