Link to the latest update below:
update
Key items:
- Based on a16z analysis, 29% of the Fortune 500 and ~19% of the Global 2000 are live, paying customers of a leading AI startup.
- What's working in Enterprise AI - the most indicative way to assess this is to overlay revenue momentum across use cases against the theoretical capabilities of the models as defined by GDPVal, a well-known benchmark from OpenAI which assesses model capabilities on real-world economically valuable tasks.
- Where is the Enterprise AY delivering the most value today - On the revenue momentum, enterprise adoption of AI is dominated by a clear set of use cases and industries. Coding, support, and search represent the lion's share of use cases by far (with coding being an order-of-magnitude outlier even among this set), while the tech, legal, and healthcare sectors have been the industries most eager to adopt AI.
- Separate Industtries and examples:
- Technology: By far the most common industry to adopt AI so far is the tech industry. ChatGPT itself reported that 27 percent of its business users come from
tech, and many of the early customers of companies like Cursor, Decagn and Glean were tech companies. This is wholly unsurprising given tech is almost always
an early adopter and is the industry that spawned the AI wave.
- Legal: Legal was surprisingly one of the first-mover industries in AI. Legal was historically known to be a difficult market for software, with lengthy timelines and
a less tech-forward buyer.
- Healthcare: Healthcare is another market responding to AI in a way it never did for traditional software. Companies like Abridge, Ambience
Healthcare, OpenEvidence, and Tennr have grown tremendously quickly in revenue off the back of discrete use cases like medical scribing, medical search, or back
office automation of the byzantine rules governing how healthcare gets delivered and paid for.
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Todor Kostov
Director
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