Why Rebuilding Your Business First for AI is a Flawed Strategy

There's a common piece of advice floating around about AI implementation: before you can leverage AI, you must redesign your entire operating model. The idea is that AI is so transformative, it requires a complete overhaul of your processes. But here's the unglamorous truth: this advice might sound wise, yet it often leads to unnecessary complications.

The Myth of the Complete Overhaul

Many executives are captivated by the idea of a sweeping transformation. It's appealing to think that by reworking everything, the value of AI will automatically follow. However, I've seen this movie before. The reality is that changing an operating model means changing people, and people are the slowest component of any business.

Start Small to See Real Value

In my experience with building a data platform, we did not rebuild the business first. We began with a few essential data models that addressed genuine needs. This approach allowed us to ship something of immediate value without requiring a complete reorganization. Decisions happened faster, and new questions emerged because they were suddenly answerable.

When Incremental Change Works

Incremental changes are effective when each step has standalone value. In contrast, a wholesale change is necessary only when there's no payoff until the entire system is upended. Most projects sold as needing total transformation fail this test.

"Innovation is not about saying yes to everything. It's about saying NO to all but the most crucial features." — Steve Jobs

The Pitfalls of Bundled Change

Bundling all changes into one massive project often leads to failure. In a previous role, we were pitched a cloud migration that included everything—both modern and legacy platforms. Predictably, the scope was unmanageable, and the timeline blew up. This was a technical migration, where the scope was at least knowable. But when you apply this strategy to how people work, it becomes infinitely more complex and fraught with risk.

The Real Incentives Behind "Total Transformation"

The push for a complete overhaul often comes from parties that stand to benefit financially. A redesign is the largest engagement possible, billing more and lasting longer. But the people proposing it are rarely the ones dealing with the stalled reorg and AI pilot phase that never quite delivers.

What's the Smarter Approach?

The question isn't whether AI will change your business—it most likely will. The real question is whether that change can follow from things that are demonstrably working. Start by shipping something small and real. Let it show value, and let the operating model adapt around what works. The transformation will still happen, but it will be based on evidence, not assumptions.

Key Takeaways

• Rebuilding your business for AI before seeing any value is often a mistake.
• Incremental changes can provide immediate value without massive disruptions.
• Understand the incentives behind "total transformation" pitches.
• Focus on small, real projects that show value first.

Frequently Asked Questions

1. Why is starting small with AI projects beneficial?
   Starting small allows you to see immediate value and adapt your business processes around what works, rather than betting everything on unproven assumptions.
2. What are the risks of a complete overhaul?
   A complete overhaul can lead to stalled projects, unmet expectations, and wasted resources, especially if the scope is unmanageable.
3. How can I identify if my business needs a full transformation?
   Assess if each step in your process has standalone value. If incremental changes can deliver value, a full transformation may not be necessary.
4. Who benefits from a "total transformation" strategy?
   The parties proposing it often benefit the most, as these engagements are larger and more lucrative.