What Consulting Firms Can No Longer Afford to Reuse Blindly
As AI accelerates production, anything that circulates without being fully understood becomes a risk — not an asset.
For years, consulting firms operated under a comfortable fiction: each engagement was unique, therefore each deliverable had to be as well.
That logic produced thousands of brilliant slides — and very few assets that could be reused without caution.
It rested on a rarely questioned assumption: value resided in the final document, not in what made that document possible.
Artificial intelligence is now shattering that fiction.
The paradox consulting firms now face
On the ground, the trend is clear. Consulting firms produce:
more analyses,
faster,
from a broader range of sources,
with unprecedented computational power.
Part of this acceleration is now institutionalized: internal assistants, augmented search tools, synthesis engines connected to knowledge bases.
Another part is more diffuse: more fluid writing, issue analyses drafted upstream, early versions produced before the framing is fully stabilized.
At the same time, a different reality persists:
teams frequently start from scratch on familiar topics,
core assumptions are reformulated from one engagement to the next,
reasoning circulates faster than it is capitalized,
and knowledge remains disconnected from real delivery accountability.
AI did not create this paradox.
It made it visible — and harder to contain.
When knowledge can no longer keep up with delivery speed
Historically, knowledge played a supporting role:
benchmarks,
frameworks,
reference studies.
That role fit a world where production was sequential, and reasoning naturally went through validation cycles.
When AI intervenes directly in production, that buffer disappears.
Knowledge is no longer simply consulted.
It is mobilized continuously, recomposed, sometimes extrapolated — often without clearly stated conditions of validity.
In this context, knowledge ceases to be an input.
It becomes an infrastructure for reasoning.
When that infrastructure remains implicit or fragmented:
teams can move quickly,
deliverables become more fluid,
but partners sign without clearly knowing what has been reused, transformed, or extended.
Speed without shared structure turns knowledge into a blind spot.
The real shift: from documents to reasoning
The most advanced firms have begun a quiet but profound shift.
They no longer focus primarily on storing:
slides,
deliverables,
finished documents.
They seek to capitalize what previously remained invisible:
structures of reasoning,
explicitly discussed and owned assumptions,
clearly defined scopes of validity,
reusable interpretive models that do not require re-engaging full responsibility each time.
What becomes reusable is no longer the deliverable.
It is the logic that led to the deliverable — including when that logic was partially assisted by AI.
Why AI forces this shift now
Without AI, this weakness was costly but tolerable.
With AI, it becomes dangerous.
As production accelerates:
inconsistencies multiply,
contradictions across engagements become visible,
gaps widen between what is officially assumed and what is actually mobilized.
This shift extends far beyond consulting firms.
An analysis of 2024 SEC filings shows that 90% of S&P 500 companies now mention AI in their annual reports (10-Ks), up from 359 companies in 2023.
When AI-assisted reasoning circulates at this pace, the absence of a shared framework is no longer a methodological detail.
It becomes a reputational risk.
AI forces firms to confront a question they have long avoided:
what are we willing to let be reused — and under what conditions?
Three questions AI makes impossible to avoid
As reasoning circulates faster than decisions, some questions can no longer remain implicit. They are neither methodological nor technical. They go to what firms are genuinely prepared to stand behind.
Which figures, models, or analyses would we be unable to explain — line by line — if asked today?
What has become “reusable by default” in our teams, not because it is robust, but simply because it is available?
How many of our AI-augmented deliverables would actually survive a critical review before signature?
From local production to collective responsibility
This shift profoundly changes consulting practice.
Responsibility no longer rests solely with:
an individual consultant,
a manager,
or even a single partner.
It becomes collective, at the practice level — and sometimes at the firm level.
When reasoning is adapted, reused, and recomposed, the question is no longer just the quality of the final deliverable, but what the organization accepts as defensible without systematic revalidation.
These are not tooling questions.
They are questions of reasoning governance.
What AI reveals about real firm maturity
AI acts as a blunt revealer.
It quickly exposes:
where reasoning is structured,
where it remains implicit,
and where it still depends on individual practices rather than a shared framework.
The firms that will succeed will not be those that use AI most intensively.
They will be those that clearly distinguish what can be reused, what must remain situated, and what must be collectively owned.
Conclusion
The true promise of AI is not to produce more.
It is to force organizations to clarify what they are willing to transmit, reuse — and stand behind over time.
The question is no longer:
“What are we able to produce?”
But:
“What are we prepared to let circulate without looking away?”
This is where the practice of consulting is being redefined.
When knowledge becomes a collective asset, signature can no longer remain an individual gesture.
It becomes an act of governance.
