Which of our current cost structures assume a world without AI — and how do they change in a world with it?

Labor-intensive processes, manual reporting, and large support teams are pre-AI cost structures. AI changes the relationship between headcount and output — fewer people handle more volume.

Where are our competitors likely to deploy AI first — and what happens to our margins if they do and we do not?

The first mover that automates a cost-heavy process sets a new price floor you must match. If they deliver the same service at 30 percent lower cost, your margins erode even with equivalent quality.

What new business models become possible if our production costs drop by an order of magnitude?

When production costs drop dramatically, previously uneconomical models become viable — serving smaller clients, offering more granular services, or providing capabilities the current cost structure cannot support.

Business & Workforce Impact

Economic disruption & cost expansion

By Mark Ziler · Last updated 2026-04-05

AI is expanding what small teams can produce while disrupting the economics of entire industries. A five-person company can now deliver output that previously required fifty. This creates both opportunity and threat: opportunity if you adopt AI to punch above your weight, threat if a competitor does it first. The businesses most exposed are those selling services that AI can commoditize — basic report writing, standard analysis, routine consulting.

Go deeper

A two-person consulting firm just pitched one of your enterprise clients with deliverables that look like they came from a 20-person team — polished data analysis, custom dashboards, detailed market research. They're charging a third of what your 15-person team quotes. They didn't hire anyone. They just wired AI into every step of their delivery process. This is what cost expansion looks like in practice: the floor on what a small team can deliver has risen dramatically, and the price premium for large teams is getting harder to justify.

The trap most companies fall into is protecting their current pricing model instead of adapting their value proposition. If AI commoditizes the deliverable, your value has to shift to what AI can't do — deep client relationships, domain judgment built over decades, accountability when things go wrong. Those are real differentiators. But 'we have more people' is no longer one of them.

Questions to ask

Which of our services could a smaller competitor replicate using AI tools at a lower price point?
Where does our value genuinely come from — the deliverable itself or the expertise and judgment behind it?
Are we investing in AI internally fast enough to maintain our margins, or are we waiting for a client to force the issue?