How AI Is Giving Investment Banking an Upgrade

There was a time when “AI in investment banking” sounded like something you’d hear over a bad Bluetooth connection at a fintech conference. Fast forward to today, and AI isn’t just crashing the party; it’s at the head of the table, asking for the deal deck. Whether you’re considering your next big M&A or just trying to find where you left your 12th version of the pitchbook, AI is quietly becoming the partner no one saw coming.

In practice, investment banks are using AI to supercharge everything from due diligence to client prospecting, risk management, and even compliance. Imagine a world where your analysts spend less time squinting at spreadsheets and more time, well, actually analyzing. Or where the pitch is tailored so perfectly for your client that it feels like you’ve hired a psychic: one with a CFA and and not alot of need for sleep.

So, what does this mean for the future of investment banking? Let’s look at how AI is actually shaking things up on Wall Street and beyond.

Real-Life Examples of AI in Investment Banking

1. Farsight AI: An Analyst Who Doesn’t Need Coffee Breaks

Meet Farsight AI, the brainchild of former Goldman Sachs executive Mahesh Dutta. This AI tool is helping investment bankers with rapid company research, real-time due diligence, and faster deal sourcing. According to Crunchbase, Dutta’s team recently raised over $10 million to bring “billion-dollar banker” analytics to everyone—think of it as your sharpest junior associate, but one who doesn’t complain about pulling an all-nighter. Farsight analyzes massive data sets and surfaces key information in minutes, reducing the traditional two-week research process to a matter of hours. The result? More time for client meetings, less time drowning in PDFs. And yes, your bonus pool might thank you.
Read more on Crunchbase

2. Goldman Sachs Launches Firmwide AI Assistant: Modernizing the Banking Workflow

In June 2025, Goldman Sachs made headlines by rolling out its AI assistant to over 10,000 employees across the firm. This new tool supports teams in investment banking, wealth management, trading, and research by helping bankers and analysts summarize complex documents, draft client materials, and conduct data analysis in record time. According to leadership, the AI assistant is even capable of selecting the most suitable language model for a given task, making workflow smoother and freeing up staff for higher-value client activities. While junior bankers everywhere might miss the late-night caffeine runs, the firm’s move signals a clear future: even the world’s most established investment banks are making AI an everyday business partner and gaining efficiency and a strategic edge in the process. More from Reuters

3. JPMorgan’s Coach AI: Turning Market Turbulence Into Opportunity

In May 2025, JPMorgan Chase shared that its Coach AI and GenAI suite helped bankers boost sales and win clients even as markets grew choppy. During the spring’s market volatility, Coach AI enabled bankers to pre-populate research, anticipate client questions, and deliver timely, relevant insights in real time. This speed and intelligence meant a 20% jump in asset and wealth management sales from 2023 to 2024 and a projected 50% increase in new client acquisition over the next several years. What’s more, JPMorgan reported $1.5 billion in operational savings thanks to AI-powered enhancements in fraud detection, trading, credit, and advisory work. For investment banking leaders, the message is clear: AI is not just a research assistant, it’s a strategic lever for growth. More from Reuters

Prompts for Investment Banking Executives

Looking for ways to put AI to work in your own day-to-day? Here are five prompts you (or your analysts) can try, tailored for investment bankers. Just fill in the blanks where you see fit.

1. Deal Sourcing:
   “Analyze [industry/sector] for potential M&A targets based on recent financial performance, deal activity, and market trends. Highlight companies with high growth, low debt, and recent management changes. For [specific company name(s)], include analysis of the following key metrics: [list specific metrics, e.g., EBITDA margin, revenue growth, ROE, etc.]. Provide a summary table with these metrics, key financials, and any red flags you identify. Add commentary on why these metrics are relevant for our current investment thesis or acquisition criteria.”

2. Due Diligence Acceleration:
   “Review the attached [set of contracts/data room documents] for [deal name]. Summarize any unusual clauses, contingent liabilities, and regulatory risks. Identify areas such as intellectual property, outstanding litigation, environmental liabilities, change-of-control provisions, employee and pension obligations, material customer or supplier dependencies, insurance coverage gaps, and any off-balance sheet items. Assess the quality and completeness of financial statements, confirm major compliance issues, and flag any inconsistencies or missing information. List anything that requires further legal, financial, or operational review before proceeding with the deal. Provide a summary table of findings categorized by risk type and urgency, along with suggested next steps for the diligence team.”

3. Pitchbook Customization:
   “Prepare a personalized pitchbook for [client name] considering their recent M&A activity, peer transactions, and current market conditions. The pitchbook should include: an overview of the client’s business and strategic objectives, a detailed analysis of recent peer transactions, valuation benchmarks, financial summaries, market trends, and investment highlights. Highlight potential deal structures, financing options, and illustrative transaction scenarios. Include analysis of relevant risks, mitigation strategies, and potential synergies. Provide a one-page executive summary with talking points tailored to the client’s leadership team, as well as recommended next steps for the deal process.”

4. Market Intelligence for Clients:
   “Summarize current market conditions in [target region/sector] relevant to [client name]’s business. Include:

   • Macro trends and economic factors: GDP growth, interest rates, regulatory changes, inflation, and FX pressures.

   • Market sizing and growth forecasts: segment revenue, CAGR, and projected expansion based on recent data.

   • Deal flow insights: number, size, and type of transactions (M&A, IPOs, spin-offs) over the past 12 months—highlighting valuation multiples and buyer/seller profiles.

   • Competitive landscape mapping: market shares, product positioning, and recent strategic moves by top players.

   • SWOT analysis comparing [client] to its top three competitors—covering financial strength, management quality, operational efficiency, innovation, and regulatory exposure.

   • Customer and supply chain dynamics: concentration risk, stop-gap reliance, and cross-border dependencies.

   • Emerging threats and opportunities: disruptive technologies, ESG or geopolitical shifts, potential substitute entrants, and regulatory or compliance trends.

   Wrap up with a strategic narrative that ties these insights to practical implications for [client]—including suggested decisions on timing, positioning, or structuring your next deal.”

5. Regulatory Compliance Monitoring:
   “Monitor recent changes in [regulatory area—e.g., ESG, anti-money laundering, data privacy, tax or industry-specific rules] and summarize how these might impact current and future deals for [firm name]. Include:

   • Regulatory updates: new laws, amendments, enforcement actions, or guidance from bodies like the SEC, FCA, or equivalents in target jurisdictions.

   • Compliance & transaction impact: implications for deal structures, timelines, disclosures, reporting standards, and licensing.

   • Cross-border issues: foreign jurisdiction regulations, tax treaties, FX controls, trade restrictions or national security reviews (e.g., CFIUS).

   • ESG and sustainability metrics: upcoming requirements (EU’s CSRD, SFDR, etc.), potential stranded assets, greenwashing risks.

   • Anti-money laundering / KYC: new thresholds, ultimate beneficial owner rules, sanctions screening, eKYC practices, and KYB/KYCC considerations.

   • Data privacy & cybersecurity: implications of GDPR/CCPA and required breach-disclosure standards or controls.

   • Best practice suggestions: recommended policy updates, process checkpoints, external advisor touchpoints, and cultural training.

   • Deal review checklist: structure a checklist by regulatory area, noting status (e.g., “Pending review,” “Clear,” or “Flagged”), who’s accountable, and next steps.

   Also, flag any industry-specific or upcoming rule changes that could present material exposure or opportunity—complete with suggested mitigation or deal strategies.”

AI is not here to replace the sharp minds or the legendary negotiating skills that made investment banking famous. But it is here to give every partner and executive a new set of tools: think of it as an upgrade from the Excel spreadsheet to the Tesla Roadster of analysis. The firms that embrace AI will find themselves outpacing the competition and freeing up precious time for higher-value work. Either way, in a world where deals are moving faster and clients expect more, it’s not a question of if you’ll use AI, but how soon you can start.