Platforms. Automation. AI-assisted everything. Leaner teams doing more with less. More scrutiny on every dollar of capital spent. That is not a forecast — it is already how fixed asset work is being done in the organizations paying closest attention.

I am far more interested in where this work is heading than in how it used to be done. So the method gets revisited accordingly — not thrown out, revisited.

The fundamentals have not moved

The shape of a sound fixed asset lifecycle is the same as it has always been: capital planning, capitalization, depreciation, reconciliation, physical verification, retirement, reporting, audit. Nothing arriving in this market changes what any of those stages is for. An in-service date still has to be defensible. A cost still has to trace to a source document. An asset still either exists in the building or it does not.

That stability is a gift, honestly. It means every hour an organization has ever put into getting those stages right still counts. Nobody has to start over because the tooling got better.

What has changed is the coordination between them

What is different now is how much of the work between those stages can be assisted instead of left to memory, email, and whoever happens to still work there.

That in-between space is where I have spent most of my career, and it has always been the expensive part. Facilities knows the chiller was replaced. Accounting knows what capitalizing it requires. Projects knows the building opened in March. Tax knows which classification it needed. Every one of those facts is correct and available, and the sentence connecting them has historically been carried by a person deciding to send an email.

That is not a data problem, and it never was. It is a coordination problem — and coordination is exactly the kind of thing automation and AI-assisted tools are finally good enough to help with.

A close look at what that actually means

I got a close look at it a few weeks ago, working alongside a live cross-industry experiment testing whether a real-time building model could help enforce evidence-based decisions across systems that were never built to talk to each other — pausing a decision instead of guessing when the evidence was not there yet.

The full account of that is in Digital Twins and the Fixed Asset Lifecycle, but the short version is the part that stayed with me. The technology was not the interesting layer. What was interesting is that the process refused to move forward on an assumption. It named the missing item, routed a human to resolve it, and then continued from verified fact.

It is a different industry's proof of the same point I have been building toward in my own practice: the biggest gaps in fixed asset control were never really about data. They were about handoffs nobody owned, and about decisions made confidently on evidence that had quietly gone stale.

Where the leverage is, and where it is not

Being genuinely enthusiastic about this does not mean being uncritical about it. There is a version of this that goes badly, and it is well documented: point capable tooling at an unexamined process and you get a faster, more confident version of the wrong answer. That is the whole argument in Don't Automate a Broken Fixed Asset Process, and the reason dirty data in still means dirty data out.

So it is worth being specific about where the leverage actually sits. The things automation and AI-assisted tooling are good at, in this particular field:

  • Noticing that a physical event happened and telling the person with the financial obligation, without either of them having to remember the other exists.
  • Holding a decision open until the evidence standard is met, rather than closing it on the best guess available at 4:45 on the last day of the close.
  • Re-checking an answer when the underlying facts change, instead of letting a determination from three years ago ride indefinitely because nothing prompted a second look.
  • Making the same reconciliation cheap enough to run continuously rather than heroically, once a quarter, by the one person who knows how.
  • Recording corrections instead of absorbing them, so a repeated failure can be seen as a pattern rather than experienced as bad luck.

And the things it will not do: decide who owns a stage, define what counts as sufficient evidence, or supply the policy it is meant to enforce. Those remain human, organizational and entirely answerable today — on the systems most organizations already own and, more often than people expect, on capability they are already licensed for and have simply never switched on.

Which is why the method keeps getting revisited

That is the lens my Fixed Asset Health Assessment methodology is built through: 15 lifecycle stages, 14 cross-lifecycle dimensions, and a deliberate habit of asking, at every engagement, which parts of this should still be done by hand and which parts should not have to be anymore.

That second question is newer than the framework, and it earns its place. Five years ago, "this step depends on a person remembering" was an observation with no remedy attached — you named it, you documented it, you hoped the person stayed. Now it is frequently a solvable finding. The fourteen dimensions I listen across have not changed (they are laid out in 14 Fixed Asset Warning Signs You're Ignoring), but what a reasonable recommendation looks like inside several of them has moved considerably, and it would be a disservice to clients to pretend otherwise.

Leaner teams are the reason, not the objection

The two pressures showing up in nearly every conversation right now are smaller teams and heavier scrutiny on capital. Both get used as reasons to defer this work. I would argue they are the strongest available argument for doing it.

A smaller team cannot afford processes held together by institutional memory, because there is less memory in the room and fewer people to route around an absence. And capital scrutiny is unforgiving in a specific way: it does not ask whether your register is tidy, it asks whether the number a decision was made on was right. Those are the exact two failure modes that coordination gaps produce.

Leaner teams and heavier capital scrutiny are not a reason to hold onto the old way of doing this work. They are the reason not to.

Where this goes

I will keep writing about this as it develops, because it is developing quickly and most of it is good news. The organizations that get ahead of it are not the ones with the most headcount. They are the ones whose method keeps moving — who know which handoffs they own, what evidence they require, and where their own process is still running on someone remembering.

That inventory is worth taking before the tooling arrives rather than after. See how a Fixed Asset Health Assessment works →