The landscape of capital markets is undergoing a transformative shift, driven by advancements in artificial intelligence. Kris Bennatti, CEO and co-founder of Hudson Labs, emphasized this transformation during her keynote speech at a recent virtual conference for financial executives. Bennatti, with her background as both a technologist and a former CPA and KPMG auditor, highlighted the potential of AI to address pressing challenges faced by finance professionals. These challenges include managing reporting burdens, overcoming talent shortages, and improving stakeholder communication efficiencies. She argued that AI is not just a tool for engineers or venture capitalists but a solution to real-world problems in the finance sector.

Bennatti's presentation was marked by bold assertions about the future of structured data. She proclaimed that XBRL, once considered essential for making data usable, has become outdated due to advancements in vision-language models. Modern AI tools now excel at extracting data and context directly from unstructured formats like PDFs, images, and call transcripts. This capability allows machines to interpret complex disclosures much like humans do, focusing on nuances and contextual details.

Another key point raised by Bennatti was the growing adoption of AI among institutional investors. While many finance teams are yet to embrace generative AI for external reporting, investors are already leveraging specialized platforms to perform rapid, nuanced analyses. This trend underscores the importance of consistency in disclosures over time, as AI systems can quickly identify contradictions. Furthermore, Bennatti distinguished between general-purpose AI models and finance-specific ones, advocating for specialized platforms that offer numeric accuracy, context tagging, and long-document reasoning.

In terms of immediate returns, Bennatti identified several areas where AI could deliver significant benefits. These include automating the extraction of complex disclosures, condensing earnings call commentary into peer comparisons, eliminating manual tagging in XBRL, and integrating disparate systems using AI for data transformation. She emphasized that these tools are not replacements for expertise but rather powerful accelerators for workflows, akin to how Excel revolutionized data management.

While optimistic about AI's potential, Bennatti also issued a cautionary note. Much of the current hype around AI is based on controlled testing environments rather than real-world applications. Despite this, she urged finance executives to view AI not merely as a risk but as a responsibility. By embracing AI, finance professionals can contribute to maintaining fair, transparent, and efficient capital markets. The choice before them is clear: will they lead the change or struggle to keep pace?

As AI continues to evolve, its impact on how financial information is consumed and prepared becomes increasingly profound. Finance leaders who adopt specialized AI solutions stand to gain a competitive edge, enhancing their ability to manage data effectively while ensuring compliance and transparency. The challenge now lies in harnessing these technologies responsibly and strategically to shape the future of capital markets.