The Wake-Up Call
We need to have an uncomfortable conversation about your "successful" Pilot.
You gathered a small team. You subscribed to an LLM API. You built a chatbot that summarizes PDFs or writes marketing copy. It worked. Everyone clapped at the demo day. And then… silence.
Three months later, that project is sitting in what I call "POC Purgatory." It hasn’t scaled. It isn’t impacting your P&L. It’s just a cool toy collecting digital dust.
You are not alone in this. Gartner recently predicted that at least 30% of Generative AI projects will be abandoned after proof of concept by the end of 2025. In my view, that number is optimistic. When I look at the broader market, the functional failure rate—where a project technically "works" but delivers zero business value—is closer to 80% or 90%.
The industry is currently drunk on the possibility of AI, but it is starving for the profitability of AI.
Here is the cold reality: A successful demo is not a business strategy. If your AI initiative doesn't have a direct line to revenue, cost reduction (EBIT), or competitive velocity, it is not an investment. It is a hobby. And in this economy, you cannot afford expensive hobbies.
The Interpretation
Why is this happening? Why are smart companies with brilliant engineers failing to cross the chasm from "cool demo" to "enterprise deployment"?
In my 25+ years in the tech trenches, and now leading First AI Movers, I have seen this pattern before. We saw it with Cloud. We saw it with Big Data. Now, we are seeing it with GenAI, but at a much faster velocity.
The problem is not the technology. The models are capable. The problem is the "shiny object" syndrome.
I recently polled my partners, asking what their biggest barrier to scaling AI was. The answers weren't about "GPU shortages" or "context windows." They were about governance, integration, and workflow.
Most companies are trying to bolt a Ferrari engine onto a horse cart. They have high-speed AI models (the engine) trying to fit into legacy workflows, unstructured data swamps, and terrified organizational cultures (the horse cart).
When I look at a failed POC, I usually see three root causes:
No "Why": The project started with "We need to use AI," not "We need to solve Problem X."
Data Chaos: The AI is hallucinating because the underlying proprietary data is a mess.
The "Human in the Loop" Failure: The leadership assumed the AI would replace the human, rather than augment the expert.
As I often share in the newsletter to 5,000+ AI leaders: Automation without optimization magnifies inefficiency.
What High Performers Do
So, how do you escape POC Purgatory? How do you join the top 10% of companies that are actually generating value?
You need to stop acting like a startup running an experiment and start acting like an enterprise building an asset. Here is the protocol I use with my private clients:
The "Boring" Audit: Before you write a line of code, you must audit your workflow. Where is the friction? Where is the redundancy? AI is a force multiplier. If you multiply zero, you get zero. We focus on the unsexy work of cleaning data pipelines and defining standard operating procedures (SOPs) first.
The "Day 2" Mindset: Most teams plan for "Day 1" (The Launch). High performers plan for "Day 2" (Maintenance, Drift, and Governance). Who owns the model when it starts hallucinating? Who updates the vector database? If you don't have a "Day 2" owner, do not launch.
Solve for the "Last Mile": An LLM gives you 80% of the answer instantly. That’s the easy part. The value lives in the Last Mile—the integration of that answer into your ERP, CRM, or decision-making process. Your focus should not be on prompting; it should be on engineering the hand-off between the AI and your human experts.
The Essence: True innovation requires the courage to be boring. It requires the discipline to say "no" to a flashy chatbot so you can say "yes" to a predictive supply chain model that actually saves 15% on logistics.
Why I Focus on the "Boring Stuff"
I’ll be honest with you: The protocol I just outlined is hard.
It is much easier to hire a junior developer to wrap an OpenAI key in a Python script and call it a "solution." It is much harder to restructure your data governance, retrain your workforce, and redesign your business processes to truly accommodate AI.
But the "hard way" is the only way that works.
I didn't build First AI Movers or spend two decades in this industry just to help companies build toys. I built this advisory practice because I saw brilliant leaders getting burned by the hype cycle. I saw a gap between technological capability and business reality.
My firm exists to close that gap. We don't just deploy technology; we design the governance, the strategy, and the human workflows that make the technology stick. We do the heavy lifting that ensures you aren't just "doing AI," but are transforming your business with it.
The era of "playing with AI" is over. We are entering the era of AI Utility.
You have a choice. You can keep building POCs that look great in a slide deck but fail in the real world. Or, you can decide to do the hard work required to build a lasting competitive advantage.
Are you ready to transform your business?
If you are feeling frustrated that no one gets your vision, or if you are tired of burning cash on projects that don't scale, let's talk.
Let’s do this. Together.
Dr. Hernani Costa Founder at First AI Movers