Why High-ROI AI Projects Start With Workflows, Not Models

Brado Greene
Nov 11
2 min read

The Real Differentiator Between AI That Delivers and AI That Disappoints

Summary

A new McKinsey report revealed a defining trait of high-performing AI organizations: they don’t just deploy models, they redesign workflows.While most companies focus on model selection, infrastructure, or headcount, leaders in AI ROI are restructuring how work actually gets done. These organizations integrate AI into decision loops, not just dashboards.

The lesson is clear: AI success isn’t built on sophistication, it’s built on fit. The model matters, but the workflow determines whether value compounds or evaporates.

Key Takeaways

For Business Leaders

The biggest AI ROI driver isn’t the model’s accuracy, it’s how deeply it reshapes everyday workflows.
Stop treating AI as a bolt-on tool. Start treating it as a process re-engineering opportunity.
High-performing firms pair model deployment with redesigning who does what, when, and how.

For Investors

The next growth wave won’t come from more powerful models, it’ll come from AI systems that improve decision velocity and operational flow.
Prioritize startups and vendors embedding AI into core business mechanics, not those chasing model benchmarks.

For Founders

You don’t need a cutting-edge model to compete, you need to align existing ones with the pain points of actual workflows.
Enterprise buyers are no longer impressed by accuracy rates, they want AI that eliminates manual loops, accelerates throughput, and ties directly to margin expansion.

Deep Dive

Want the full analysis?

In the Insider Edition of Insights on AI ROI, I unpack:

Why workflow redesign is the hidden lever separating top-quartile performers from the rest.
How misplaced focus on model performance leads to slow adoption and weak returns.
Real examples of companies rethinking work, not just technology—and seeing 2–5x ROI gains as a result.

👉 Read the full Insider Edition → Access Here