Thenextweb iconThenextwebSep 23, 2026 ~3 min source read

OpenAI’s Colin Jarvis: enterprise AI stalls on deployment, not models

Colin Jarvis, head of OpenAI’s forward deployed engineers, says roughly 80% of enterprise AI failures come from rollout and governance problems. He describes what FDEs do inside customers, common pilot mistakes, and how successful projects scale.

OpenAI’s Colin Jarvis says enterprise AI is stuck on deployment, not models

Share this story

Send the public story page.

Useful takeaways from this story.

About 80% of enterprise AI problems are deployment-related — governance, rollout, trust — not model capability.

Forward deployed engineers (FDEs) embed with customers to convert proofs of concept into production and measure success by live usage and real metrics.

Common failures: picking use cases because they fit AI rather than because they matter, and keeping solutions as localized demos that never scale.

# What Jarvis said and why it matters

# What FDEs do inside companies

Engagements start with a two-day visit where FDEs ask business leaders to ignore AI and describe the biggest levers in their business. The team then targets whichever lever matters most, not the most AI-friendly use case.

# Concrete examples

  • Clinical trials: a system helps draft trial documents while keeping a human in charge of approvals.

# Why pilots fail Jarvis named two frequent mistakes:

  • Choosing a use case because it looks like a fit for AI rather than because it moves a meaningful business metric.
  • Letting a successful pilot remain a demo inside one department instead of moving it into production and other units.

He contrasts this with a semiconductor customer that had about 35 live use cases after roughly 18 months because it built a central team to scale projects and placed small engineering groups in each business unit.

# How success is measured FDEs are judged on whether a project reaches production and moves real metrics, not on usage revenue or adoption incentives. Jarvis says OpenAI has no financial incentive tied to usage. When OpenAI's embeddings were too slow for a Klarna search service, he advised using an open-source model instead, stressing that OpenAI should act as a temporary solution when appropriate.

# Safety, pace, and testing frameworks Jarvis noted OpenAI has shown it will pause work when safety frameworks have reached their limits. He said the company paused a main reinforcement learning run "in September this year" and that OpenAI published a post on 18 August describing a two-week pause in reinforcement learning training on its latest models. He also said FDEs help test whether safety frameworks that work in labs hold up in messy, real-world company environments.

# Market context Other large providers use similar deployment models: AWS has invested about $1bn in comparable on-site engineering, and Microsoft launched a $2.5bn deployment business in July.

# Bottom line

More context around this story.

The most valuable part of AI may not be the model
E27 iconE27Sep 9, 2026

The most valuable part of AI may not be the model

Throughout 2026, Claude users repeatedly reported the same practical failure: workflows that had worked reliably stopped working, long sessions lost their thread, and instruction-following became less dependable. The complaints did not arrive as a smooth decline. They came in bursts. Users would suddenly report that a

Моделей больше недостаточно: зачем OpenAI запускает DeployCo с $4 млрд инвестиций
Computerra iconComputerraSep 3, 2026

Моделей больше недостаточно: зачем OpenAI запускает DeployCo с $4 млрд инвестиций

Источник: Компьютерра - Журнал о науке и технологиях За одну неделю мая 2026 года две крупнейшие ИИ-лаборатории объявили о запуске сервисных компаний. Сначала Anthropic вместе с инвестиционными партнерами создалакомпанию для работы со средним бизнесом. Через семь дней OpenAI представила OpenAI Deployment Company, или D

Loading more related stories...

Keep reading in the app

Open the app view to save this story, compare related coverage, and continue from the same source.

Open in app