Work Smarter, Not Harder: Top 5 AI Prompts Every Finance Professional in New York City Should Use in 2025

New York City finance teams face relentless data, tight compliance windows, and client expectations for faster, smarter advice - which is why targeted AI prompts matter: prompt libraries can automate reporting, flag compliance risks, and model scenarios so analysts spend time on strategy, not formatting; Glean's finance AI prompts collection streamlines forecasting, expense categorization, and fraud detection to boost productivity and decision quality (Glean collection: 30 AI prompts for finance professionals).

Adoption is already material in NYC: a 2025 Horsesmouth AI usage survey found advisors using AI multiple times per day rose to 24%, signaling a shift from one-off queries to iterative, workflow-driven use (Horsesmouth 2025 survey on AI use by financial advisors).

For finance professionals who need practical training, Nucamp's AI Essentials for Work bootcamp teaches prompt-writing and workplace AI skills in a 15-week, hands-on format (AI Essentials for Work - Nucamp 15-week workplace AI training), making it realistic to convert a few high-impact prompts into hours saved each week.

“No longer starting from a blank page … AI gives me momentum on writing, presentations, and even structuring meetings.” - Horsesmouth survey respondent

Selection focused on prompts that deliver repeatable, auditable value for fast‑paced NYC finance teams: candidates were first filtered by fit with a structured prompt template (the PTCF Persona–Task–Context–Format prompting framework by ADDRC PTCF prompting framework - ADDRC), then screened for measurable business impact based on industry adoption research and outcomes (prompt engineering as a core finance skill and adoption forecasts summarized by WithVayu prompt engineering adoption and forecasts - WithVayu), and finally culled from practical libraries of ready‑to‑use prompts (candidate prompts came from collections such as Glean's prompt library 30 AI prompts for finance professionals - Glean).

Criteria emphasized clarity, compliance readiness for New York workflows, and low friction deployment (no‑code templates and pre‑built workflows), with final refinement in practitioner settings - including hands‑on workshops - so the five prompts are small, reusable templates that research shows can reduce editing time by up to 70% and free analysts to focus on interpretation, not formatting.

“Clarity in instructions leads to clarity in execution”

For quarterly close reviews, a single, structured ChatGPT prompt transforms raw trial balance and recon data into an audit-ready variance memo, evidence checklist, and suggested substantive tests: instruct the model with role

“Audit Manager, mid‑sized NYC finance team”

, scope (current quarter vs.

prior quarter and YTD), accounting standard (US GAAP), thresholds for material variances, and required outputs (1‑page executive summary, a table of top 10 variances with likely causes, PBC checklist, and draft journal entries for review); this mirrors best practices in audit prompt crafting and keeps client confidentiality front and center while streamlining confirmations and evidence collection described in audit‑focused guides like Circit ChatGPT prompts for audit management and DFIN AI prompts for financial reporting; so what? - the result is a concise, reviewer‑friendly close pack and PBC list that teams can hand to auditors, cutting manual editing and handoffs and freeing time for interpretation rather than formatting.

Use Google Gemini to generate a compact, investor‑grade NYC macro brief by prompting the model to act as a “New York City macro analyst” and return: a one‑paragraph executive summary citing local GDP and AI ecosystem metrics, a short list of sector opportunities (finance, real estate, media), a “policy & compliance red flags” box that calls out Local Law 144, NYDFS AI cybersecurity guidance, and pending state bills (e.g., S011692 and A007683), plus a 3‑point takeaway for clients or portfolio managers; anchor the brief to city research so outputs reflect local realities - see the NYCEDC action plan and ecosystem numbers for applied AI context and the detailed state regulatory framing in the NYCEDC report on AI in New York City for applied AI context (NYCEDC report on AI in New York City) and the Chambers practice guide "Artificial Intelligence 2025 - USA: New York" for governance notes (Artificial Intelligence 2025 - USA: New York governance and trends); so what? - including a built‑in compliance checklist means each Gemini brief becomes a single, audit‑ready page a CFO can hand to legal and investment committees, avoiding repeated lookups across disparate city and state sources.

"What I love about New York is that you have people from all over the world working on all aspects of AI in a very dense area. It's a common occurrence to go to an event and meet folks from academia, from pretraining startups, from bigger technical companies, and from art, journalism, and media." - Sasha Rush

Turn client calls into auditable next steps by borrowing Abridge's core capabilities - speech‑to‑text tuned for noisy, multi‑speaker conversations, linked‑evidence summaries, and provenance tracking - and prompting the system as “meeting scribe & compliance annotator”: provide the speaker‑attributed transcript, the meeting role (e.g., “Client PM, VP Finance, external counsel”), and ask for (1) a one‑paragraph client‑facing summary, (2) a prioritized list of action items with owners, deadlines, and suggested calendar invites, and (3) an evidence map that links every action to transcript timestamps or supporting quotes.

That structure mirrors enterprise‑grade workflows Abridge builds for clinical notes - so outputs are both contextual and verifiable - and pairs well with meeting‑to‑task flows shown in AI scribe guidance (automatic summaries and action‑item extraction) used across platforms like Tactiq.

The practical payoff for NYC finance teams: concise, compliance‑ready deliverables that reduce after‑hours write‑up and handoffs by moving verification into the transcript itself, not separate paper trails; for implementation details see Abridge's product features and contextual reasoning engine and Tactiq's meeting‑notes best practices.

“The reduction in cognitive load with Abridge has been incredibly freeing and is giving me back precious time with my patients and family.” - Dr. Kristin Jacob, Corewell Health

Legora's AI workspace brings contract and compliance review into NYC finance workflows by turning “folders full of contracts” into an interactive tabular review where each document is a row and custom prompts produce comparison columns - so teams can extract key clauses, benchmark against firm playbooks, and spot inconsistencies without manual copying; its Word add‑in and conversational Assistant keep drafting, redlining, and citation‑backed answers inside the document, while integrations with DMS providers (including the native NetDocuments link) and EDGAR‑enabled research let counsel cross‑check SEC filing language and disclosure triggers in the same workflow, reducing risky cross‑referencing before deadlines.

For New York finance legal teams handling leases, vendor agreements, and SEC‑sensitive covenants, that means faster, auditable reviews that hand negotiators concise, source‑linked recommendations instead of piles of exported PDFs - see Legora's product overview and its NetDocuments partnership for implementation details.

“The partnership with NetDocuments is another example of our commitment to collaborations that add the most cutting edge innovations to our platform and deliver real value to our users. The combined power of NetDocuments' AI-powered search and Legora's agentic capabilities working in tandem does exactly this. Through this native integration our clients will be able to easily and securely conduct deep research of their NetDocuments-stored files, frictionlessly transfer documents directly to and from Legora, and instruct Legora to execute tasks with the documents. They'll be able to do all of this through intuitive, natural language prompts or through direct access to their NetDocuments storage from within Legora, whilst remaining totally assured that their documents are secure and protected throughout the process.” - Max Junestrand, CEO, Legora

Anthropic's Claude (Claude 4 + Claude Code) can be turned into a pragmatic code‑generation partner for ETL and automation by applying concrete prompt engineering: be explicit about role, input formats (CSV, database query, or piped logs), and the exact output you need (modular Python/SQL scripts, tests, and a cleanup step), add repository context via a checked‑in CLAUDE.md so every analyst's session pulls the same bash commands and style rules, and ask Claude to run tools in parallel or in headless mode for CI automation while cleaning up temporary files when finished; these practices - drawn from Anthropic's Claude 4 prompt engineering guidance and Claude Code best practices - help NYC finance teams move from ad‑hoc snippets to reproducible ETL runs that integrate with git, gh, and CI workflows, reducing brittle one‑off scripts and making code handoffs auditable and predictable (Anthropic Claude 4 prompt engineering best practices, Anthropic Claude Code agentic coding best practices).

To get started in a New York City finance role, pick one high‑value, low‑risk prompt (Founderpath's library shows teams save meaningful time - implementing 10–15 targeted prompts reduced routine work dramatically and cut consultant fees) and run a two‑week pilot that uses the SPARK or PTCF prompting checklist to set role, scope, inputs, and a clear output format; pair that pilot with an AI adoption roadmap that prioritizes security and measurable ROI so you can answer IT and compliance questions (see the Founderpath prompt examples for finance teams at https://founderpath.com/blog/top-ai-prompts-finance-business and the Workiva AI Adoption Blueprint for governance and pilot templates at https://www.workiva.com/resources/ai-adoption-blueprint-how-get-ai-you-actually-need).

If you want hands‑on training to standardize prompt craft and governance across your team, consider Nucamp's 15‑week AI Essentials for Work course to turn one successful pilot into repeatable workflows that legal, audit, and portfolio teams in NYC can trust (AI Essentials for Work - Nucamp: https://url.nucamp.co/aiessentials4work).

Start small, measure time saved and accuracy, then scale the prompts that pass compliance and stakeholder review.

“an umbrella term without precise boundaries, that encompasses a range of technologies and techniques of varying sophistication that are used to, among other tasks, make predictions, inferences, recommendations, rankings, or other decisions with data…”