AI model "capability overhang" biggest challenge facing European businesses, says OpenAI revenue chief
Summary
OpenAI's Vice President of Enterprise, Ashley Kramer, states that a "capability overhang" is the biggest challenge for European businesses adopting AI. This refers to the gap between the rapid advancements and utility of AI models and enterprises' ability to successfully deploy and extract value from them. European businesses, particularly in Germany, France, and the UK, are among OpenAI's top global adopters, transitioning from pilot projects to deep AI integration. To address this, OpenAI launched a new business unit, the OpenAI Deployment Company, which includes the acquisition of applied AI consulting firm Tomoro. Tomoro's 150 forward-deployed engineers will embed within businesses to enhance model productivity. This initiative also involves partnerships with 19 investment and consultancy firms, including Bain, Goldman Sachs, and SoftBank, aiming to help customers like Virgin Atlantic, BBVA, and Novo Nordisk fully leverage AI.
Key takeaway
For Directors of AI/ML overseeing enterprise-wide AI transformation, recognize that simply adopting advanced models is insufficient. Your teams must prioritize dedicated resources for value extraction to overcome the "capability overhang." Consider integrating specialized AI deployment expertise, potentially through partnerships or embedded consultants, to bridge the gap between model utility and tangible business impact. This proactive approach ensures your AI investments yield their full potential, moving beyond pilot phases into deep operational integration.
Key insights
European businesses face a "capability overhang" in AI adoption, struggling to extract full value from rapidly advancing models.
Principles
- AI model utility outpaces enterprise deployment.
- Deep AI integration requires specialized support.
- Value extraction is key to AI transformation.
Method
OpenAI's method involves acquiring Tomoro, an applied AI consulting firm, to embed 150 forward-deployed engineers within client businesses. These engineers help close the gap between model capabilities and extracted value, boosting productivity.
In practice
- Embed specialized AI engineers for deployment.
- Partner with consulting firms for AI integration.
- Target digital native, healthcare, finserve sectors.
Topics
- AI Deployment
- Enterprise AI
- OpenAI
- Capability Overhang
- Value Extraction
- Applied AI Consulting
Best for: CTO, Executive, Investor, Director of AI/ML, VP of Engineering/Data, Consultant
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Editorial summary, takeaway, and curation by AIssential. Original article published by Tech.eu - Tech.eu.