In the previous posts I argued that most companies think about AI linearly. Make the process faster. But keep the layout the same. Bolt the electric motor onto the old belt-and-shaft system and call it AI-progress.
But there is a bigger question that almost nobody is asking. What if AI does not just change how work gets done inside your company? What if it changes why your company is shaped the way it is?
Oliver Williamson won the Nobel Prize in 2009 for a deceptively simple insight. Companies exist because coordinating work internally is cheaper than buying it from the market. That is it. The boundary of any firm sits wherever the cost of doing something yourself becomes higher than the cost of getting someone else to do it.
Those costs have specific names. Search costs, finding the right supplier or partner. Monitoring costs, making sure they deliver quality. Coordination costs, managing handoffs across organizations. Contracting costs, negotiating and enforcing terms. Every company you have ever worked at is shaped by these four forces. The departments that exist, the functions that are in-house, the work that gets outsourced. All of it traces back to where those costs tip.
AI just tipped them all at once.
No previous technology did this. The telegraph reduced search costs. You could find a supplier in another city without traveling there. Containerization reduced coordination costs. Standardized boxes replaced custom loading at every port. The internet reduced distribution costs. You could sell directly without a physical storefront. Each technology moved one or two cost categories and reshaped one or two industries as a result.
AI hits all four simultaneously. It reduces search costs because an agent can scan, compare, and qualify suppliers in minutes. It reduces monitoring costs because machine-audited quality checks replace manual inspection. It reduces coordination costs because protocol-based integration replaces bilateral negotiation. It reduces contracting costs because automated compliance tracking shrinks the surface area for disputes.
When all four drop at the same time, firm boundaries do not just shift. They recompose. Functions that companies kept internal because market coordination was too expensive suddenly become cheaper to buy. And functions that were outsourced suddenly become worth bringing back inside, because AI made internal coordination cheap enough to justify full control.
Both movements happen simultaneously. That is what makes this different from a simple outsourcing wave or a simple insourcing trend. It is a recomposition. The pieces come apart and go back together in a different configuration. Same LEGO bricks, different structure.
You can see it happening now in three places.
In outsourced services, the BPO industry is being recomposed. FTE-based pricing, paying for headcount, dropped from 42% of contracts to 28% in three years. Outcome-based pricing, paying for results, grew from 20% to 39%. The relationship between buyer and provider is being redrawn because AI made it cheap enough to monitor outcomes instead of supervising people. The BPO firm that used to sell labor is becoming a firm that sells completed work. That is not an improvement to the old model. It is a different business.
In manufacturing supply chains, AI-driven demand sensing and real-time quality monitoring are changing which parts of the supply chain companies own and which they contract. When you can monitor a supplier’s output quality in real time through machine inspection, the case for vertical integration weakens. When you can coordinate just-in-time delivery across dozens of suppliers through automated scheduling, you no longer need to own the warehouse. The transaction cost that justified the old structure disappeared.
In professional services, legal research, financial analysis, compliance screening. These functions existed inside large firms partly because the cost of finding, coordinating, and monitoring external specialists was too high. AI is collapsing those costs. The result is not that law firms or banks shrink. It is that the boundary between what they do internally and what they source externally is moving. New specialist firms emerge to serve functions that used to require an in-house team. Old generalist providers lose work that gets absorbed back into the client organization.
The trap is thinking about this as “transformation,” a word that implies the same company changes shape over time. What is actually happening is faster and more structural. The economics that determined why your company has the shape it has are shifting underneath you. Departments that exist because coordination with the outside was too expensive may no longer need to exist. Partners you outsourced to because internal capacity was too costly may no longer be the right answer either.
Three questions:
- First, list the functions you keep in-house. For each one, ask whether the transaction costs that justify internal ownership have actually changed. If AI made external coordination 5x cheaper, does the function still belong inside?
- Second, list what you outsource. For each one, ask whether AI has made internal coordination cheap enough to bring it back. Sometimes the right move is the opposite of what you expect.
- Third, look at where your industry boundaries are drawn. Companies that see recomposition coming will redraw their own boundaries first. Companies that do not will have the boundaries redrawn for them.
This is not about making your company faster. It is about whether your company is still shaped for the economics it operates in. The pieces are the same. The structure they fit into is not.
Sources:
- Williamson/Coase framework: California Management Review, “From Coase to AI Agents” (2025)
- Oliver Williamson Nobel Perspectives: UBS
- AI and transaction cost reduction: Labor Market Matters, “AI, Transaction Costs, and Self-Employment”
- BPO recomposition data (FTE to outcome pricing): a16z, “Unbundling the BPO”; FirstSource, “Future BPO Services”
- Fluid firm boundaries: Raktim Singh, “The Fluid Boundary of the AI-Era Firm”
- AI as coordination-compressing capital: arXiv 2602.16078
- Healthcare AI transaction cost framework: arXiv 2604.16465
