Why Most AI Investments Will Look Like ERP Projects by 2028

 

Right now, enterprise AI feels like the iPhone moment. A demo lands, a room gasps, someone signs a budget, and everyone pictures a clean, magical product that just works.

Here's my prediction. By 2028, most of those investments won't be remembered as the iPhone. They'll be remembered as SAP.

If you were in a boardroom in the late 1990s or 2000s, you know exactly what that means, and your stomach probably just dropped. ERP was going to unify the company, kill the silos, and give leadership one version of the truth. Some of it delivered. A lot of it ran years long, cost multiples of the estimate, and ended in a system nobody quite loved and everyone learned to work around. The software was never the hard part. The company was.

AI is walking into the same story. Not because the technology is weak, but because of what always happens when powerful technology meets a large organization: the innovation becomes operations.

Why ERP is the right rhyme, and the iPhone is the wrong one

The iPhone was a product you bought and used. ERP was a program you implemented. That difference is everything.

A product pays off the moment you unbox it. A program only pays off after you've rebuilt your processes, retrained your people, cleaned your data, and rewired how decisions get made. The technology is maybe a fifth of the work. The other four-fifths is organizational surgery.

Enterprise AI is a program, not a product. The chatbot demo is the product. Getting it to actually change how your claims get processed, your contracts get reviewed, or your supply chain gets planned, safely and at scale and with someone accountable, is an implementation. And implementations rhyme. The technology works. The organization doesn't. That was the real story of ERP, and it's about to be the real story of AI.

This isn't even the first time. ERP, then CRM, then cloud, then the data-warehouse wave: each arrived as innovation and left as governance. Salesforce didn't fix bad sales processes; it exposed them. "Lift and shift" to the cloud didn't cut costs until companies rebuilt what they moved. Every wave starts as a breakthrough and matures into an operating-model change. AI is simply reaching that stage faster than anyone expected.

The specific ways it will rhyme

Budgets balloon and timelines slip. The demo cost a rounding error; the deployment will not. Wiring AI into real workflows means data pipelines, access controls, evaluation, monitoring, and endless edge cases the demo never showed. ERP taught us the pilot is the cheap 10%. AI is teaching the same lesson to anyone paying attention.

A consultant economy appears overnight. ERP built Accenture and Deloitte as we know them. The same thing is happening now: the "AI transformation practice" is being staffed as you read this. The irony your CIO will feel personally: after a decade of selling "disruption," they'll end up hiring the exact roles that made ERP work: enterprise architects, business analysts, data stewards, integration specialists, program managers, change managers. The revolution will be delivered by the people who ran the last one.

Customization eats the promise. The pitch is a general model that does everything. The reality is that your data, your compliance rules, and your processes are unlike anyone else's, so every serious deployment becomes a custom build. The gap between "standard package" and "our special requirements" that made ERP balloon is waiting for AI, in the same place.

The value is in the redesign, not the tool. This is the deepest rhyme. ERP only paid off for companies that used it as a reason to simplify how they actually worked. The ones who bolted it onto their existing mess just automated the mess, expensively. AI is merciless about this. Drop it on a broken process and you get a faster broken process. Bad knowledge management becomes bad RAG. Bad documentation becomes confident hallucination. Bad workflows become automated chaos. The model doesn't fix the rot; it scales it. Most of the return will come from the redesign the AI forces, not the AI itself.

And then it becomes table stakes. The part executives least want to hear. ERP stopped being an advantage the moment everyone had it; it went from competitive edge to the cost of staying in business. Enterprise AI is on the same curve, only faster. The general capability you're paying a premium for today will be a commodity your competitors also have by 2028. The advantage was never the software. It was what only you could do with it.

Where the analogy breaks, to be fair

It isn't a perfect match, and I'd be doing bad analysis if I pretended it was.

AI is cheaper to start with, adopts bottom-up before any big program begins, and iterates in weeks where ERP iterated in years. A team can get real value from an off-the-shelf tool tomorrow, with no eighteen-month rollout. That's genuinely different, and it's good.

But that changes the entry, not the endgame. Easy pilots are exactly what will lull companies into underestimating the enterprise-scale version, which is where the ERP dynamics come roaring back. Cheap to start is not the same as cheap to deploy across a regulated, political, legacy-bound organization.

What to actually do with this

If your AI program is being budgeted like a software purchase, it will fail like an ERP project. Budget it as the organizational change it really is. Assume the model is the cheap part and the change management is the expensive part, and staff for that.

Expect the pilot magic to die on contact with the org, and plan for that death instead of being surprised by it. Pick the processes you're genuinely willing to redesign, not the ones you just want to sprinkle AI onto. And stop treating the general capability as your moat, because it won't be one for long. Your moat is your data, your workflow, and the specific redesign a competitor can't copy.

The companies that came out of the ERP era ahead weren't the ones with the biggest implementation. They were the ones who used a painful technology program as an excuse to become a simpler, sharper business.

So the question worth sitting with, before the next AI budget gets signed: are you buying a product, or signing up for an implementation? Because by 2028, almost everyone will discover it was the second one.