Why We Built AI NOW: The Case for a Firm, Not a Freelancer

Enterprise AI isn't a one-person job. Here's what my co-founder Cheryl Dopp and I set out to build — and why we did it together.

When Cheryl Dopp and I started AI NOW, we made a deliberate choice: this would be a firm, not a solo practice.

That distinction matters more than it sounds. The market is flooded with individual AI consultants — many of them talented, some of them excellent. But enterprise AI is not a one-person problem. It sits at the intersection of data architecture, governance, cloud infrastructure, business strategy, regulatory context, and organizational change management. No single practitioner covers all of that credibly. And when the engagement stakes involve Fortune 500 data and regulated industries, the gap between "consultant" and "firm" becomes existential.

The problem we kept seeing

Cheryl has spent nearly three decades inside the data layers of banks, insurers, healthcare systems, federal agencies, and media companies. What she kept observing — and what became the founding thesis of AI NOW — is that enterprise AI initiatives almost never fail at the model. They fail at the data foundation beneath the model. Roughly 95% of enterprise AI pilots never reach production, and the reasons are almost always the same: fragmented definitions, weak governance, master data chaos, architectural debt, and organizational misalignment about what "AI-ready" actually means.

Meanwhile, the market response has been to hire more data scientists and buy more AI platforms. Both help. Neither addresses the underlying problem.

Why a firm, not a freelancer

We built AI NOW as a small, deliberate firm because the work requires two things simultaneously:

Depth of enterprise data experience — the kind that only comes from having built and stabilized data platforms inside dozens of Fortune 500 environments. That's Cheryl's core.

Modern platform, delivery, and operating-model expertise — cloud-native architectures, semantic layers, vector infrastructure, and the operational discipline to actually ship. That's where I come in.

Together, we can walk into an AI readiness engagement and cover the full stack: strategy, architecture, governance, platform selection, and delivery — without handing the client off between three vendors, four consultants, and a systems integrator.

What we're building

AI NOW is intentionally small and senior. We're not scaling into a body-shop consultancy. We're building a firm that can be trusted with the most sensitive parts of an enterprise's data foundation — the parts that determine whether an AI initiative becomes a production system or a very expensive slide deck.

If you're a Chief Data Officer, VP of Data, or Head of AI at a mid-to-large enterprise wrestling with the gap between AI ambition and data reality — that's exactly the conversation we're built for.

More thinking to come.

— Nikita Khlopchatnikov
Co-Founder, AI NOW