Preql

?? 75% of CFOs are now being asked to lead or co-lead data strategy. That stat came from a Gartner analyst Gabi Steele spoke with this month, and it represents a big shift. CFOs are no longer just financial stewards; They are shaping how businesses use AI and data to drive efficiency. On this week's episode of The Growth-Minded CFO Podcast, Gabi explained the order of operations for CFOs investing in AI. ?? Step 1: Get your data house in order. What data actually matters? What doesn’t? Most companies are drowning in data they don’t need, which makes it harder to find insights that drive real business impact. ?? Step 2: Automate manual workflows. It is not just about cutting costs or reducing headcount. It is about making sure your best people are working on the right problems. What if you could recover 75% of your analysts’ time to do thinking work instead of validation work? AI is not here to replace CFOs; It is here to amplify them. The biggest problems you had before AI are _still_ your biggest problems. The difference now is that you have better tools to solve them. >> How your finance team is thinking about AI adoption? Catch all of Gabi’s insights on this week’s episode of The Growth-Minded CFO Podcast by Upflow with my fabulous cohost Alex Louisy! I'll share the links in the comments, or search "The Growth-Minded CFO" on Apple, Spotify, or YouTube to hear the full discussion! ___ ?? Hi, I’m Lauren. A 3x Founder-turned-CFO nerd who writes about building better companies. ?? Enjoy this content? FOLLOW for more! ?? Want my newsletter? SUBSCRIBE (link in profile).

Somewhere along the way, the conversation around generative AI got caught up in the excitement and lost sight of a fundamental truth: AI is not magic. It wasn’t invented yesterday. And it won’t work without structure and high-quality data. A few years ago, we were obsessed with big data—how to manage it, clean it, and extract insights. But now? Too many companies are skipping straight to AI and are in a hurry to buy anything with an AI label on it without addressing the data foundations needed to make it work. I recently spoke with Gabi Steele, Co-Founder & CEO of Preql, on The Growth-Minded CFO Podcast together with Lauren (Link to the full episode in the comments). Her take? Finance leaders must “earn the right” to use AI—by first investing in data governance and infrastructure. The biggest challenge? Achieving a single source of truth in financial data. Right now, finance teams are drowning in fragmented, inconsistent, and siloed data. Which means? Even the most advanced AI tools will generate unreliable insights. ?? Without a strong data strategy, AI isn't an asset. ?? It's a liability. As Gabi put it: "Budgets are going towards AI and away from data... That is a backward approach—your AI will only ever be as good as your data." Before chasing the latest AI trend, finance leaders must take ownership of: ? Data quality ? Standardization ? Accessibility Only then can AI truly enhance decision-making—turning raw data into a competitive advantage instead of a costly mistake. Are you seeing this same disconnect in your organization?

In our latest episode, we sat down with Gabi Steele (Co-Founder and CEO of Preql and Ex-WeWork Head of Data Visualization Engineering) to talk about one of the biggest challenges for finance leaders today: ??♀? How to get ready for the new era of AI. Gabi shared incredible insights on: ? How CFOs should approach AI investments – Start by focusing on the right data, cleaning it up, and then layering on automation. The goal? Freeing up analysts to do more thinking, not just validation. ? Why data siloes don’t work – Too often, data teams are disconnected from the business. The best results happen when finance leaders bring data teams into the decision-making process and use tools that support both business needs and advanced technical workflows. ? The power of multidisciplinary teams – Success doesn’t come from decentralizing data teams but from hiring people with diverse skill sets. A great tip from Gabi: If you see SQL or data infrastructure experience on a resume—even for a non-data role—take note. It could bring a whole new dimension to how your team operates. The key takeaway? AI and data strategy aren’t just technical challenges. They’re business challenges. And you need the right foundation in place. Check it out below?? (and subscribe to our 'New This Week' newsletter right here on LinkedIn to get a quick, digestible summary of every episode as soon as it drops).

In our latest episode, we sat down with Gabi Steele (Co-Founder and CEO of Preql and Ex-WeWork Head of Data Visualization Engineering) to talk about one of the biggest challenges for finance leaders today: ??♀? How to get ready for the new era of AI. Gabi shared incredible insights on: ? How CFOs should approach AI investments – Start by focusing on the right data, cleaning it up, and then layering on automation. The goal? Freeing up analysts to do more thinking, not just validation. ? Why data siloes don’t work – Too often, data teams are disconnected from the business. The best results happen when finance leaders bring data teams into the decision-making process and use tools that support both business needs and advanced technical workflows. ? The power of multidisciplinary teams – Success doesn’t come from decentralizing data teams but from hiring people with diverse skill sets. A great tip from Gabi: If you see SQL or data infrastructure experience on a resume—even for a non-data role—take note. It could bring a whole new dimension to how your team operates. The key takeaway? AI and data strategy aren’t just technical challenges. They’re business challenges. And you need the right foundation in place. Check it out below?? (and subscribe to our 'New This Week' newsletter right here on LinkedIn to get a quick, digestible summary of every episode as soon as it drops).

In our latest episode, we sat down with Gabi Steele (Co-Founder and CEO of Preql and Ex-WeWork Head of Data Visualization Engineering) to talk about one of the biggest challenges for finance leaders today: ??♀? How to get ready for the new era of AI. Gabi shared incredible insights on: ? How CFOs should approach AI investments – Start by focusing on the right data, cleaning it up, and then layering on automation. The goal? Freeing up analysts to do more thinking, not just validation. ? Why data siloes don’t work – Too often, data teams are disconnected from the business. The best results happen when finance leaders bring data teams into the decision-making process and use tools that support both business needs and advanced technical workflows. ? The power of multidisciplinary teams – Success doesn’t come from decentralizing data teams but from hiring people with diverse skill sets. A great tip from Gabi: If you see SQL or data infrastructure experience on a resume—even for a non-data role—take note. It could bring a whole new dimension to how your team operates. The key takeaway? AI and data strategy aren’t just technical challenges. They’re business challenges. And you need the right foundation in place. Check it out below?? (and subscribe to our 'New This Week' newsletter right here on LinkedIn to get a quick, digestible summary of every episode as soon as it drops).

Who's my mentor? What's my favorite part of the startup journey? Who makes the impossible feel possible? Leah Weiss, every single time! Building data companies from scratch comes with its share of challenges, but having someone in your corner who's always a voice of reason, wisdom, support and friendship makes all the difference. Thank you for being that person, Leah and continuing to show up every day for all of us in every way. Happiest birthday to my co-founder, co-CEO and partner in all things! ?? Here's to another year of building, learning, and transforming challenges into opportunities together :)