By Abhishek Gupta, Co-Founder, Dekrypt Labs
There is a ritual that has played out in Indian boardrooms for decades. The CFO greenlit a ₹40–80 lakh engagement with a tier-one consulting firm. Three months later, a fresh-faced team of analysts showed up with slide decks built on publicly available data, secondary research, and a few stakeholder interviews your own team had already conducted. The final report landed. It looked impressive. Half the recommendations were never acted upon.
If that sounds familiar, you are not alone.
The Indian management consulting market crossed ₹25,000 crore in 2024. A significant chunk of that spend went toward deliverables that a well-briefed in-house team — or increasingly, an AI system — could produce faster and cheaper.
That gap is what is being disrupted right now.
Before writing off the industry, it is worth understanding what consulting firms have genuinely delivered value on. At their best, they provide three things: structured frameworks for ambiguous problems, access to benchmarks and cross-industry data, and a credible external voice that can tell leadership what internal teams cannot.
The first two are rapidly commoditising. The third is harder to replace — but it is not worth ₹60 lakh when the underlying intelligence is weak.
The core bottleneck in any consulting engagement has always been the research phase: gathering market data, mapping competitors, tracking regulatory shifts, synthesising industry signals. Junior analysts spend 60–70% of their time on this. It is the least differentiated part of the work, and it is exactly where AI has become dangerous to the traditional model.
Here is a specific problem Indian mid-market companies face. A ₹500 crore FMCG company wants to understand whether a new product category is viable in Tier 2 cities. A traditional consulting engagement for this — primary research, competitive mapping, distribution analysis — costs ₹35–50 lakh and takes 10–14 weeks.
By the time the report arrives, the market has moved. Competitors have launched. Distributors have made commitments. The window is narrower than it was.
The same company, using AI-powered business intelligence tools today, can get structured competitive mapping, regulatory context (GST implications, FSSAI requirements), and market signal analysis in days — not months. Not for ₹50 lakh. For a fraction of that.
This is not hypothetical. It is happening across sectors: NBFCs running credit underwriting intelligence in hours instead of weeks, mid-market manufacturers tracking competitor pricing in near real-time, D2C brands running channel intelligence before a category launch.
Fairness requires acknowledging where experienced consultants still add value.
Change management is one. When an organisation needs to restructure, the political capital that a respected external firm carries still matters. AI cannot walk into a boardroom and say "your ops team is the problem" with the same effect.
Deep primary research is another. When you need 200 interviews with kirana store owners in Rajasthan, you need humans on the ground.
And genuine strategic synthesis — the kind that comes from having sat in 50 boardrooms across your industry — is not something a model produces spontaneously. Pattern recognition across lived experience is still a human edge.
But here is the reality: most engagements are not pure change management or primary research. They are intelligence-gathering dressed up as strategy. That is the part that is being automated.
The consulting firms that will survive — and some are already adapting — are the ones that use AI to accelerate the research phase dramatically and deploy senior partner time almost exclusively on synthesis and client relationship work.
For in-house teams, the implication is different. A 3-person strategy team armed with AI-powered intelligence tools can now punch far above their weight. They can track 20 competitors, monitor 15 regulatory bodies, and run structured market analyses on demand — without adding headcount or calling in external consultants for every major question.
The economics are hard to ignore. An annual licence for a serious AI intelligence platform runs a small fraction of a single consulting engagement. The output is continuous, not episodic.
India's mid-market has historically been underserved by consulting. The tier-one firms focused on large enterprises. Smaller firms offered variable quality. Most companies between ₹100 crore and ₹2,000 crore in revenue simply did not get access to structured business intelligence at all.
AI changes that equation. For the first time, a ₹200 crore NBFC in Pune or a ₹500 crore manufacturer in Coimbatore can access the kind of competitive, regulatory, and market intelligence that only large enterprises could previously afford.
The opportunity is not to replace thinking. It is to eliminate the weeks of research that used to precede it.
If you want to see what AI-powered business intelligence looks like in practice for Indian companies, visit dekryptlabs.com.