Look at tomorrow's track list and count the rooms that have absolutely nothing to do with engineering. Go ahead, I'll wait.
Thursday’s schedule is running 12 parallel tracks. The AI in Healthcare, AI in Finance, and AI in GTM are brand new this year. On top of that, there are entirely dedicated audiences for founders, researchers, and data buyers. Trust me, that is not a scheduling decision. That is a deliberate segmentation decision that reflects where this industry is headed.
For three years, this conference spoke to one very specific audience: the AI engineer. The person writing the agent, wiring the retrieval pipeline, running the eval suite. That audience built a discipline from scratch and gave it a name. But this year, the organizers looked at who was actually hitting the registration page. People from companies like Vanguard, CVS Health, Intuitive Surgical, Two Sigma, Capital One, and more. It’s a marked expansion and a recognition of AI engineers existing not just at tech companies but in other areas of work as well.
Tomorrow's Healthcare track is running sessions on diagnostics, drug discovery, clinical workflows, and regulatory constraints. Finance covers trading, risk assessment, fraud detection, and compliance. GTM sits right next to both of them. These aren’t fluff panels about "the future of AI.” They are actual, practical working sessions for people who need AI to clear a compliance review, reduce false positives in a fraud model, or shorten a sales cycle. These are people who do not care what framework you used.
This is what real adoption looks like when it stops being theoretical. It’s not a bigger model or flashier demo. It’s a room full of clinicians, traders, and go-to-market operators who showed up because the tool finally got specific enough to matter to them.
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