Let's not sugar-coat it.
If your AI pilot went well, there's a good chance it's headed straight for the scrapheap.
Gartner just made it official: by the end of 2025, 30% of generative AI projects that prove successful in pilot will be abandoned before reaching production. Not because the tech didn't work—but because the business wasn't ready.
You don't need better AI.
You need a better plan for what comes next.
Successful AI pilots are designed to prove the art of the possible—not the rigour of the real.
They're built on:
But once the pilot ends, reality begins.
Suddenly you're facing:
That's not a technical problem.
It's a framework problem.
HFS Research coined the term "GenAI Pilot Purgatory" to describe this exact scenario:
Where innovation gets stuck between validation and value.
The technology works—but the business isn't built to scale it.
We've seen this play out in both public and private sectors. Pilots get board-level airtime, but when it's time to integrate with mission-critical systems, the gaps appear. AI initiatives are derailed not by model drift, but by organisational friction.
McKinsey summed it up well:
"Business leaders face increasing pressure to generate ROI from their GenAI deployments.
And that pressure is real. Especially when every other line item in your budget is being challenged.
Here's the common failure pattern we see:
Launch a pilot to test a use case
Celebrate early success
Attempt a scale-up without foundational readiness
Hit resistance across governance, integration, and adoption
Quietly abandon the effort—or delay indefinitely
It's the equivalent of building a show home before securing zoning approval.
If you're solving for tech first, you're solving the wrong problem.
At LuminateCX, we built Ignite to help organisations avoid exactly this scenario.
Ignite is not about improving your pilot.
It's about creating the strategic conditions that allow pilots to scale—with confidence.
Here's how we do it:
We don't rely on success theatre. We analyse your actual architecture, governance readiness, data posture, and stakeholder alignment—across systems, silos, and scenarios.
That means:
This isn't about use cases. It's about use value.
We develop a structured approach to:
The goal isn't to get AI into production—it's to keep it in production and deliver meaningful returns.
Not a tech wishlist. A pragmatic, sequenced pathway from now to next, with clear ownership, executive sponsorship, and milestones that withstand internal scrutiny.
AI success isn't about picking the right tool—it's about building the right conditions for scale.
We've seen the pattern across sectors—whether it's a government agency piloting language models for service delivery, or a national insurer testing claims automation. The tools work in isolation. The frameworks often don't exist.
And while few organisations have mastered AI at scale, the red flags show up early:
At LuminateCX, our team have spent their careers guiding clients through complex digital transformations—across MarTech, data integration, and cloud migration. While GenAI is newer, the underlying transformation risks are familiar.
We know what it looks like when frameworks are missing—and we know how to build the ones that unlock momentum.
That's how long you have before Gartner's prediction becomes your reality.
Eight months to either:
Before you double down on scaling your AI pilot, take a day to pressure-test your readiness.
Book a Spark Session—a structured, advisory-led engagement that identifies the key blockers, risks, and opportunities before you commit capital or credibility to a flawed rollout.
Let's ensure your pilot is the starting line and not the finish.
Book a Spark Session with our team to assess your AI readiness and build a framework for success. Don't let your pilot become another statistic.
Book Your Spark Session"Your AI pilot is working perfectly. That's the problem. The winners in this next wave won't be the ones who prototype the best—but the ones who plan for production from day one."
— Steven Muir-McCarey