10 Powerful Finance Firms Using AI Interns Today
Introduction: The Intern Revolution No One Saw Coming
I remember my first internship. Long hours. Data entry. Lots of printing. Plenty of coffee runs. It was a rite of passage in the finance world: cut your teeth, prove your worth, hustle, repeat.
But in 2025, things are different.
Today’s most competitive financial firms aren’t just hiring fresh college grads to do the grunt work. They’re onboarding something faster, tireless, and, let’s be honest, much cheaper. They’re using AI interns.
And no, that’s not just a clever nickname. These are AI tools like Hebbia, FinGPT, Sift, and a growing ecosystem of purpose-built language models that handle what junior analysts used to spend weeks on: reading filings, summarizing research, scanning news, and extracting insights from financial documents.
At first, I was skeptical. But then I dug deeper.
Major players like Morgan Stanley, BlackRock, and Goldman Sachs aren’t testing these tools in labs anymore. They’re deploying them across departments. Compliance. M&A. Wealth advisory. Trading desks. And they’re doing it not to replace their workforce, but to amplify it, giving humans more time to think, interpret, and act while the machines do the heavy digital lifting.
In this article, I’ll introduce you to 10 powerful finance firms currently using AI “interns”, and what that really looks like inside their walls.
Because this isn’t science fiction. It’s the new standard of speed, insight, and scale in finance.
And it’s only just getting started.
AI tools changing finance workflows
Why It Matters: AI Interns Are Changing the Finance Playbook
We used to think of interns as wide-eyed college kids learning the ropes. But in 2025, many of those “entry-level” roles are being shared, or even outpaced, by LLMs and task-specific AI tools.
Why?
Because AI interns:
- Don’t get tired
- Don’t make careless mistakes
- Learn instantly from feedback
- Scale effortlessly across geographies
But here’s the important part: they’re not replacing human workers, they’re expanding what’s possible.
Instead of spending all day pulling 10-K data, human analysts now ask:
“What does this data mean?”
“What’s the story here?”
“How can I turn this insight into action?”
It’s not about automation replacing intelligence. It’s about automation freeing intelligence.
1. Morgan Stanley – Scaling Advice with GPT-4
Morgan Stanley is leading the charge with its partnership with OpenAI to deploy a GPT-4-powered assistant trained on over 100,000 internal research reports.
Instead of flipping through PDFs or asking senior associates, wealth advisors now ask their AI assistant, “What’s our latest outlook on renewable infrastructure ETFs?”, and get curated summaries instantly.
This tool acts as a junior analyst: fast, accurate (within limits), and always available.
Why It Matters: It shortens the time between client question and informed response, a game-changer in wealth management.
2. BlackRock – AI for ESG Screening
As the world’s largest asset manager, BlackRock uses AI not only to assess market signals but also to screen thousands of companies for ESG compliance. The firm has integrated natural language processing to monitor sustainability reports, press releases, and even social media.
Their proprietary AI identifies red flags in governance, carbon disclosures, and more, long before humans catch them.
The AI Intern Role: Think of it as a compliance analyst who never sleeps.
3. JPMorgan Chase – Contract Review on Autopilot
JPMorgan’s COiN (Contract Intelligence) platform has reviewed millions of legal documents, automating what used to be 360,000 lawyer hours annually.
Today, they’re applying similar tech across their risk and compliance divisions, using AI to extract clauses, flag discrepancies, and summarize terms in loan agreements.
Why It Matters: It reduces legal bottlenecks and lowers operational risk, all while freeing human experts to handle complex exceptions.
4. Goldman Sachs – AI for M&A Deal Scouting
Goldman Sachs uses AI models trained on past deal flows, press releases, and public filings to identify potential acquisition targets before they hit mainstream radar.
Their AI intern doesn’t just summarize, it predicts fit, analyzes synergy models, and helps scout for signals in private company data.
The Output: Analysts receive ranked lists of “high-likelihood” M&A candidates based on live market signals.
5. Citi – News Aggregation on Steroids
Citi has invested in AI tools that track market-moving news in 14 languages, summarize it in seconds, and route alerts to traders in real time.
No more sifting through dozens of RSS feeds or waiting for Bloomberg terminals to update.
Their internal system even ranks sentiment, bullish, bearish, or neutral, and flags anomalies.
Why It Matters: It’s like having a multilingual media desk that never misses a beat.
6. Bridgewater Associates – FinGPT for Macro Modeling
The legendary hedge fund Bridgewater is no stranger to AI. But lately, their use of FinGPT (a financial-tuned large language model) has deepened.
It helps analyze macroeconomic indicators across countries, simulate scenario models, and even generate summaries of central bank minutes.
The AI intern doesn’t replace economists, it turbocharges them.
Impact: Faster hypotheses, tighter models, and a more agile macro thesis-building process.
7. PwC – AI for Client Reporting and Audit Trail Generation
As one of the Big Four, PwC’s audit teams now use AI to review ledgers, flag inconsistencies, and auto-generate audit trails that satisfy regulatory frameworks.
Junior associates used to spend days formatting reports. Now, AI handles that in minutes.
Output: Consistent, formatted documentation that meets multiple compliance requirements, at speed.
8. Revolut – AI for Customer Risk Profiling
Fintech darling Revolut uses AI to profile customer behavior for fraud detection, risk scoring, and personalized financial advice.
Their system flags anomalies, suggests product nudges, and learns user patterns over time, enabling proactive, not reactive, support.
Bonus: They also use AI to write and A/B test in-app prompts, improving engagement without human micromanagement.
9. UBS – Research Summarization at Scale
UBS has deployed an internal GPT-style tool that ingests market research, analyst notes, and third-party insights, then distills them into client-ready language.
This reduces hours of synthesis into seconds. And for multilingual clients, it even translates tone-matched summaries.
Use Case: Equities desk uses it to prepare personalized pre-meeting briefs in half the time.
10. Point72 – Predictive Talent Screening
Point72 doesn’t just use AI in trading, they’ve built an internal system that analyzes resumes, coding samples, and behavioral interviews to rank potential hires for quant roles.
It’s not a replacement for human judgment, but a scoring layer that highlights hidden gems and flags poor fits early.
Why It’s Powerful: It shortens hiring cycles, reduces bias, and spots talent before competitors do.
FAQ: AI in Finance Today
Q1: Are these tools replacing junior analysts?
A1: Not entirely. They’re shifting the role, less grunt work, more interpretation and strategy.
Q2: Are these tools built in-house or outsourced?
A2: A mix. Some firms partner with startups like Hebbia or OpenAI; others build proprietary models.
Q3: Is this tech accessible to small firms?
A3: Yes. Many AI tools now offer tiered pricing or open APIs, lowering the barrier to entry.
Q4: What skills should future finance pros learn?
A4: Prompt engineering, data literacy, and the ability to translate AI insights into client value.
Final Thoughts: From Grunt Work to Great Work
Finance has always been fast-paced. But now, it’s also algorithmically augmented.
The firms leading the way aren’t just adopting AI for the hype. They’re integrating it where it matters: in the cracks of inefficiency, in the blind spots of risk, in the slow lanes of research and paperwork.
The future analyst isn’t just spreadsheet-savvy; they’re AI-fluent.
And the firms that understand this shift, that embrace AI interns not as threats, but as tools for leverage, are the ones writing the next chapter of financial dominance.
So, whether you’re a founder, fund manager, or just trying to land your next finance role, don’t just compete with AI.
Collaborate with it.