The verdict in three sentences
CFOs, corporate treasurers and fund managers in New York now ask AI assistants like ChatGPT precise questions about licensed fintech and digital asset firms before they even open a request for proposals. A firm shows up in those answers when its public information is consistent, verifiable and current: exact licence status, custody arrangements, audits, leadership, credible third-party mentions. The work is measured with a dated record of the answers to the same questions, month after month, never with a promise of being recommended.
What are New York buyers actually asking AI assistants?
The typical prospect is not a curious retail user. It is a treasury lead at a listed company, a Manhattan family office or a fund manager looking to outsource custody. The questions are factual and compliance driven. Here are realistic examples of what buyers in this market ask in 2026.
| Question asked to an AI assistant like ChatGPT | What the buyer wants to verify | Page or source that should answer it |
|---|---|---|
| Which digital asset custodians hold a BitLicense in New York? | Exact regulatory status | Licences page with references as actually held |
| Which stablecoin payment provider can serve a Manhattan-based corporate? | Geographic coverage and target clients | Enterprise solutions page, state coverage notes |
| Who audits [firm]'s reserves and how often? | Transparency of attestations | Dated security and attestations page |
| Which New York fintech offers an instant payout API for small businesses? | Product fit | Public documentation, factual product page |
| Has [firm] ever faced regulatory action? | Reputational risk | Press releases, governance page, trade press |
| What are the alternatives to [competitor] for institutional custody? | Shortlist | Mentions in third-party comparisons and articles |
| Who runs [firm] and what is the team's background? | Leadership credibility | Team page, consistent public profiles |
These questions share one trait: the assistant rebuilds an answer from what has been published about you and your competitors. If your licences page says one thing, your company profile another and a 2023 news piece a third, the answer will be vague or wrong.
Why some firms appear and others do not
In such a regulated sector, AI visibility depends mostly on the quality of available information. The factors that come up most often:
- Consistent public information: legal name, licensed entity, address, licences and executives identical across the website, professional directories and public profiles.
- Third-party mentions: trade press articles, membership lists of industry associations, case studies published by partners. An assistant rarely relies on the firm's own word alone.
- Clear factual pages: one page per product, a licences page, a security and custody page, written without any return promise.
- Structured data: markup for the organization, its executives and frequent questions, to remove ambiguity.
- Freshness: a licence obtained last year but missing from the website does not exist for the assistant.
The regulatory constraint weighs heavily. In New York, virtual currency business activity falls under the BitLicense issued by NYDFS, and both the SEC and the CFTC scrutinize how firms in the sector communicate. Content must cite licences exactly as held, display risk warnings and never suggest returns. This is not legal advice. Your compliance team should sign off every page before publication, which is precisely what makes the information reliable to a reader, human or machine.
What the work covers and what it costs on the market
This is an emerging market with no standard rate card. The ranges below are a 2026 ballpark drawn from typical quotes by New York agencies and PR firms specializing in fintech.
| Component | What it covers in broad terms | New York market range (USD, 2026 ballpark) |
|---|---|---|
| Initial diagnostic | Record of current AI answers on a panel of questions | 4,000 to 12,000 one-off |
| Information consistency | Website, directories, public profiles, structured data | 3,000 to 10,000 one-off |
| Compliance-approved factual pages | Licences, custody, security, FAQ | 600 to 1,800 per page |
| PR and third-party mentions | Trade articles, speaking slots | 8,000 to 25,000 per month |
| Ongoing monitoring | Dated monthly record, accuracy report | 1,500 to 5,000 per month |
| Website accessibility | WCAG 2.1 or 2.2 AA target, ADA Title III complaint risk | 3,000 to 15,000 depending on size |
At Kolonell, this work is on quote, after an initial diagnostic. Be wary of any offer that promises citations by an AI assistant: nobody controls those answers.
How to measure without fooling yourself
The only honest measure is a dated record: the same questions asked on the same dates, with answers archived. Three indicators matter most.
| Indicator | Definition | Example reading |
|---|---|---|
| Share of answers citing the firm | Answers mentioning the firm out of the total | 9 out of 60, or 15% |
| Accuracy | Answers citing the firm with no licence, product or executive error | 6 out of 9 accurate, or 67% |
| Position in lists | Average rank when the assistant lists providers | 4th out of 6 on average |
| Sources cited | Pages or articles the assistant attributes | 2 website pages, 1 press article |
| Time to pick up | Delay between a publication and its appearance in answers | Variable, often several weeks |
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Accuracy matters as much as presence. For a licensed firm, an assistant that states a licence you do not hold, or a discontinued product, creates a compliance risk.
Mini case study
Illustrative example: Hudson Ledger Capital, a digital asset custodian in Manhattan with 45 employees. Its head of marketing has 40 buyer questions recorded, each asked 3 times, for 120 answers. The firm appears in 18 answers, or 15%. Of those 18, 6 describe an outdated licence, a 33% inaccuracy rate.
Six-month budget under review: diagnostic at USD 6,000, information consistency at USD 5,000, 8 approved pages at USD 1,000 each for USD 8,000, monitoring at USD 2,000 per month for USD 12,000. Total: USD 31,000, excluding PR. The measurable goal is to bring inaccurate answers below 10% and track share of presence, with no promised recommendation target.
FAQ
Can anyone guarantee that an AI assistant will recommend our firm?
No. Answers from AI assistants like ChatGPT vary with the question, the date and the wording. What can be done is improve the information available and measure the effect on a panel of 30 to 60 questions.
How long before we see a change?
Expect 2 to 6 months in general to see a stable trend in a monthly record. Corrections of simple facts, such as a licence, sometimes show up faster.
Should compliance be involved?
Yes, from day one. In a sector subject to the BitLicense and to SEC and CFTC scrutiny, every public page needs sign-off, which often adds 1 to 2 weeks per content batch.
Does this replace classic SEO?
No, it complements it. Many sources that assistants read are well-ranked pages, and roughly 60 to 80% of the actions, such as factual pages and structured data, serve both.
What is a sensible minimum budget to start?
A diagnostic alone runs USD 4,000 to 12,000 in New York as a 2026 ballpark. It lets you decide with real data before any monthly commitment.
Find out how AI assistants describe your firm. We record what AI assistants like ChatGPT say today about your firm and your competitors on the questions your New York buyers ask. Request a diagnostic quote: reply within 48 hours.
Mohamed Bah
Fondateur, Kolonell
Passionate about digital and entrepreneurship in Africa, Mohamed has been helping Sénégalese businesses with their digital transformation since 2020. Founder of Kolonell, he believes every SME deserves a professional and accessible online présence.
