This is the second post in our blog series unpacking Silicon Foundry’s full suite of offerings and the thinking behind each one. In this installment, partner Camille Manso dives into Pilot Studio, a fast-track framework designed to help corporates move from pilot to production with AI. With 88% of AI pilots reportedly never making it past the testing phase, Camille explains why many approaches are broken, how Pilot Studio is engineered for real-world ROI, and why getting AI right is less about algorithms and more about people, process, and speed.
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Let’s start with the “why.” What inspired Silicon Foundry to create Pilot Studio?
Over the last decade, we’ve been helping corporates navigate what we call the $3 trillion open innovation economy, matching them with the right startups for partnerships, investments, or acquisitions. But then came the new AI era. Suddenly, every client wanted to engage with AI startups, but they kept running into the same wall: pilots that dragged on for 18 months and rarely scaled. One stat that really stood out to us was that over 88% of AI pilots never make it to production.
The pace of AI innovation is accelerating far faster than corporate internal processes can handle. The traditional corporate pilot model just wasn’t built for this kind of technology. That’s why we launched Pilot Studio, to take our expertise in startup engagement and layer in a repeatable, de-risked, and accelerated model for AI adoption—one that actually works inside the realities of large enterprises.
Why do you believe Pilot Studio is particularly relevant right now?
The timing is urgent, and corporations as well as individuals feel the pressure to adapt as headlines focus on how AI will replace jobs, and even companies as they exist now. In short, speed now beats size. On the plus side, we do believe incumbents are positioned to win because they often have decades of proprietary data, know-how, and established reach across loyal customers and partners. It’s a matter of activating those jewels in an AI-first world.
What we hear from leaders is simple: “We can’t afford to get stuck in another two-year pilot that goes nowhere.” Pilot Studio gives them a path to experiment quickly, validate real ROI, and scale what works, without risking millions before they’ve proven value.
In your own words, how would you explain the impact Pilot Studio has on corporate leaders?
The biggest question around AI right now is whether there’s real ROI behind the hype. Pilot Studio puts ROI at the center. We actually introduced an early prototyping stage designed to fail fast, cheaply, and learn quickly. Instead of betting big upfront, we help leaders refine the business problem, clarify success metrics, and validate value before committing real dollars. That confidence to act – and act quickly – is the core value proposition of Pilot Studio.
What’s a misconception people often have about Pilot Studio?
One of the biggest misconceptions is: “We already know how to run pilots. Our problem is scaling.” What we have found since launching Pilot Studio is that how you run the pilot directly impacts your ability to scale. We build the conditions for scale during the pilot phase, not after. That means engaging stakeholders across functions, building champions early, aligning KPIs to real business outcomes, and hardwiring change management into the process from day one.
Simply put: if you wait until after the pilot to think about scale, you’re already behind.
Can you share a favorite anecdote or example where this offering really made a difference for a client?
One financial services client in the Middle East stands out. They had the ambition, but were paralyzed by choice: twenty-plus startups, multiple business units competing for attention, and no clear path forward. In six months, we helped them source, vet, and execute more than 20 pilots across AI-driven credit scoring, personalization, and training. What normally would have taken 18 months, we compressed into three. More importantly, they didn’t just “run pilots,” they built an internal AI operating rhythm they now own.
What’s something you personally learned or found surprising while building or delivering Pilot Studio?
Honestly, just how critical the human element is to AI adoption. The models, data, and algorithms are important, but if the business doesn’t trust the output, if legal won’t sign off, or if change management isn’t baked in early, even the best AI solution stalls. Successful AI pilots are as much about people, culture, and governance as they are about technology.
How do you see Pilot Studio evolving in the next 12–18 months?
We’ll get even faster. As we accumulate pattern recognition across industries, use cases, and AI solution types, we’ll help clients skip steps they used to struggle through. I also see us moving deeper into implementation as more corporates build confidence running multiple AI pilots in parallel. Eventually, Pilot Studio won’t just help them adopt external startups; it will help them operationalize AI as an enterprise-wide capability.
If you could give one piece of advice to a corporate leader considering Pilot Studio, what would it be?
Don’t apply your traditional software procurement playbook to AI. This isn’t ERP. AI solutions evolve as you test them. The organizations winning in AI are those willing to start small, experiment, and refine the problem statement as they go. The only way to build that muscle is by doing it, with the right governance guardrails in place.
What excites you most about working in this space?
There’s so much noise right now between GenAI, Agentic AI, and every other acronym. We get to cut through the noise and actually see what works inside real enterprise environments. Every pilot gives us another data point on what’s possible, what’s overhyped, and where real value creation is happening. That learning cycle is what keeps it fun and makes the work feel incredibly relevant.
