You buy something good. A few years later it still does the job. The market treats it like a relic.

One short doorway: a three-year-old electric vehicle can still be excellent transportation while the used market often values it very differently from “does it still get me there?” In recent studies, used-market prices for EVs have often fallen faster than for the average vehicle of similar age — buyers price improving alternatives, incentives that don’t transfer to used, and a maturing (volatile) used market.1 This is not an EV article. It is about a gap that shows up wherever replacement gets cheaper faster than the last thing wears out.

What was true before

Useful life, technical life, and market life often moved closer together. Replacement was expensive, so we amortized — we extracted value from what we already had. The thing that still worked usually still paid to keep.

The clocks are separating

Four short clocks help name what changed:

  • Useful life — how long it keeps doing the job
  • Technical obsolescence — how soon substantially better capability exists
  • Perceived obsolescence — how soon people feel it is outdated
  • Economic life — how long the market values it enough to buy, keep, or resell

Increasingly, technical and economic life can expire long before useful life. Call that stranded utility — useful capability that still works but no longer holds proportional market value. Valuers talk about related ideas as economic life ending before useful life, often through functional obsolescence.2 We are not inventing a formal term. We are naming a familiar experience in plain words.

One more doorway: single-purpose still works

The same pattern showed up when dedicated digital cameras — and before that, music-only devices like the iPod — still captured images and played songs while phones absorbed those jobs. The devices still worked. Their market role collapsed. Useful life of the capability and economic life of the dedicated device came apart.

The race: replacement velocity vs useful-life consumption

The emerging condition is simple: innovation and replacement cycles can become shorter than useful-life cycles.

Before: Replacement was expensive, so extracting remaining value from what you had made sense. After (emerging): Replacement can get cheap enough that extracting the remaining value becomes the expensive choice.

What GenAI changes

GenAI is an accelerator, not the villain. It lowers the time and cost to create or recreate software, workflows, training materials, media, prototypes, and custom internal tools. That raises replacement velocity. Rapid improvement predated GenAI; GenAI scales it into more domains. Enterprises already debate rebuild-or-replace for systems that still run; AI-assisted modernization narratives sell shorter paths from analysis to prototype — use that as velocity cargo, not destiny.3

Expectations cut residual value early

Belief that today’s product will look dramatically worse in a few years can cut residual value today, before the thing fails. Technology need not fail for economic life to shrink. Perceived obsolescence does real work in the market even when useful life remains.

Four incentives the gap creates

None of these make buyers foolish or markets evil. They are concrete responses to the clocks coming apart:

  1. Delay — Buyers wait because “something better” is always approaching.
  2. Lease or subscribe — Looks wiser than owning when resale is volatile.
  3. Skip repair — Fixing stays technically sensible while becoming economically irrational.
  4. Replace early — Organizations swap working systems — or rebuild custom tools — before useful life is consumed.

What stays human: comprehension debt

Every swap can impose migration, retraining, integration, new uncertainty, and lost institutional knowledge. Call that comprehension debt — the cost of perpetual replace before you’ve fully understood the last tool. A “better” system may never repay switching costs before the next replacement arrives.

That is why pace still belongs to people: learn at the pace of experimentation; adopt at the pace of understanding; scale at the pace of control.

Three practical moves

  1. Separate “better exists” from “replacement is justified.”
  2. Model switching and migration costs — including time-to-competence — before you treat residual useful life as free.
  3. Prefer portability, upgrade paths, and reversibility where change is fast — buy for current utility when promised longevity is a bet you cannot collect.

Close

This is not a lament about disposable culture. It is not anti-tech. The market you inhabit has a gap between usefulness and economic value. See it. Decide inside it.

Footnotes

  1. Dated observation from used-market studies (e.g. iSeeCars off-lease / hold-value segments reporting higher average EV depreciation than all-vehicles averages in those studies); used-EV market also maturing and volatile — cite as “often / in recent studies,” not an indictment.

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  2. IVS framing of physical vs economic life and functional obsolescence: https://viewpoint.pwc.com/dt/gx/en/ivsc/international_valuat/international_valuat_INT/international_valuat_INT/International-Valuation-Standards/General-Standards/IVS-105-Valuation-Approaches-and-Methods/80_Depreciation_Obsolescence.html ↩

  3. Example of AI-assisted legacy modernization narratives shortening rebuild timelines (velocity illustration only): https://www.computerweekly.com/news/366645393/Insurer-Unum-aims-to-deliver-benefits-of-20m-using-AI-to-re-write-old-Cobol-code ↩