Will AI Destroy Consulting? - A Poorly Framed Question
In the previous post, “When Even McKinsey Is Not Immune: What the Layoffs Reveal About the Entire Industry,” we argued that the challenges facing the consulting industry are not isolated cases, but symptoms of deeper structural tensions embedded in the dominant model.
This article shifts the lens once again — from institutions to technology — to reframe a question that is often asked in the wrong way.
Few topics generate as much anxiety within the consulting industry today as artificial intelligence. Headlines oscillate between alarmism and optimism: AI will replace consultants; AI will supercharge them; AI will upend the entire value chain.
Beneath the noise lies a more fundamental issue. The question is not whether AI will destroy consulting. It is whether it exposes weaknesses that were already present in the prevailing model.
The recurring fear of automation
Consulting has always lived with technological anxiety. Each wave of innovation — from spreadsheets to advanced analytics — has raised concerns about the relevance of human expertise.
Yet the profession endured, largely because its core promise was never computation alone. It was judgment: the ability to frame problems, weigh trade-offs, and guide decisions under uncertainty.
What makes artificial intelligence different is not that it threatens judgment, but that it dramatically reduces the cost and time of many activities the industry long treated as value-generating by default.
What AI actually replaces — and why
Much of what AI now enables in consulting falls into familiar categories:
data synthesis and pattern recognition,
benchmarking and comparative analysis,
scenario modeling and rapid iteration,
production of structured outputs at scale.
These activities were never the essence of consulting. They were the scaffolding around it.
The discomfort arises because, over time, that scaffolding became monetized. When tasks that are automatable are packaged as core value, technological progress does not disrupt — it reveals.
Knowledge, judgment, and execution are not the same thing
A persistent flaw in the AI debate is the conflation of three distinct layers of consulting work:
knowledge: information, frameworks, accumulated experience;
judgment: the ability to interpret context, prioritize, and decide;
execution: translating decisions into organizational change.
Artificial intelligence is highly effective at expanding access to knowledge and supporting elements of execution. Judgment — especially in ambiguous, political, or high-stakes environments — remains fundamentally human.
The implication is uncomfortable but clear: if a consulting offering derives most of its value from activities AI can replicate, the problem is not the technology. It is the offering.
AI as a structural stress test
Rather than asking whether AI will replace consultants, it is more accurate to view it as a stress test applied to the industry’s underlying architecture.
AI compresses time, lowers marginal costs, and increases transparency. In doing so, it challenges models built on:
billing for effort rather than impact,
opacity of methods,
repetition of bespoke work that is not truly bespoke.
These pressures do not eliminate the need for advisory work. They redefine where value genuinely resides.
When technology forces a business model shift
More quietly, this pressure reaches the business model itself. As AI lowers the marginal cost of analysis and compresses delivery cycles, it weakens the logic of billing for time, volume, or artisanal production.
When insight can be generated faster and reused more broadly, value shifts away from effort and toward judgment, integration, and outcomes.
This is not primarily a technological disruption, but an economic one. The question is no longer how consultants work with AI, but what clients are actually paying for — and why.
Closing: acceleration, not annihilation
Artificial intelligence is not killing consulting. It is accelerating the decline of a specific design — one in which value is inferred from effort, complexity, and hours consumed.
What remains — judgment, accountability, and the ability to help organizations act — was never automatable to begin with.
The real question, then, is not whether consulting will survive AI. It is which forms of consulting were never built to survive a world where inefficiency is no longer invisible.
