Regulated-industry AI buyer’s guide (India).
Questions CFOs and compliance officers should ask before signing an AI vendor — DPDP, updates, liability, and evidence — not just a demo.
·8 min read
TL;DR
Indian regulated buyers should diligence AI vendors on purpose limitation, consent UX, data residency, how knowledge stays current, and what happens when the model is wrong. Brandlabs expects these questions — and asks them of our own lab products like Correct.
What should an Indian CFO or compliance officer ask an AI vendor?
Ask what personal data enters prompts, how consent and withdrawal work, where data is processed, who is liable for incorrect guidance, and how often regulatory content is updated. If answers are only model names and logos, stop the evaluation.
Steal-this list:
- What purposes does each AI feature serve — in writing?
- Can we export or delete personal data on request paths you support?
- Which subprocessors see prompts or documents?
- Cross-border transfers — where, and under what terms?
- How do you prevent hallucinated rules, rates, or deadlines?
- What audit logs can we access?
- What is the human escalation path?
Correct’s domain taught us buyers care about missed filings and wrong guidance more than chat polish.
How do you evaluate “AI that knows regulations” claims?
Demand corpus freshness metrics, source citations, eval samples for fabricated acts/sections, and a clear statement that the product is not a substitute for qualified professionals. Fluency is easy. Currency and humility are hard.
Red flags:
- No last-updated dates on regulatory content
- No refusal behavior for edge legal conclusions
- No separation between workflow status and model prose
- Security questionnaire answered with “we use encryption” only
Green flags:
- System of record separate from the LLM
- Eval gates for hallucinated obligations
- Role-based access and notice/consent UX
- Named humans behind escalations
What commercial terms protect the buyer?
Clear data processing terms, subprocessors list, uptime and support expectations, exit/export rights, and honest limitation of liability language around AI outputs. Price without posture is a future incident cost.
Whether you buy Brandlabs as a build partner or a SaaS like Correct, insist on artifacts you can show an auditor: DPAs, architecture diagrams, and sample logs.
Demoing the chatbot is the beginning of diligence, not the end.
Frequently asked questions
Is this legal advice for DPDP?
No. Use counsel for applicability and contracts. This is a buyer diligence checklist from shipping regulated products.
Does this apply only to fintech and compliance SaaS?
No. Health, HR, and any product processing personal data in India should run a similar list.