InsideOutBox: From AI hype to AI ROI

This blog post is a contribution from a member of our Wantrepreneur to Entrepreneur community. We love spotlighting the brilliance of our guests, speakers, and Growth Partners, because this community only gets stronger when we grow together.

Enjoy this guest perspective from Julie Silvestri from InsideOutBox, and let it spark some ideas (and maybe even some action!) in your own journey.

An MIT report from July found that 95% of organizations see no measurable return on their investment in GenAI. Many AI implementations flounder because companies skip the boring stuff. Here's the measured, ROI-focused approach I’ve learned that provides powerful results:

The Reality Check

We want to increase speed, quality, and scope of what we deliver.

But we also want to invest in something that delivers real ROI — not just mediocre automation that sounds impressive in meetings.

Let me share the 3-step approach that's working for clients we work with.

Step 1: Clean Your Data First (Skip the Flashy Stuff)

The unsexy truth: High-value AI starts with clean, usable data.

We don't mean spending 6 months on a data warehouse project—we mean identifying the one data integration that has your highest-value, fastest-to-market opportunities. 

Real example: For one client, this meant integrating their group email system into our application and creating a proper task management solution (see my prior post). Not glamorous, but it set the foundation for everything that followed.  There was a ton of value gained by this step alone.

Step 2: Find Your Biggest Bottleneck

Ask yourself: Where are you slowest?

Your biggest bottleneck, more often than not, is the AI that you need.  We had originally thought a chatbot would be most helpful, but in this process of making the customer service emails into tasks, we saw order entry from emailed PDFs was eating massive amounts of time. They were constantly behind, which hurt revenue and prevented them from tackling more complex, higher-value customer service work.

That's where we focused our AI efforts.  We enhanced the task management system to automatically create orders from emailed PDFs.

Step 3: Aim for 70-80% Accuracy (Not Perfection)

Here's the key mindset shift:

✅ Let AI handle the busy work

✅ Keep employees focused on complex, high-value tasks 

✅ Expect AI capabilities to grow over time 

❌ Don't demand perfection from day one

The Big Picture: What Success Actually Looks Like

The result? Our client went from drowning in manual data entry to having capacity for strategic customer relationship management. This is where the real transformation happens—not in the AI itself, but in what becomes possible next.

What will your team do with the time AI saves them?

• Where can you and your employees grow?
• How does this improve job satisfaction?
• What higher-value work becomes possible?

We literally heard "oohs" and "OMGs" when our normally straight-faced executives saw what became possible.  And, their sales for the last few months are up nearly 50% YOY – not solely due to AI, but the freed-up capacity made it possible.

What are you interested in using AI for?  What have you tried so far?  I'd love to hear about your wins — and your lessons learned.  Reach out to us at julie@insideoutbox.com