AI has been reshaping how investment banking professionals work for years, and a growing number now say it helps them sharpen their judgment and improve results. About 75% of investment banking (IB) leaders say AI helps them make better decisions, according to our proprietary 2026 AlphaSense State of AI for Business and Finance survey. That’s the highest share of any business and finance industry surveyed among those in corporate strategy, asset management, hedge funds, corporate finance, consulting, and more.
Investment banking teams need tools that elevate speed and accuracy, while giving them access to robust data and content to win mandates and close deals. While day-to-day work has typically entailed spending long, tedious hours developing pitchbooks and Excel models, AI is transforming those workflows.
IB teams still produce the same deliverables, but they now get significant help from AI. Today’s tools can handle complex tasks IB teams grapple with daily, from Excel modeling to company research to pitchbook development. Consider a sell-side M&A process from start to finish: sector research, the pitchbook, the buyer universe, process materials, and diligence through to close. AI can support each stage, and each stage feeds the next, so work done early carries forward instead of being redone.
Below, we discuss the main ways IB teams use end-to-end AI workflows, like those on the AlphaSense platform, to improve and streamline their work. We also cover the benefits and limitations of AI in investment banking.
Use Cases of AI in Investment Banking
Industry Primers and Buyer Universe
When bankers need to get up to speed quickly on a specific industry they’re exploring for a deal, AlphaSense is a one-stop shop for gathering ground-level intelligence and market-relevant information to produce differentiated industry narratives and buyer universes. AlphaSense’s SuperAnalyst can surface a complete view in seconds, with a deep analysis covering competitive positioning, M&A comps, recent funding activity, industry trends, and expert perspectives. IB teams can use SuperAnalyst to produce a number of workflows such as M&A Landscape, Company Primer, and Buyer Universe Development to build the sector view and identify likely buyers.
One-Stop Pitchbook Creation
Investment banking teams work feverishly across internal PDFs, PowerPoint decks, and Excel models to build the story that wins the mandate. This work is very manual and time-consuming. With AlphaSense’s suite of slide creation tools, featuring a native PowerPoint add-in, this work can now be done in a fraction of the time.
Research and synthesis is compressed into one end-to-end workflow, allowing users to generate, edit, and modify full slide decks, financial models and reports all while they research. Decks can be stress-tested against AlphaSense’s exclusive broker research, expert commentary, earnings transcripts, and company financials, as well as a firm’s own internal documents, and then formatted to the firm’s bespoke brand. These slides can also be linked directly to Excel models so they can update automatically when assumptions change.
Accelerate Model Building and Valuation Analysis
Excel models are critical for evaluating corporate valuations, mergers, and transaction structures. These models are complex and can take many hours to build. With tools like AlphaSense’s Work Products, a heavy lift becomes a prompt. IB teams can build peer or transaction comps, benchmark their model’s assumptions against consensus, and trace every number back to a filing, transcript, or broker note in AlphaSense, so the model is both faster to build and easier to defend.
Lightning-Fast Client Meeting Prep
IB teams are often pulled into client meetings that require them to get up to speed quickly on a particular company or industry. AI can condense hours of meeting preparation into minutes, enabling teams to vet questions and drive strategic conversations with confidence. With AlphaSense’s SuperAnalyst, bankers can surface C-suite strategic priorities and identify business risks within minutes. SuperAnalyst can also build a public information book for a specific company and feature financials, analyst views and investor sentiment, industry comps, and recent M&A activity.
Capitalize on Proprietary Intelligence
A successful pitch often relies on proprietary intelligence that is built into previous deal decks, buyer lists, and confidential information memorandums (CIMs). However, most enterprise platforms struggle to locate and re-purpose that intelligence on a new opportunity.
IB teams can seamlessly capitalize on this valuable level of internal insight by searching their proprietary documents using AlphaSense, so the work that won one mandate informs the next. On top of that, SuperAnalyst works across deal notes, pitchbooks, PDFs, and CIMs, alongside AlphaSense’s exclusive content sets in one unified platform.
In practice, that can mean pulling the buyer list and valuation framing from a comparable sale process into a new pitch. Bankers can now carry insights from prior transactions into pitchbooks, memos, and updates more easily than ever with these tools, driving higher client impact.
Related Reading: Top AI Use Cases for Investment Banking
Benefits of Using AI in Investment Banking
Time Savings
Productivity is the most common measure of AI value, tracked by 46% of respondents in the AlphaSense survey of business and finance professionals. By building pitch decks and Excel models, AI saves junior staff time and frees them for higher-value work like deal strategy and meeting prep. By automating routine administrative tasks, AI acts as a massive productivity multiplier.
Better Decision-Making
Of all respondents across the business and finance industry, 60% say AI helps them make better decisions. Tools like AlphaSense give professionals the insights they need by synthesizing vast amounts of unstructured data into actionable intelligence and providing real-time risk assessments that were previously too labor-intensive to produce. Rather than replacing human judgment, these tools are increasingly used to elevate work.
Identifying Risks Earlier
As AI has evolved from single-turn chatbots to agentic systems, deal teams can catch issues earlier in a process. AI agents can surface gaps and risks across diligence materials and outside research, so teams can address them before they affect valuation or timing.
Watch our exclusive webinar on what AI agents mean for investment decisions.
Uncovering Insights
About 84% of respondents in the AlphaSense survey say AI surfaces an insight they would not have found otherwise at least weekly. AI allows banking teams to turn fragmented information into unified insights that were previously too dense or disorganized to analyze effectively. By identifying patterns and market relationships in datasets that a traditional analysis might miss, AI enables teams to surface non-obvious buyers, precedent transactions, and sector themes.
Limitations: Where Human Judgment Still Matters
For a good deal of AI output, human effort is still essential. According to survey results, 79% of AI users across platforms verify its output always or often. AI is best at drafting, structuring, surfacing, and updating. Yet bankers still own positioning, judgment, and final sign-off.
For the same reasons a banker wouldn’t send a junior analyst’s deck to a client without checking it first, teams need to establish a level of trust with general-purpose AI output. The final investment judgments, portfolio decisions, and fiduciary responsibilities are expected to remain within the domain of human professionals for the foreseeable future. While AI supports faster and more accurate processes, human accountability remains essential for strong outcomes.
Gain the Competitive Edge in Your Next Pitch
Pitches are won on speed, insight, and numbers that hold up under scrutiny. AI takes on the first drafts, searches, and updates that fill a deal team’s day, from the first buyer list to the last diligence request, so bankers can spend more time on positioning, judgment, and the client. Every figure AlphaSense’s AI pulls traces back to a filing, transcript, or broker note, and when you integrate your internal knowledge with the AlphaSense platform, the work that won your last mandate informs the next one.
See how AlphaSense’s decision-grade AI works on your next pitch. Start your free trial today.
