Why Finance Leaders Should Embrace AI as a Strategic Advantage, Not a Threat

Artificial intelligence is reshaping how capital markets consume financial information—and it’s coming for the preparation side next. That was the clear message from Kris Bennatti, CEO and co-founder of Hudson Labs, in her keynote at a recent virtual conference for financial executives.

Speaking not only as a technologist, but as an ex-CPA and former KPMG auditor, Bennatti offered a unique vantage point: AI is not just for engineers and venture capitalists. It’s here to solve real problems for finance professionals—reporting overload, talent shortages, and inefficiencies in stakeholder communication.

“We need AI more than most industries,” Bennatti said. “We’re responsible for capital markets efficiency, dealing with regulatory complexity, and communicating massive volumes of information—often with too few people and too little time.”

The End of Structure-as-We-Know-It

One of the more provocative claims in her talk? “XBRL is dead.” Not because standardization has failed, but because it’s no longer the only—or even best—way for machines to understand financial disclosures.

Thanks to rapid advances in vision-language models, Bennatti explained, modern AI can extract data and context directly from unstructured formats: PDFs, images, call transcripts. The new generation of AI tools doesn’t require rigid templates. Instead, they’re making sense of complex disclosures the way humans do—by interpreting nuance, context, and even voice inflection.

“Structure used to be essential for making data usable. Now, structure matters a lot less. That’s great news. It means you can focus on the message, not the format,” she said.

Investors Are Already Using AI—Are You?

While most finance teams on the call reported they are not yet using generative AI in external reporting, institutional investors are well into adoption. Hudson Labs’ platform, for instance, allows users to track themes such as tariff exposure or evolving AI strategies across earnings calls and filings in seconds.

This kind of fast, nuanced analysis—done without keyword hacks or manual digging—is increasingly shaping investor perception. For finance leaders, that means one thing: consistency matters more than ever. AI is unforgiving when it comes to contradictions in disclosures over time.

Specialized AI Beats General AI

For those who’ve piloted ChatGPT internally and been disappointed, Bennatti had a simple message: “That’s normal.” General-purpose AI models often fall short in enterprise settings because they lack domain context. Finance-specific AI, by contrast, is trained for numeric accuracy, context tagging, and long-document reasoning.

Bennatti argued that building AI tools in-house is likely not viable for most finance teams—unless they’re Google. Instead, executives should look for highly specialized platforms with embedded domain knowledge, strong security protocols, and clear limitations on model training with proprietary data.

“The difference between a useful AI solution and a useless one isn’t just the model. It’s how the data is processed, retrieved, and contextualized,” she said.

Where AI Is Already Delivering ROI

According to Bennatti, the “low-hanging fruit” for finance teams includes:

• Automating extraction of complex disclosures (e.g., going concern warnings or internal control weaknesses).

• Condensing earnings call commentary into peer comparisons.

• Eliminating manual tagging in XBRL.

• Integrating disparate systems using AI for data transformation (e.g., between CRMs, ERP, analytics tools).

She emphasized that AI tools today are not replacements for expertise—but they are powerful accelerators for workflows. “Think of it like Excel,” she said. “It’s not intelligent, but we rely on it every day. AI is like Excel, but with better reasoning.”

A Caution—and a Call to Action

While optimistic, Bennatti offered a caution: much of the AI hype rests on in-sample testing, not real-world use cases. “Scoring high on the bar exam doesn’t mean GPT-4 can be your lawyer,” she quipped. Still, she stressed that limitations don’t negate AI’s value.

For finance executives, the takeaway is clear: AI will reshape how financial information is consumed and prepared. The question is whether your team will drive that change—or scramble to catch up.

“We need to see AI not just as a risk, but as a responsibility. It’s how we keep capital markets fair, transparent, and efficient.”
For more tips for embracing AI, register for FEI’s 2025 Financial Leadership Summit.