OpenAI CEO Sam Altman speaks in San Francisco about the future of AI and its growth plans.
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OpenAI’s new $10 million+ AI consulting offering proves one thing: in 2025, the edge in AI is in its deployment — not just its access. This move appears to be borrowed from Palantir’s two‑decade‑old playbook, signaling the ascent of AI deployment‑as‑a‑service as the next transformative frontier.
From API Access to Execution Edge
Historically, AI firms competed by offering the most powerful LLMs via API access. But as this post points out, “the power is not in the LLM, it’s a commodity. It’s all about how you execute it.” Palantir knew about this playbook two decades ago: it knew its profits come not from software benchmarks but from embedding consultants and engineers into client operations to integrate their software to drive business outcomes.
Now, OpenAI is replicating that playbook. OpenAI’s offering starts at $10 million for enterprise-grade GPT‑4o deployments, staffed with forward‑deployed engineers embedded in client workflows. Early adopters reportedly include the U.S. Department of Defense and Southeast Asia’s Grab.
Why Consulting Margins Trump API Margins
API license fees may seem lucrative, but consulting generates “sticky” margins. Deep-pocket consulting engagements can yield margins of 40%–60%, compared to much lower SaaS‑style API margins.
Henri Terho put it succinctly: “Models and AI is not the problem, it’s the deployment, integration, user access… consulting margins beat API margins.”
This is a pivotal change. As more clients demand not just access but complete integration, execution becomes the competitive moat.
OpenAI Vs. Palantir: Strategy in Action
Palantir’s DNA has always been embedded deployment. The company achieves over 40% free‑cash‑flow margins by integrating deeply into mission‑critical operations, delivering sustained business outcomes.
OpenAI took a chapter from this playbook and is now investing in the same high‑stakes consulting playbook. And now, OpenAI’s move is is having ripple effects across the industry:
Google, Meta, Anthropic and others are racing to augment their tools with deep deployment offerings.
IT consultancies like Accenture and HCLTech are formalizing AI‑services partnerships, such as HCLTech’s deal with OpenAI to drive enterprise adoption.
The challenge now for AI startups and incumbents alike is to pivot from model‑led commodification to outcome-driven integration.
So for the rest of the market, such as AI builders, enterprise buyers, investors and analysts, what are the recommendations? Below is a list of suggestions based on the latest news:
For AI Builders
Design for deployment: architect models, APIs and UI front‑ends that support full‑stack integration with client systems from day one.
Invest in on‑site capability: build or partner for delivery teams equipped to manage real‑world AI rollouts, change management and governance.
For Enterprise Buyers
Demand deployment plans: ask vendors not only “show me a demo” but “who stays when the model breaks or needs scaling in your systems?”
Budget for transformation, not tools: embed consulting and support into procurement decisions — because AI success hinges on execution, not just tech.
For Investors and Analysts
Reassess valuation models: companies that integrate and deploy AI — mirroring Palantir’s consulting‑anchored margins — may merit higher multiples.
Track deal signals: early government and enterprise contracts (like OpenAI’s $200 million DoD deal) signal a broader financial pivot in the AI market.
OpenAI’s Forward Pivot
OpenAI’s $10 million+ AI consulting division is more than a premium price tag — it’s a strategic pivot onto a path where every company adopts AI, with no excuses. As every AI model becomes a commodity, execution now becomes the determining factor for success. This pivot in its playbook will rewrite the rules of AI competition and implementation.
In today’s AI arena, execution is the differentiator, not the API. Welcome to the era of AI deployment‑as‑a‑service.