Click here for original Interview or Mind Map from our conversation with Armando Gonzalez.
Q1: Why does data matter so much for AI in finance?
AI models are only as good as the data they consume. In finance, poor inputs can destroy credibility or lead to flawed investment assumptions. As Armando Gonzalez puts it: “There is no AI without data.” Trusted, curated, and auditable data sources are the foundation for making AI outputs reliable.
Q2: How do investment firms measure whether an AI tool is successful?
AI products survive only if they clearly generate alpha, reduce risk, or lower costs. Vendors must prove exponential ROI—often 5–10x—because firms incur opportunity costs when allocating scarce analyst and engineering resources. Renewal cycles, not initial contracts, are the ultimate test of value.
Q3: What risks come from using generic or poorly curated AI outputs?
Outputs that “look right” but rely on inaccurate data can derail investment decisions. For example, a polished AI-generated report on crypto valuations contained nine out of ten materially wrong figures. Without audit trails, firms risk not just money but their reputations with clients and compliance teams.
Q4: How do professionals ensure AI outputs are auditable and trustworthy?
Firms demand traceability—knowing exactly which sources fed an AI’s conclusion. This involves whitelisting publishers, ranking sources for bias and reliability, and maintaining an audit trail. For asset managers, this isn’t just about accuracy—it’s about credibility with clients and regulators.
Q5: What role does customization play in using AI for investments?
Asset managers want control. They may prefer one earnings call provider over another or want their own rankings of data sources. Platforms like Bigdata.com enable “bring your own license” integration and deliver standardized, AI-ready outputs across different providers.
Q6: What is the value of a knowledge graph in this context?
Entity resolution is essential. Knowledge graphs map securities, subsidiaries, and products into consistent identifiers, so when an analyst queries “Meta,” the system automatically connects to Meta Platforms and its business units. This removes ambiguity and accelerates investment research.
Q7: How do asset managers and vendors think about monetization?
Subscription models dominate. One or two good trades can justify the fee, making renewals the best indicator of lasting value. Pay-per-click or per-document models fail because AI systems are optimized to minimize those transactions.
Q8: Why is compliance such a critical factor in AI adoption?
One compliance violation can be more damaging than years of strong returns. As a result, adoption is often paced by compliance teams rather than PMs. Vendors that deliver AI in compliance-friendly formats—transparent, auditable, and source-controlled—earn greater trust and traction.
Q9: How are professional skills evolving with AI?
Just as Excel skills once opened doors in finance, prompting skills are now becoming a baseline expectation. Increasingly, it matters less whether someone can code, and more whether they can effectively direct an AI to produce usable outputs.
Q10: Should firms build or buy AI infrastructure?
The trend is shifting toward “buy for speed, build for compliance.” Post–ChatGPT, many firms initially tried building their own stacks, but the pace of obsolescence and rising costs have pushed them toward vendor solutions. Internal builds are now reserved for compliance, IP, and security-sensitive use cases.
Q11: Who gains adoption advantages—large or small firms?
Smaller, more agile firms can onboard new data and test strategies faster, often cutting cycles from years to weeks. Larger firms have resources and behind-the-firewall data, but they risk losing share to nimbler competitors if slowed by compliance and bureaucracy.
Disclaimer: The information contained in this newsletter is intended for educational purposes only and should not be construed as financial advice. Please consult with a qualified financial advisor before making any investment decisions. Additionally, please note that we at AInvestor may or may not have a position in any of the companies mentioned herein. This is not a recommendation to buy or sell any security. The information contained herein is presented in good faith on a best efforts basis