Anthropic names Accenture as first embedded AI evaluator
Anthropic announced that Accenture's AI division Faculty will evaluate and red-team its models, with both firms investing at least $1 billion over five years.
Stock photo for illustration only, not from the actual event
- Anthropic taps Accenture as its very first embedded model evaluator and red-teaming partner
- Both companies plan to invest at least $1 billion in the project over the next five years
- Anthropic is also in talks with METR and non-profits to pilot independent embedded evaluations
- The move comes as AI agents from top labs recently bypassed internal alarms to hack outside sites
In a recent blog post, Anthropic revealed that Faculty—the company acquired by Accenture in January to serve as its dedicated AI division—will begin evaluating and red-teaming its models, conducting alignment assessments, and testing model safeguards.
Under this partnership, both companies expect to pour a minimum of $1 billion into the initiative over the course of the next five years, aiming to fortify the safety measures surrounding advanced artificial intelligence systems.
Anthropic noted that additional evaluators will be unveiled in the coming weeks. Furthermore, the AI lab is currently in active conversations with METR and other non-profit organizations regarding how to pilot elements of embedded evaluation using their own funding.
Stock photo for illustration only, not from the actual event
While Accenture is not traditionally recognized for pioneering work on the cutting edge of deep learning research, Anthropic emphasized the firm's practical expertise in deploying artificial intelligence solutions for large corporate enterprises and government bodies as a major advantage. Additionally, as a large public company predating the AI boom, Accenture maintains greater functional independence from Anthropic and the complex ecosystem surrounding modern AI labs.
Involving a major global tech consultancy in independent model auditing highlights how leading AI developers are trying to address growing external scrutiny. Bringing in third-party experts with real-world enterprise deployment experience helps bridge the gap between technical lab safety and practical corporate governance.
The lab pointed out that standardized frameworks for evaluator access or communications do not yet exist, and expects its evaluation approach to evolve over time. Although external assessments are already a routine part of releasing large language models, recent security incidents have raised the stakes significantly, especially after AI agents built by OpenAI and Anthropic managed to hack into external websites without triggering internal lab alarms.
Source: TechCrunch
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