The Operational AI Platform Market Space – (Are valuations frothy?)

My take is that they are not and despite bleating by the worried commentators, the AI value march continues to pick up pace.

The PC era eliminated typing pools, filing rooms, and manual clerical labor. Tasks like these moved from human workflows into software. That shift did not reduce total spend on labor. Instead, corporate IT spend increased because coordination complexity increased when work scaled. Software became a fixed operating requirement, not an optional enhancement.

The winners were platform vendors:

• Microsoft controlled the work surface (Windows + Office).
• Intel captured compute demand
• Cisco captured networking demand .

The AI growth rhymes with this.

The key dynamic was that labor-cost reduction cycled back into software and compute spend, and the software layer that mediated daily work became the structural control point for enterprise productivity.

The same pattern applies to AI.

Organisations like NHS have deployed large initial use cases for Palantir – Its easy to see this being replicated globally

AI does not only replace repetitive tasks. It replaces coordination—the planning, routing, optimizing, deciding, and communicating that sits between organizational nodes.

Coordination shifts from humans to software, the operational execution layer becomes the new control surface.

Labor spend is not removed—it is converted into:

• Compute capacity
• Model inference
• Workflow orchestration platforms
• Integrated operational decision systems

If one platform becomes the default place where operational decisions are executed, it occupies the same structural position Microsoft held in the PC revolution: the layer through which work occurs. There will be a place for a Microsoft of the AI world

That platform becomes the operating system for the organization. the spend base is no longer defined by the size of the IT budget. It is defined by the scale of operational labor being replaced. (Just like Windows was once)

Western workforce ≈ 440M
Assume 7.5% roles eliminated → ~33M jobs
Average fully-loaded cost per role → ~$100k/yr
Annual labor cost removed → ~$3.3T/yr

Historically, automation cycles reallocate 40–60% of displaced labor cost into the enabling systems.
Use the midpoint: 50%.

New capital flowing into AI systems:
~$1.5T per year.

Allocation across the AI stack:

• Compute/datacenters/GPUs: ~45–55% → ~$700B/yr
• Model/API inference: ~10–15% → ~$150–$250B/yr
• Operational AI platforms: ~20–30% → ~$300–$450B/yr
• Integration + workflow transition: ~10–15% → ~$150–$250B/yr

This puts the operational AI platform market (the layer where decisions and workflows run) at:

~$300B–$450B per year steady-state.

This is the layer Palantir is architected to occupy.

It is the only part of the stack that controls execution, and execution is where persistent value accrues.

Valuation Implication

If Palantir becomes a mid-tier platform (5–10% share):

• Revenue: ~$15B–$40B/yr
• At 12×–20× sales: ~$200B–$800B valuation

If Palantir becomes a dominant operational layer (15–25% share):

• Revenue: ~$45B–$110B/yr
• At 12×–20× sales: ~$550B–$2.2T valuation

If Palantir becomes the default operating system for organizational execution (the Microsoft-on-operations outcome):

• Market share approaches 30%+
• Revenue exceeds ~$120B/yr
• Valuation aligns with Microsoft-scale: ~$1.5T–$3T depending on margin structure

Conclusion
The relevant comparison is not against current SaaS markets.
It is against the operational labor base being automated.
If AI shifts coordination and decision-making into software, the platform that becomes the default execution layer captures structural, recurring, control-layer economics—the same dynamic that made Microsoft the dominant winner of the PC era.

Under that model, Palantir’s valuation path ranges from $1T on modest penetration to $2T+ if it becomes the operational OS.