New research · September 2026

See where pharma is really putting AI to work.

The Ariya Pharma AI Landscape 2026 analyses 47 named Commercial and Medical AI deployments, from Sanofi, Pfizer, Novartis and GSK to mid-sized companies like KalVista and Norgine. What each one does, where they cluster, and what companies can actually prove.

Cover of the Ariya Pharma AI Landscape 2026 report

The full map of 47 deployments across 3 categories and 10 use cases
The six workflow steps where AI is concentrating
Why adoption numbers mislead, and what to measure instead

Free report · 35 pages · PDF

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47: named pharma AI deployments
84: evidence records reviewed
10: Commercial & Medical use cases
40: cited sources, all checkable

A preview of the findings

Pharma isn't automating end to end. It's fixing bottlenecks.

Across all 47 cases, companies apply AI where work slows down: finding information, sorting evidence, prioritising HCPs, preparing interactions, drafting content and checking it before approval. Three patterns stand out.

Knowledge work leads, by a wide margin.

Knowledge & Intelligence28

Sales & HCP Engagement14

Content Creation & Approval5

Almost 60% of deployments help people find and interpret information. The largest single use case is Medical & Scientific Intelligence, with 12.

Four companies make up 20 of the 47.

8deployments from Sanofi alone, more than any other company

Sanofi, Pfizer, Novartis and GSK dominate the public record. But mid-sized companies show that narrow, focused use cases don't require enterprise-wide platforms.

Adoption is reported. Value rarely is.

“Adoption is an input measure. It tells us that people opened the tool, not that the company made a better decision.”

User numbers and satisfaction scores appear regularly. Revenue, profit, medical quality and better decisions are rarely reported.

In the full report

The rest is in the full report.

All 47 deployments, named. Company, solution and what it actually does, from Sanofi Turing and Merck's GPTeal to Pfizer's Charlie.
The ten-use-case taxonomy. Deployment counts for each Commercial and Medical use case, from HCP targeting to MLR pre-check.
The six workflow steps. Find, sort, prioritise, prepare, create, check: the steps where the 47 deployments concentrate.
What companies can prove. The reported numbers, from an 88% cut in manual literature review to 50,000+ users, and how much weight each one can bear.

Unlock the full report

Appendix · The 47 named deployments 47 rows

SanofiTuring

Merck & Co.GPTeal

PfizerCharlie

Roche UKAMII

GSKGiGi

NovartisSherlock

BayerMarket Access board

Boehringer IngelheimiQNow

GenentechDeepsense

+ 38 more deployments in the report

Written for the people deciding what comes next

Not another list of things AI might do. A clear view of what other companies are actually putting into practice.

Commercial & brand leaders

See how peers use AI for HCP targeting, next best action, field support and coaching.

Medical Affairs

Benchmark medical information assistants, literature monitoring and scientific intelligence.

Insights, CI & Market Access

Understand where knowledge and intelligence tools are heading, and where the gaps are.

Digital & AI leads

Build the business case on what has been shown in practice, not on vendor promises.

How we built it

Named companies. Real deployments. Sources you can check.

We reviewed 84 evidence records and counted only deployments with a named pharma or biotech company, a specific Commercial or Medical use case, and a tool reported as live, rolled out or in a real-world pilot. Broad platform announcements, future commitments and anonymous case studies were excluded.

The report cites 40 sources, from company announcements to partner case studies and reputable reporting. Two of the 47 cases, Galderma and KalVista, were delivered by Ariya. The report discloses this and documents them from first-hand project records.

Some Ariya customers