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Causal AI sounds like another buzzword until someone explains what it actually does. Enter Hitesh Wadhwani, who may have been GM of Alembic for just three weeks when we spoke at Possible 2026, but came from 12 years at Google building measurement products including Google Meridian! He knows a little something about marketers having a ton of data but with less confidence in what it means. But Hitesh has a specific answer to that problem and it’s why he joined Alembic and its solution using causal AI.
Hitesh wrote in his LinkedIn post explaining his new role: “You cannot hallucinate your way through a multimillion-dollar strategic budgeting or pricing decision.” As he puts it, LLMs were designed to predict the next word, not the next number so aren’t really up to the task of enterprise-level measurement. But that’s what CAUSAL AI was built for.
The idea is to build a real-time graphical representation of your entire enterprise: every marketing channel, pricing decision, promotion, and inventory movement as interconnected nodes.
The model then identifies not just what happened, but what caused it, with enough granularity to answer the question every CMO and CFO is actually asking: did that campaign drive sales, and how do we know?
The operative words there are “CMO and CFO” and their sometimes cavernous gap in like mindedness. The core problem is that brand teams, performance teams, and measurement teams are all approaching the same business with different methodologies and incompatible metrics. Hitesh says Alembic’s framework puts everything in the same causal graph, translated into language a CFO can engage with. And yes — even creator marketing and influencer data go into the model, as long as you have the data to represent them.
One case study Hitesh shares was around Delta’s heavy investment in Olympic campaign spend. You’ll hear him explain the challenges in assessing Olympic-sized investments in general, but Alembic’s model was able to identify exactly what moved the needle. Causal AI was able to show, at a moment-by-moment level, that the placement of the brand logo during the medal ceremony drove more flights to Paris than any other moment in the entire campaign. CMO and CFO can enjoy that a logo, in the right place, at the right emotional moment, put them on the winner’s platform.
Three weeks into his new role, Hitesh is like a kid in a candy shop, especially with #NVIDIA as a compute partner and a brand-new supercomputer in the building.
Listen/Watch for how to leverage the latest in AI-workflows in what’s our brave new world of marketing. Then catch the other three “POV: Possible” episodes in this mini-series with other fascinating companies who are herding cats, or at least bots!
Key Moments:
0:02:34 — From Google Meridian to Alembic: Hitesh Wadhwandi’s measurement career that led to this moment
0:03:08 — Why LLMs weren’t built for enterprise data — and what causal AI does instead
0:05:35 — How causal AI connects the dots between marketing, pricing, inventory, and sales
0:09:33 — The CMO-CFO gap — and how one shared measurement framework closes it
0:10:37 — A case study that proved out a multi-million dollar investment — at moment-level granularity
0:16:33 — Creator marketing, influencer data, and what the model needs to measure it all
0:18:46 — What’s next: NVIDIA, a new supercomputer, and Alembic’s road ahead
CONNECT WITH:
Alembic: https://alembic.com/
Hitesh Wadhwani: https://www.linkedin.com/in/hiteshwadhwani-google/
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