Express
₹1.5L5 days
Best forFirst conversation with the framework, single business unit, single industry.
- 7-dimension scoring against the Criterion rubric
- Executive summary memo
- Top 5 prioritized recommendations
Most mid-market AI initiatives fail at the wrong question.
A board-ready AI Readiness Audit in 2 weeks. Built for Indian enterprises in the ₹100–1,000 Cr revenue band.
Anthropic Claude Certified Architect · GCP Professional Cloud Architect · TOGAF
of mid-market AI initiatives stall in pilot.
Across Indian mid-market enterprises, most AI programs never leave the pilot stage. The budget is approved, a proof-of-concept runs, and then the initiative stops short of production — not for lack of ambition, but because the groundwork underneath it was never measured. The question is rarely whether to invest in AI. It is whether the data, governance, and operating model can carry it past the pilot.
Figure: BCG / Zinnov analysis of enterprise AI adoption. Reported as a directional benchmark, not a precise market measurement.
The framework
Seven dimensions of AI readiness
Every audit scores the same seven dimensions. Together they decide whether an AI initiative reaches production — or stalls in pilot. The maturity rubric behind each one is proprietary; what it measures is not.
01
Strategic Alignment
How tightly AI initiatives are tied to board-level outcomes and the annual operating plan.
02
Data Foundation
The quality, lineage, and governance of the data that production AI depends on.
03
Infrastructure & Platforms
Whether cloud, MLOps, and integration choices can carry AI from pilot to production.
04
Talent & Skills
How widely AI fluency is distributed across engineering, product, and operations.
05
Governance & Risk
Model risk management, AI policy, and incident response — the gating constraints for regulated deployment.
06
Use Case Maturity
The depth of the use-case portfolio and the discipline behind build, buy, and partner choices.
07
Operating Model
Decision rights, funding, vendor management, and change management — what turns pilots into business-as-usual.
How it works
Two weeks, three steps
A fixed-scope engagement with a defined start and end. No open-ended retainer, no scope creep.
Week 0
Intake
A mutual NDA, a short scoping call, and a document request. We agree the business units in scope and the questions that matter before any scoring begins.
Weeks 1–2
Audit
Evidence review and stakeholder interviews across IT, data, security, and the business. Each of the seven dimensions is scored against the rubric and triangulated against what the evidence shows.
Week 2
Delivery
A board-ready readout — the composite score, the dimension breakdown, the prioritized gaps, and a sequenced 12-month roadmap — walked through live in a closing workshop.
Not ready for a paid audit? Take the free self-assessment.
15 minutes. 7 dimensions. A personalized AI Readiness Score with your top 3 gaps and recommended next steps.
- A composite AI Readiness Score (1.0–5.0)
- Dimension-level breakdown across all 7 dimensions
- Your top 3 priority gaps with one-line context per gap
- A PDF report of the result by email
Audit options
Three fixed-price engagements. Two weeks or less, except where the scope explicitly calls for more.
Standard
₹3L2 weeks
Best forA board-ready audit for a single legal entity, 200–2,000 employees.
- Everything in Express
- Full stakeholder interviews across IT, data, security, business
- 12-month transformation roadmap
- Closing executive workshop
Comprehensive
₹5L2 weeks
Best forMulti-BU enterprises, 2,000–5,000 employees, regulated industries.
- Everything in Standard
- Multi-BU treatment with cross-entity variance analysis
- Joint compliance assessment (DPDP + sectoral)
- Board-ready executive presentation deck
Enterprise engagements (₹7–10L, 3 weeks) available on request for complex multi-entity scope.
Who runs the audit
Kanhaiya Singh
Criterion is led by Kanhaiya Singh, an enterprise architect who has spent his career designing and governing large-scale data and AI platforms for regulated, multi-entity organizations. The audit methodology is the distillation of that work — the seven dimensions, the rubric, and the scoring discipline come from years of seeing where enterprise AI actually stalls, and what separates the initiatives that reach production from the ones that do not.
Every audit is run by a senior architect, not delegated to a junior team. That is the point of a fixed two-week scope: depth from one person who has done this before, not headcount.
Credentials
- Anthropic Claude Certified Architect
- GCP Professional Cloud Architect
- GCP Professional Data Engineer
- TOGAF
Questions