Now Important: Making Board Disclosures AI Legible

This is groundbreaking stuff from Labrador’s Iain Poole and Nicole Victoria! Now that AI is playing a bigger and bigger role in reading your disclosures, it’s time for us to learn how to best craft disclosure so it can be read by this new important player. Register now for the complimentary September 9th webcast about this topic with Iain and Jenn Cooney.

Here’s an excerpt from this Labrador explanation of this 13-page “Thought Piece,” complete with useful examples of the changes necessary to effectuate this change:

“Your investors are still reading your disclosures. But increasingly, so is an AI model, deployed by an institutional investor, a proxy advisor, or an analyst, to parse your governance disclosures to find the same answers sought by the human readers.

This rapid evolution in your readers led us to ask, “if a human can read a page and understand it in seconds, can a machine do the same”? We started to find answers in 2022, when we first piloted AI to accelerate our analysis of disclosures for the Transparency Awards.

That work taught us a lot, not just about what AI is remarkably good at extracting from a well-built document, but also about what it misses and why. Icons with no accompanying text. Charts with data trapped inside an image. Skill matrices that a human eye reads instantly but a machine can’t parse.

We now have incorporated what we learned into our advisory practice and the design system we use on every engagement. Today, when we help a client prepare disclosure, we’re thinking about the human reader and the algorithm running in the background. The goal is the same content and design telling the same story clearly to both.

That’s what this Thought Piece is about. In the following examples, we are sharing some of the practical, specific things we’ve learned, the kind of tips you can easily apply to board and governance disclosures in your next proxy statement to make them visually compelling and machine-readable. Every idea proposed here is something we build into our own project processes and is EDGAR compatible.”

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