Existential Threat to Consulting = Huge Opportunity

How AI-encoded expertise disrupts consulting's traditional basis for premium fees, and what firms need to do about it.

This essay has been revised to integrate later developments in my thinking, including the frameworks it now references. The version here is authoritative.

Consulting is expert advice for hire. The entire business model rests on asymmetry: the consultant knows things the client does not. This asymmetry justifies premium fees, long engagements, and the elaborate pyramids of associates, managers, and partners that populate every major firm.

AI is encoded expertise. As that encoded expertise expands in depth and accessibility, the asymmetry that sustains consulting starts to collapse. Clients can increasingly access expertise as a commodity. On demand. At marginal cost. Without the overhead of relationship management or the hassle of procurement.

This is happening now.

The Competitive Scenarios

I’d break down the competitive landscape into five scenarios that consulting firms need to evaluate ruthlessly:

Status quo is the traditional model. Junior consultants gather data and build analyses. Senior consultants provide judgment and manage client relationships. This model assumes expertise asymmetry holds and that clients keep paying for the bundled package of labor and insight.

AI expertise alone covers tasks where AI can do the work without human intervention. When AI capability reaches 100% for a given task, that task becomes commodity-accessible. As undifferentiated as a Google search. No consulting firm can charge premium rates for commodity work.

AI combined with all experts is the race every major consultancy claims to be running. Few have achieved meaningful transformation beyond pilot programs and marketing materials.

Junior expertise plus AI is an interesting middle ground. Less experienced professionals augmented by AI tools might deliver acceptable quality at lower cost. This potentially disrupts the pyramid economics that consulting firms depend on.

Senior expertise plus AI is the most potent combination. And the most dangerous competitor to traditional consulting firms.

The Variables That Matter

Understanding this landscape requires tracking three variables as AI capability advances.

X is the automation threshold: the percentage of a given task that AI can accomplish independently. When X approaches 100%, that task becomes commodity. Consulting firms cannot build sustainable businesses on commodity work. The real question: which tasks are approaching commodity status, and how fast?

A is the acceleration factor: how much existing experts can multiply their output using AI tools. This acceleration represents near-term profit opportunity. A senior consultant who previously managed three engagements might now manage eight. A research team that took two weeks to complete an analysis might finish in two days.

But this acceleration carries a dangerous assumption: that clients won’t demand the benefits. Sophisticated clients will expect firms to pass along AI-driven gains in both time and cost. The acceleration factor is a temporary advantage at best. A window during which firms must build more durable competitive positions.

Z is the senior-plus-AI combination threshold: the percentage of consulting work that a senior expert armed with AI tools can accomplish. As Z approaches 100%, the existential threat to consulting firms becomes acute.

The Existential Math

A senior expert plus AI represents the most dangerous competitor to any consulting firm. This competitor has deep domain knowledge, established relationships, professional credibility, and now access to the same encoded expertise that large firms are racing to deploy. The overhead is minimal. The margins are attractive. The client relationships are personal rather than institutional.

Scale this slightly: a small group of senior experts, each augmented by AI, operating as a lean firm or informal network. This combination might eliminate the need for traditional consulting in entire industry verticals. The pyramid model depends on junior consultants generating leverage for senior partners. It becomes untenable when senior expertise plus AI can accomplish the same work without the pyramid.

Three Hard Questions

The Harvard Business Review recently noted that “AI is changing the cost and availability of expertise, and that will fundamentally alter how businesses organize and compete.” They’re right. Consulting firms need to confront three hard questions to identify whatever durable value might remain.

First: Which aspects of the problems we solve will customers use AI to solve themselves?

This question identifies revenue that will simply disappear. Not revenue lost to competitors. Revenue lost to self-service. When clients can access encoded expertise directly, they will. The analysis that once required a consulting engagement becomes an afternoon with the right AI tools. Firms need to honestly assess which portions of their current revenue fall into this category and plan accordingly.

Second: Which expertise will need to evolve most rapidly to remain ahead of AI’s advancing capabilities?

Static expertise is no longer a defensible advantage. The consultant who mastered a framework five years ago and has been deploying it since faces obsolescence. AI systems are trained on those same frameworks, can apply them more consistently, and improve continuously. The only sustainable position is expertise that evolves faster than AI can encode it. That demands continuous learning, novel synthesis, and the kind of creative judgment that remains difficult to automate.

Third: Which assets can we build that remain competitive as AI advances?

This question points toward the few actually defensible advantages: brand reputation that clients trust implicitly, relationships that transcend transactional value, scarce physical assets or access rights, network effects that become more valuable as they grow. These assets cannot be easily replicated by a senior expert with an AI subscription. They represent the foundation for whatever consulting business model survives this transition.

The Opportunity in the Threat

Organizations that fully exploit AI to rapidly adapt will thrive. This is true for consulting firms and their clients alike.

The firms willing to honestly assess their position, ruthlessly evaluate which scenarios apply to their practice areas, and build toward durable assets will capture disproportionate value. Those clinging to the status quo will discover that encoded expertise waits for no one.

The consulting industry built on information asymmetry must become an industry built on something more durable: verification, accountability, and the kind of synthesized judgment that emerges from deep expertise applied to novel problems. Executable Knowledge Architecture offers one pattern for this transformation, built on a capability-based definition of knowledge that makes human-AI collaboration coherent. The window is narrowing. The pattern exists for those ready to implement it.