The Deployment Company, Back to the 70s, Apple and Intel

2026-05-13 · Source: Stratechery by Ben Thompson · Field: Business & Management — Corporate Strategy & Leadership, Operations & Process Management, Consulting & Professional Services · Depth: Intermediate, long

Summary

OpenAI has established a new entity, the OpenAI Deployment Company, with over $4 billion in initial investment, aimed at assisting organizations in building and deploying AI systems. This new venture, majority-owned by OpenAI, will acquire AI consulting firm Tomoro, bringing approximately 150 experienced AI engineers and deployment specialists. Concurrently, Google Cloud plans to hire hundreds of "forward deployed engineers" to help customers adopt its business-focused AI products, forming a new team within Google Cloud. These moves by major tech companies reflect a broader industry trend towards providing extensive human support and consulting partnerships to facilitate enterprise AI adoption, drawing parallels to the mainframe computing era of the 1970s where top-down enterprise implementations drove significant business process re-engineering.

Key takeaway

For CTOs and enterprise architects evaluating AI integration, recognize that successful large-scale AI deployment is not a plug-and-play solution. Your teams will need significant "boots on the ground" engineering and consulting support, akin to past mainframe implementations, to fundamentally rethink business processes and prepare data. Factor in these human capital requirements and potential partnerships with specialized deployment firms when budgeting and planning your AI strategy to avoid underestimating implementation complexity.

Key insights

Major AI developers are deploying human engineering teams to facilitate enterprise AI adoption, mirroring 1970s mainframe implementations.

Principles

• Enterprise AI adoption requires significant human integration.
• AI's impact on business processes resembles mainframe era changes.

Method

OpenAI's strategy involves embedding specialized engineers into client organizations and acquiring consulting firms to scale deployment capabilities, focusing on executive-level business process rethinking.

In practice

• Consider AI for top-down enterprise process re-engineering.
• Prioritize data preparation for effective AI agent deployment.

Topics

• OpenAI Deployment Company
• Enterprise AI Adoption
• Forward Deployed Engineers
• AI Business Transformation
• Apple Intel Chip Deal

Best for: Investor, CTO, Executive, Director of AI/ML, VP of Engineering/Data, Consultant

Related on AIssential

• OpenAI Just Created a Whole New Company for AI Businesses — OpenAI is shifting to direct AI integration services, bridging the gap between model access and effective enterprise deployment.
• Economist Enterprise: How Leading Firms Make AI Deliver — Successful AI adoption requires organizational change, disciplined execution, and continuous governance beyond initial deployment.
• Executive Briefing: Your company is about to get cheap intelligence. That is not the same as being able to use it. — The real scarcity for companies is not AI intelligence, but the internal structure and capability to apply it effectively.
• OpenAI allies with 4 big consulting giants as the agentic enterprise battle heats up — Strategic consulting partnerships are key to scaling enterprise AI agent adoption and overcoming implementation barriers.
• Why OpenAI and Anthropic Are Becoming Consultants — Organizational transformation is critical for successful AI deployment, as individual AI capabilities often outpace enterprise readiness.
• OpenAI launches DeployCo to help businesses build around intelligence — Effective AI deployment requires specialized engineers to integrate frontier AI into critical business workflows for measurable impact.

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Editorial summary, takeaway, and curation by AIssential. Original article published by Stratechery by Ben Thompson.