According to Gartner's report, over 40% of organizations in banking and investment services will use AI agents to automate workflows and enhance decision-making.
For those following the space closely, this isn't surprising. They see that it's already happening.
This week, Auquan was named a Cool Vendor in Gartner's report on Agentic AI for Banking and Investment Services. While we're honored by the recognition, what matters more is what it signals: the era of AI assistants is giving way to the era of AI agents.
And that shift changes everything.
Most AI tools in finance today serve as assistants. They help you draft an email. They summarize a document. They answer questions.
AI agents are radically different. They complete entire workflows autonomously, from data gathering through structured, audit-ready outputs.
Using AI Assistants:
A credit analyst uploads a borrower's financials and asks the AI to summarize cash flow trends. The tool provides bullet points. The analyst then manually pulls comparable company data, checks covenants, and inputs that information into the tool. The AI then drafts a memo, and the analyst revises and formats it for the investment committee.
Using AI Agents:
The analyst assigns the workflow to an AI agent. The agent autonomously gathers borrower data, pulls relevant market comparables, analyzes covenant compliance, drafts a complete credit memo with citations, and delivers an IC-ready document in the style and format the IC committee expects. The analyst focuses on higher-value work and gets started on analyzing another company faster.
One approach saves an hour or two off the analyst's day. The other saves them 10 hours and dramatically reduces the risk of manual error.
Finance has zero tolerance for error. Well-designed and built AI agents deliver deterministic calculations, verified facts with full citations, and audit trails that meet institutional standards. That's why leading institutions are moving from pilots to production.
Generic AI tools struggle with finance because finance is regulated, has low error tolerance, and is unforgiving.
Investment committees don't accept "approximately 12% IRR." They need precise calculations with a transparent methodology.
LPs don't accept "generally compliant with industry standards." They need documented evidence mapped to specific frameworks.
Regulators don't accept "AI said so." They need audit trails showing exactly how conclusions were reached.
AI agents that are purpose-built for these requirements understand how to structure an IC memo. They know what covenants matter in a credit agreement. They can verify sustainability data against multiple disclosure frameworks. They deliver what LP reporting templates require.
This domain specificity is why Gartner's recognition matters. Their report doesn't highlight general-purpose AI tools. It recognizes emerging players redefining how institutions handle mission-critical workflows, specifically in banking and investment services.
Firms adopting AI agents aren't doing it to replace people. They're doing it to unleash them.
When brilliant finance professionals spend their days manually processing data and formatting reports, they're not driving results that matter for the firm.
One of our customers, a partner at a firm managing over $100 billion, put it simply: "We're evaluating three times as many deals without adding headcount. Our team finally has time for the strategic work that drives returns."
Another customer in credit monitoring told us: "We used to spend 80% of our time gathering data and 20% analyzing it. Now it's reversed. The agents handle the data work. We focus on generating returns."
This is the future Gartner is seeing. It's not just about efficiency. It's about outperformance and competitiveness.
When brilliant minds spend less time on manual work and more time on strategic high-value work, better outcomes follow. More deals evaluated. Better risk management. Faster response to market changes. Stronger returns.
Gartner's 40% adoption prediction for 2027 might actually be conservative.
The institutions moving first are seeing such dramatic outcomes that competitive pressure will drive broader adoption faster. If your competitors are evaluating 3x more deals with the same team size, you can't afford to stick with what worked yesterday.
At Auquan, we're building for that future.
→ New agents launching for credit, risk, sustainability, and reconciliation
→ Deeper integrations with the data systems institutions already use
→ More sophisticated reasoning capabilities for complex edge cases
But technology is only part of the story. The bigger shift is cultural: finance teams learning to delegate entire workflows to AI, not just individual tasks.
The teams making that shift now will have a decisive competitive advantage.
Being named a Gartner Cool Vendor validates what our customers already know: finance doesn't run on AI prompts. It runs on finished work.
The question isn't whether AI agents will transform institutional finance. Gartner says they will. Our customers prove they already are.