We recently came across a theoretical confirmation of something we’ve experienced in practice for years. The latest study by MIT’s NANDA Project, The GenAI Divide: State of AI in Business 2025, echoes a message we consistently emphasize to our clients: organizations can only truly benefit from the AI boom if they first prepare themselves for change.
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The Four Gaps Separating AI Hype from Reality
According to the study, most enterprises are experimenting with generative AI (GenAI), but meaningful transformation remains rare. The reasons are primarily structural, not technical. The “GenAI Divide” shows up in four consistent patterns observed across industries:
- Limited disruption: Only 2 out of 8 major sectors show meaningful structural change.
- Enterprise paradox: Large firms lead in pilot volume but struggle to scale.
- Investment bias: Budgets skew toward sales and marketing, even though back-office automation delivers better ROI.
- Implementation advantage: Projects developed with external partners are twice as likely to succeed compared to internal builds.
These observations feel very familiar. At Peakstride, we frequently encounter situations where an AI solution is expected to “land” in an organization that isn’t structurally ready — workflows are fragile, processes are overly person-dependent, and there’s little room for contextual learning. These conditions alone can prevent even the most advanced models from delivering value.
Why We Don’t Start with AI — And Never Recommend It Just Because It’s Trendy
This is exactly why our approach is different. We don’t assume a specific technological solution from the outset — and certainly not AI just because it’s currently in vogue. Instead, we begin by developing a deep understanding of how the organization actually operates: how people work, what kinds of decisions they make on a daily basis, where the friction points are, and where the real opportunities for improvement lie.
Based on those insights, we recommend the most effective interventions — whether that’s organizational redesign, process improvements, or yes, a well-integrated technological solution. AI becomes part of the conversation only if and when it proves to be the right tool for the job — in sustainable, practical, and effective ways.
Visibility ≠ Value: The Real ROI Is Often Behind the Scenes
The MIT study also highlights a striking paradox: while most GenAI budgets are funneled into visible, top-line use cases (like content generation or customer-facing chatbots), the areas where AI can deliver the highest returns — internal operations, logistics, or decision support — are consistently underfunded.
In the retail networks we see enormous untapped potential in areas from shop deployment process optimization, to automation of data flow, and predictive maintenance. These are not glamorous, but they are foundational — and when improved through the right combination of process thinking and technology, they deliver clear, measurable results.
In Conclusion
The Winners Will Be the Realists, Not the Magicians
GenAI isn’t plug-and-play. It’s not a quick win. It’s a complex business and operational question that requires a systems mindset. The key isn’t whether you’re using AI, but how, where, and why you’re using it — and the true competitive edge lies in the answers of these questions.
Is your organization truly ready for AI? Technology alone won’t solve your deepest challenges. If you want to know how to build a robust foundation for sustainable growth and a future powered by smarter operations, we’re here to help.
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