Hello there,
For the past two years, the conversation around artificial intelligence has been dominated by one question: which model will win?
OpenAI. Anthropic. Google. Meta.
Investors have poured billions into the companies building frontier models, while enterprises have spent much of that time experimenting with how to use them.
But the next competitive advantage may no longer come from building better models, but from helping businesses deploy them. This week, Anthropic, Blackstone, and Hellman & Friedman officially launched Ode, a standalone AI services company created to help enterprises move beyond experimentation and into implementation.
At first glance, you might think this looks like just an AI startup. It isn't. Its cap table includes some of the world’s largest alternative asset managers and institutional investors. Its origins lie not in Silicon Valley, but in a problem identified across private equity portfolios. And its ambition extends beyond consulting: to become the infrastructure layer that connects frontier AI models to enterprise adoption.
If that model succeeds, it may tell us less about Anthropic’s strategy than about where private capital believes the next phase of AI value creation will emerge.
The Next Bottleneck Is Infrastructure
For much of the AI boom, success appeared to depend on building the smartest model. However, the constraint is no longer intelligence. It’s implementation.
Most large companies no longer question whether AI can create value. The challenge is integrating it into existing workflows, products, and decision-making processes. That requires redesigning business operations, connecting AI to proprietary data, managing security and governance, and building entirely new software systems around foundation models.
In other words, AI adoption has become an engineering problem rather than a model problem. That is the gap Ode has been created to address.
Built on top of Fractional AI, the applied AI engineering firm Anthropic acquired earlier this year, Ode aims to provide enterprises with highly specialized engineering teams capable of turning frontier AI into operational systems.
The New Scarcity Is Applied AI Talent
The company grew out of Fractional AI, the applied AI engineering firm Anthropic acquired earlier this year. Rather than selling software licenses, Ode builds teams of experienced engineers who work alongside enterprises to redesign products, automate workflows and integrate AI into core business processes. Today, the company employs around 100 engineers, more than half of whom are former founders.
The emphasis is telling.
Ode’s executives argue that choosing a model is only one component of enterprise transformation. The harder work lies in redesigning processes, integrating proprietary data, and building systems that can operate reliably at scale. Model quality matters, but implementation increasingly determines business value.
The Cap Table Says As Much As The Product
Perhaps the most interesting part of Ode isn’t the engineering but the ownership. Alongside Anthropic, the company is backed by Blackstone, Hellman & Friedman, Goldman Sachs, General Atlantic, Apollo, GIC, Sequoia Capital and Leonard Green & Partners. That is an unusual investor group for what is, on paper, an AI services company.
The explanation lies in how Ode was created.
According to TechCrunch, Blackstone conceived the business after struggling to deploy AI consistently across its own portfolio companies. Traditional consulting firms proved too broad. Boutique AI consultancies proved difficult to scale. Fractional AI stood out, and instead of becoming another supplier, it became the foundation of an entirely new company.
The broader implication is that private equity firms may no longer be satisfied with funding AI adoption. They are beginning to build the infrastructure that enables it.
Private Equity Is Becoming an Ecosystem Builder
Historically, private equity created value by buying companies, improving operations, and exiting at a higher valuation.
AI may be changing that playbook.
Instead of treating AI implementation as another operational initiative inside portfolio companies, firms are beginning to build dedicated platforms that can serve entire portfolios and eventually the broader market. Ode is a clear example. Rather than hiring another consulting firm, Blackstone helped create a standalone company after identifying a common implementation challenge across its investments. In effect, it transformed an internal operational need into a scalable business.
According to Deloitte's latest State of AI in the Enterprise report, worker access to AI increased by 50% during 2025, and the number of organizations with at least 40% of AI initiatives in production is expected to double within six months.
Yet only 34% of companies say they are fundamentally reimagining their business around AI. The gap is no longer access to models; it is the ability to redesign workflows, integrate data, and deploy AI at scale.
That explains why implementation is becoming strategically important. Frontier AI labs such as Anthropic and OpenAI are building dedicated deployment businesses, while consulting firms including Deloitte, Accenture and McKinsey are expanding AI engineering teams to help clients operationalize the technology. The competition is no longer centered solely on who builds the most capable model. It is increasingly about who can translate that capability into measurable business outcomes.
Two decades ago, the biggest opportunity wasn't simply creating better software; it was building the infrastructure that enabled every enterprise to adopt it. Today, AI implementation is emerging as a similar layer.
For private equity, that could represent more than a new operating capability. It could become a new platform strategy, where value creation comes not only from owning AI-enabled businesses, but from owning the infrastructure that allows entire portfolios to adopt AI faster and more effectively.
We Continue The Conversation at 0100 Emerging Europe
If AI is entering an era of implementation, investors face a different set of questions. Which AI applications are delivering measurable returns? Where are enterprises moving beyond pilots? And how should LPs and GPs distinguish lasting value creation from another wave of AI hype?
We’ll continue that conversation at 0100 Emerging Europe 2026 in Budapest (23–24 September). The discussion will focus on enterprise adoption, vertical AI platforms, valuation in an increasingly crowded market, and how investors can identify companies that are creating durable competitive advantages rather than simply demonstrating technical capabilities.
Joining the panel are investors who have spent years backing technology companies through multiple market cycles. Together, they’ll explore where AI is creating real enterprise value, how implementation is reshaping investment opportunities, and what investors should be watching as the next phase of AI adoption unfolds.