For the past several years, the global conversation on Artificial Intelligence has been dominated by spectacle. We have been captivated by the seemingly magical capabilities of large-scale generative models and the sheer computational power of the advanced chips that train them. This focus on the “magic show” has created a critical blind spot.

At B9F7 Parvis Trust, our thesis is built on a simple, foundational truth: AI is not magic; it is a data-driven utility. And like any utility, its value is entirely dependent on the quality of its “plumbing.”

The single greatest barrier to the next wave of economic transformation—the deep integration of AI into the core of the enterprise—is not a shortage of models or a lack of compute power. It is a crisis of data.

For decades, corporations have accumulated vast, messy, and siloed “data swamps.” Information is trapped in legacy databases, unstructured documents, and disparate cloud applications. This data is often incomplete, unverified, insecure, and non-compliant. The “garbage in, garbage out” principle has not been repealed; it has been dangerously amplified. When an AI is trained on flawed data, it does not just fail—it fails with catastrophic, high-speed confidence, embedding bias, leaking proprietary secrets, and “hallucinating” false information.

This is where the real work, and the real investment opportunity, lies. The future of AI is not in the model; it is in the “data foundation” that feeds it. We are shifting from a “model-first” world to a “data-first” world.

Our investment thesis is focused on this unglamorous but essential “plumbing.” This is the new, critical layer of infrastructure that we call the Data Foundation, which itself sits at the nexus of our core sectors: AI, Data Security, and Infrastructure.

This opportunity is threefold:

1. The New Infrastructure: Data Governance and Control Before data can be used by an AI, it must be found, cleaned, and governed. The most valuable companies of the next decade will be those that provide the “data fabric” and “data mesh” solutions. This is the software and infrastructure that creates a single, secure “control plane” for all of an enterprise’s data, no matter where it lives. It is the only way to know what data you have, who can access it, and whether it is fit for use.

2. The New Security: AI-Native Data Security In the old paradigm, we protected the perimeter. In the new paradigm, where data is constantly moving to and from AI models, we must protect the data itself. This requires a new, AI-native security model built on a “Zero Trust” framework. We are investing in the platforms that can anonymize, encrypt, and audit data in real-time as it is being ingested by an AI, ensuring that intellectual property is protected and that strict legal frameworks, like the EU’s GDPR, are never breached.

3. The New Education: The Rise of the Data-Centric Leader Our Education thesis is also critical here. The world is full of “AI strategists” who cannot answer the most basic question: “Is your data ready?” We are investing in the new educational models that are training a hybrid class of leaders—executives who are fluent in both business strategy and the technical realities of data integrity.

The public will remain focused on the spectacle. We will remain focused on the foundation. The most durable, long-term value in the AI revolution will not be captured by the creators of the magic, but by the architects of the plumbing.