The Untapped Opportunity in AI Services

The conversation around AI is often dominated by the frontier: new models, bigger benchmarks, faster performance. But in many ways, the real opportunity isn’t at the bleeding edge—it’s in the gap between those models and the organizations struggling to adopt them.

A Tier 1 venture capital firm recently shared their thesis on this “AI services” market. While we’re not pursuing investment right now, their perspective crystallized something we’ve been seeing on the ground:

👉 AI models are advancing faster than the talent and know-how to integrate them.

The Talent Bottleneck

Frontier models are evolving at breakneck speed, but the number of people capable of helping enterprises implement them is limited.

• Top engineers are clustered in Y Combinator startups, major tech firms, and AI labs.

• Few operators bridge both worlds—the technical depth required to use AI effectively, and the human-centered skills needed to build trust, map workflows, and guide adoption.

It’s telling that OpenAI itself launched a consulting arm. If the model provider feels compelled to step into services, it shows how big this gap has become.

Why Traditional Consultancies Are Struggling

Large firms like Accenture, PwC, and McKinsey are positioned as natural players in this space, but they’re constrained by structural realities:

• Long procurement cycles delay the adoption of AI tools internally, slowing their own teams down.

• Bloated delivery structures require maintaining large teams even when AI could do the work more efficiently.

• Pricing pressures force them to inflate fees to sustain margins, leaving enterprises frustrated.

The result? Many organizations eager to explore AI are left paying more for slower, less efficient outcomes.

The Case for a Leaner Model

Lean AI services firms can operate differently:

• Faster adoption cycles: new tools and workflows integrated without procurement bottlenecks.

• Smaller, specialized teams: fewer people, but with the right mix of technical depth and human problem-solving.

• Better economics: pricing 30–50% lower than large firms while sustaining ~50% margins.

This balance—efficient delivery with sustainable margins—is exactly what enterprises have been missing. It’s not about undercutting; it’s about aligning pricing with value delivered.

External Validation

Hearing this perspective from a leading VC was validating. They’ve synthesized what many of us are experiencing in the field: dozens of small experiments across industries pointing to the same narrative.

• Customers have already confirmed the need for practical AI services.

• Institutional investors are now highlighting it as one of the defining opportunities of the next wave.

That alignment underscores the size of the opportunity—and the urgency for organizations to explore it.

Closing Thought

The story of AI isn’t just about bigger models. It’s about whether businesses can actually adopt them. Right now, the demand for practical AI integration far exceeds the supply of talent that can deliver it.

The firms that succeed in this space will be the ones that combine technical expertise with human-centered consulting skills, operating with the lean efficiency enterprises need.

The models are ready. The gap is in services. And that’s where the next wave of value will be created.