FOUNT Global, Inc.

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Deciding how to use AI in your organization can be a complicated process, but even more difficult is trying to validate that big AI investment. A final ROI number may be years down the road. So how can you tell earlier on whether AI is working in the meantime? Our latest post breaks down the tricky business of discerning AI’s impact on things like productivity and efficiency and explains why your workforce – the folks working with those AI tools every day – hold the key to getting an early measure of your project’s potential success. https://lnkd.in/gThsr58W

📬 The March edition of the FOUNT newsletter is now live! This month’s focus: AI transformation only works if it works for employees. Inside this issue: 🟣 Why work friction is becoming a critical metric for AI success 🟣 How to assess whether new tools are helping or hindering daily work 🟣 Guidance on validating AI investments - before traditional ROI metrics surface 🟣 Featured blogs and articles on worker impact, leadership blind spots, and measuring what matters most The takeaway? If you want your AI efforts to succeed, you have to start with the experience of work.

 How is your current AI project performing? What's next on the horizon? If you’re not sure how to answer those questions, we’ve got a new playbook for you. Join the leading edge of transformation leaders who have go-to methods for… 📏 Measuring AI transformation ROI 🛟 Rescuing an ROI-negative AI transformation 📋 Prioritizing future AI transformations 📈 Scaling AI transformations Get the full playbook https://lnkd.in/gyB2y-78

Psst! That new AI tool is going to change more than you think. When you automate some parts of work, the nature of the rest of the work changes. Some of those changes are good. Some are bad. Some are neutral. What they have in common: you can’t predict what they’ll be. Here’s our guide to spotting work changes post-launch and figuring out which ones you need to deal with ⬇️ https://lnkd.in/ezuXAHkx

Enterprise leaders don’t have time for guesswork when it comes to adoption, efficiency, and retention. From AI rollouts that miss the mark to digital transformations that stall, these 9 cases show how global enterprise companies identified and fixed hidden friction. The takeaway? The right data leads to the right solutions. That means 35% attrition improvement in 4 months, $13M in annual savings, 120,000 hours recovered, and more. Swipe through to see what worked. ⬇️

Once you’ve deployed a new AI tool, the real pressure begins. Now you’re on the clock⏰. When will the technology start delivering on its promise of increased productivity or reduced costs? While actual bottom-line results may take a year (or more!) to show, employee adoption and acceptance can be an early indicator of which way your AI investment is likely to go: ⬆️/ ⬇️/ ↔️   Our latest blog post explains how: https://lnkd.in/eAbTknEx

We couldn’t say it better. Lagging vs. Leading Indicators of AI Transformation - rarely discussed but make all the difference. Most transformations hinge on adoption, yet too many rely on lagging indicators - looking back at what happened instead of leading indicators that predict success.

There are 3 types of AI transformations: employee-facing service AI, customer-facing AI, and productivity-improving AI. For all three, you can improve ROI by reducing work friction. #enterpriseAItransformations

With AI investments expected to top $2.5 trillion by 2033, measuring their success has never been more important. But it’s also complicated. In our latest blog post, we lay out the keys to determining how an AI transformation is going, namely: - Knowing how to classify workers - Measuring the impact of AI on work We also take a look at those AI transformations that affect everyone in the organization. https://lnkd.in/eNuxSBHi