AI is collapsing the cost of the analysis that strategy and M&A advisory was built to sell. The firms that endure will stop shipping one-time decks and start running always-on intelligence — reserving their people for the judgment clients actually pay for.
Strategy and M&A advisory rests on a quiet premise: that rigorous market analysis is expensive and slow to produce, and therefore worth paying handsomely for. A growth question — where to expand, what to buy, who might buy us — once meant weeks of market reports, expert calls, and modeling, synthesized by a leveraged team into a hundred-slide deck and a seven-figure invoice. That premise is now under direct assault, and with it the economics of an entire profession.
What the analysis used to cost
The value was always tied to the cost of producing insight. Commercial due-diligence reports from leading firms routinely run into the hundreds of thousands of dollars and take weeks to deliver; the price reflected the labor required as much as the conclusions reached. Generative AI compresses that labor dramatically, turning weeks of research, synthesis, and drafting into hours. The Financial Times has reported that the resulting pressure is forcing McKinsey and its peers to rethink the billable-hour pricing that has underpinned consulting for decades. When the analysis becomes cheap to produce, the deliverable that was the analysis loses its scarcity — and a deck built on a point-in-time market read begins aging the moment it is bound.
The productivity paradox
Here the industry meets an uncomfortable bind. The same efficiency AI offers also cannibalizes the billable hours on which firm economics, leverage ratios, and partner compensation depend. The rational response has been to adopt the technology visibly while deploying it carefully — investing to look innovative while protecting the pyramid underneath. Firms are spending heavily on the future they are slow to fully embrace: standing up proprietary analytics units such as McKinsey’s Quantum Black, committing billions to AI partnerships, and, in Bain’s case, acquiring a deal-data business built around a living industry taxonomy before later divesting it. The direction of travel is clear; the operating model has not caught up. Meanwhile, AI-native challengers — several founded by former diligence leads at the major firms — are unbundling the most repeatable analytical work and selling it faster and cheaper.
When the analysis is cheap to produce, the advantage shifts to whoever maintains it continuously — and to the judgment laid on top.
From deck to living system
The resolution is not a better deck produced faster. It is a different artifact altogether. The repeatable analytical core of strategy and M&A work — the market map, the company landscape, the target screen, the buyer universe — should not be rebuilt from scratch for each engagement and discarded at its close. It should be a living system, maintained continuously and drawn upon on demand.
Such a system rests on four capabilities. A detailed, living industry taxonomy that resolves a sector into its real segments, sub-segments, and adjacencies, and stays current as it evolves. Coverage of both the demand and supply sides at once — who is acquiring and why, who is consolidating, where capital concentrates, and which assets are coming into play. Every company linked to that taxonomy and to its own strategic priorities, not just the names in a current mandate. And predicted transaction likelihood, on both the buy- and sell-side, before anyone is at the table.
On that substrate, a commercial diligence is refreshed rather than reconstructed; a market map is a query rather than a project; a target screen or buyer universe is standing and ranked. The bespoke deck becomes a view into a system that was already current — and the advisor’s time shifts from assembling the analysis to interpreting it, which is the work clients were always paying a premium for in the first place.
Why now
This is the more durable version of the shift the consulting industry is already gesturing toward: from pyramid to platform, from selling hours to maintaining intelligence, from recommendations to decisions. What separates the two futures is where the analytical work lives. Firms that keep rebuilding it by hand will find themselves competing on cost against tools that never tire. Firms that run it as an always-on asset will compete on judgment — and reserve their most expensive people for the part no model can supply.
That is the layer Espalier provides: an always-on decision intelligence system that keeps an industry continuously mapped, so the analytical foundation of strategy and M&A advisory is maintained rather than manufactured. The deck will always have a half-life. The intelligence beneath it does not have to.
